Manufacturing Hub

Episodes

• Ep. 260 - Why Ignition Is Winning: Colby Clegg and Carl Gould on SCADA, Open Access, & Industrial AIMay 14, 2026 · 1 hr 10 minInductive Automation cofounders Colby Clegg and Carl Gould go deep on the origins of Ignition, the road to 8.3, and what AI means for industrial automation. Vlad and Dave host Colby Clegg, CEO, and Carl Gould, CTO, of Inductive Automation together for the first time to trace the full arc of the company. The story begins in 2003, when Sacramento systems integrator Steve Heckman brought Colby and Carl in to build the missing glue layer between OT data and modern IT tooling. What began as logging values into SQL databases became Factory PMI and eventually Ignition. A key thread is why Ignition broke through when larger automation vendors had superior distribution. Colby points to Clayton Christensen's Innovator's Dilemma. Incumbents could not match Inductive's unlimited per gateway pricing or partner with integrators because their own services groups competed with them. Carl adds the culture piece. Inductive refused to gate downloads, kept the module SDK open, made education free, and ran a public forum when competitors called it reckless, a posture they once called innovation without permission. Ignition 8.3 takes center stage, arriving after a deliberate five year gap from 8.1. Carl frames it as the completion of work that began with 8.0 in 2018. Gateway configuration is now stored in open, readable formats on disk, the gateway web interface was rewritten, and the platform supports orchestration, environmental separation, and infrastructure as code workflows Carl expects to become table stakes. The release also adds event streams, a revamped historian, and perspective drawing tools. For integrators still on 8.1, 8.3 is the version built for distributed deployments across many gateways. On AI, Carl is candid that the new MCP server module is intentionally a minimum viable product. It ships as a raw toolkit for integrators to author MCP primitives that expose Ignition data to agentic systems like Claude Code. First party MCP tools are coming, but Inductive wants to define the guardrails before shipping an API surface they will support for years. Carl frames AI as a new axis of software possibility, comparable to the shift from DOS to Windows. Colby ties it back to legacy SCADA conversion, framing the security and reliability gains as a national security issue. The episode closes with notes on the Inductive ecosystem, including a new collaboration with Tiger Data behind TimescaleDB, plus career advice on soft skills, context, and agentic coding tools. About Colby Clegg and Carl Gould Colby Clegg is the CEO and cofounder of Inductive Automation, the California based company behind Ignition, the cross platform SCADA, MES, and IIoT software used by manufacturers and integrators worldwide. Carl Gould is the CTO and cofounder, leading product and engineering direction across Ignition. Both joined founder Steve Heckman in 2003 and have shaped the platform's open, integrator first philosophy ever since.<bPlayPlay Ep. 260 - Why Ignition Is Winning: Colby Clegg and Carl Gould on SCADA, Open Access, & Industrial AI
• Ep. 259 - Logan Terry of LSI on Change Management: The Soft Side of SCADA, MES, & ERP ProjectsMay 7, 2026 · 1 hr 8 minChange management decides whether your MES or digital transformation project lasts, or quietly gets shut off six months after go live. Vlad Romanov and Dave Griffith sit down with Logan Terry, who leads digital transformation at LSI, to dig into change management as the deciding factor in any automation or MES rollout. Logan defines change management as a methodical approach to moving an individual, team, or organization from a current state to a desired future state. The closer a system sits to where decisions are actually made, the more change management it requires, which is why MES is the single hardest place to land a project successfully. Much of the episode digs into why change management is rarely scoped properly. In competitive RFPs, the integrator who includes a robust change management line item often loses to the lowest bid, and end users frequently do not know how to evaluate that line item even when it is offered. Logan starts every client engagement with a direct question: what does your continuous improvement practice look like internally? If the client cannot sustain the change after handover, the project is on borrowed time no matter how clean the FAT and SAT looked. Logan walks through one of the most useful failure stories on the show this year. His team delivered a technically perfect OEE dashboard for a production line. Six to nine months later, every terminal was shut off. The postmortem surfaced two missed details. Maintenance was never folded into the design, and a single failed photo eye broke throughput calculations with no manual reconciliation path, which destroyed operator trust in the data. The second miss was behavioral. Showing a 30 percent OEE against a 90 percent ideal demotivates the floor, while reframing the same number as 80 percent of a realistic 36 percent target turned out to be a cleaner motivator. Looking forward, Logan sees vendors moving away from monolithic 14 function MES suites toward modular, use case specific deployments, which compresses change management scope from twenty five workflows to five or six. On AI, he argues that managing generative agents in production is closer to managing a team of people than managing software, with continuous validation replacing one time qualification. He cites the line that AI does not make bad data worse, it makes it more convincing. LSI now uses AI assisted coding agents and React based prototypes to shrink design cycles from three or four weeks of Figma work down to three or four days. About Logan Terry Logan Terry leads digital transformation at LSI, a multinational systems integrator with roughly 400 resources across 13 North American locations and offices in Asia Pacific. A mechanical engineer by training, Logan spent a decade in PLC, HMI, and SCADA development before moving into digital transformation consulting and joining LSI in late 2024. His work spans advanced SCADA, MES, analytics, and BI integrPlayPlay Ep. 259 - Logan Terry of LSI on Change Management: The Soft Side of SCADA, MES, & ERP Projects
• Ep. 258 - Hannover Messe Recap, the State of Industrial AI, and What Comes Next at Automate 2026Apr 30, 2026 · 1 hr 8 minIndustrial AI is moving past the chatbot phase. From the Hannover Messe show floor to system integration workflows, here's what end users actually want now. Vlad just returned from his first Hannover Messe, the largest industrial automation and manufacturing trade show in Europe. The takeaway that defined the week was a shift in how end users open conversations. A year ago, every booth visit started with the question, do you have AI? This year every vendor has some flavor of AI, so the question has flipped back to the one that actually matters. How does your product solve a specific problem in my plant? Vlad and Dave unpack what that shift means for vendors, integrators, and the end users buying these tools. On the end user side, the reality is mixed. Most knowledge workers in manufacturing have access to Microsoft Copilot and use it for better emails and meeting notes. Everything else is still mostly experimentation. While auditing PLC and SCADA logic on a recent project, Vlad expected the customer to insist on a hardened on premise model with a Dell IPC and dedicated GPUs. Instead, they shrugged and said put it in ChatGPT, the boilerplate logic has no real IP. Data governance on the carpeted side of the business is mature. On the OT side, it barely exists, and that gap matters as more plant floor data flows toward AI tools. For systems integrators, AI is compressing timelines on slow, repetitive work. Tag validation, electrical drawing automation, screenshot to bill of materials extraction, and functional spec to PLC starting points are all in active development. The tradeoff is that some of these tools save four weeks of manual auditing but require a couple of weeks to set up correctly, and a probabilistic LLM still demands human signoff on safety and control logic. Senior engineers benefit most because they already know what good output looks like. The bigger industry question is what happens to the junior to senior pipeline if entry level work disappears. Hardware tells a different story. Moore's Law, first proposed in 1965, held for about 60 years before chip density at three nanometers and heat budgets broke the cost curve. GPUs on the consumer side have been roughly stagnant since the Nvidia 30 series. On the industrial side, demand for radical hardware change has been low. PLCs, switches, IO modules, and field protocols look much like they did twenty years ago. IO Link, the protocol that should be a baseline for any Industry 4.0 deployment, was founded in 2006. Image recognition has unlocked pick and place applications that used to be too expensive to engineer the traditional way. The workforce thread runs underneath all of this. UPS recently negotiated voluntary buyouts of roughly one hundred and fifty thousand dollars per driver to remove tens of thousands of positions, while large technology firms continue to lay off staff and reinvest in data centers. Timestamps 0:00 IntroducPlayPlay Ep. 258 - Hannover Messe Recap, the State of Industrial AI, and What Comes Next at Automate 2026
• Ep. 256 - Why Machine Learning Still Outperforms LLMs for Manufacturing Process ControlApr 9, 2026 · 1 hr 9 minDigital twins and machine learning are redefining batch optimization in manufacturing. Learn how centerlining models can catch quality issues in real time before they become irreversible. Concepts like digital twins, golden batch profiles, and statistical process control have long promised more than they delivered. Virag Vora of Twin Thread argues that layering machine learning on top of these ideas is what finally brings them to life. In this context, a digital twin is entirely data centric: a real time and historical representation of a process that serves as the foundation for AI models. The core use case is batch centerlining. The model compares current conditions against historically successful profiles, segmented by raw material source, product type, and seasonality. An orange juice manufacturer uses Twin Thread to determine whether incoming fruit should be sold fresh or routed to concentrate based on seasonal sugar content. The model identifies contributing variables in real time and alerts operators before a batch drifts beyond recovery. Twin Thread tackles the "not enough data" objection head on. With over 60 connectors, the platform works with the fragmented data reality of most manufacturing sites. Even low frequency data can train a useful model that quantifies what higher resolution instrumentation would unlock. Virag draws a clear line between ML and LLMs for process control. ML models trained on historical data produce deterministic outputs trusted for real time guidance on machine settings. LLMs excel at document retrieval and natural language interaction but are not suited for recommending set points on a live line. Twin Thread layers both: ML handles optimization, while Twin Thread Advisor lets users interrogate data and configure models through conversation. The standout proof point is Hills Pet Nutrition. After three years on Twin Thread, their models automatically feed recommendations into live production. That closed loop followed a deliberate path from human validation to A/B trials to automated execution with operator opt out. About Virag Vora Virag Vora is a solutions professional at Twin Thread, a platform that combines data centric digital twins with machine learning to optimize manufacturing processes. With a background in chemical engineering, Virag began his career deploying MES and DCS systems in biotech and pharma before joining Tulip and then Twin Thread. He helps manufacturers connect their existing data infrastructure to AI powered optimization across batch, continuous, and hybrid processes. Timestamps 0:00 Introduction 1:20 Virag's background in chemical engineering and industrial software 6:30 Moving up the ISA 95 stack from DCS to MES and applications 9:00 How AI reinvents digital twin, golden batch, and SPC concepts 12:PlayPlay Ep. 256 - Why Machine Learning Still Outperforms LLMs for Manufacturing Process Control
• Ep. 255 - From Virtual Design to Physical AI: Vention's Blueprint for Industrial RoboticsApr 2, 2026 · 1 hr 4 minPhysical AI is arriving on factory floors ahead of schedule, and Vention is already deploying it on applications four automation integrators failed to crack. François Giguère, CTO of Vention, draws a precise line between agentic AI and physical AI. Agentic systems process data and return data. Physical AI controls motion and actuation that produce real world consequences on a factory floor where a hundred percent uptime is the only acceptable standard. Giguère has spent a decade helping build Vention, a platform that lets manufacturers design robotic cells in 3D, program them through natural language, simulate them in a browser, and receive the physical machine shipped in modular components like an industrial kit. With a team of 95 engineers and three years as CTO, he brings a grounded perspective on where AI delivers real value in industrial automation and where it still falls short. The design, automate, simulate workflow at Vention represents one of the most complete implementations of AI-powered machine engineering currently in production. In the design phase, customers build systems from a modular component library. In the automate phase, an AI agent converts natural language prompts into Python control code for the entire cell including robot arms, conveyors, vision systems, and grippers. The program is validated in simulation before a single component ships. This is made possible by Vention's motion streaming architecture: instead of treating the robot as the master controller the way KUKA KRL does, Vention brings all motion planning, inverse kinematics, forward kinematics, blending, and trajectory optimization into its own software stack. The robot becomes a passive component consuming a motion stream, and the entire machine becomes programmable from a single unified codebase that AI tools excel at generating. Giguère notes that Vention's choice to use Python as the programming language for automation control gives their AI tools a measurable edge over environments built on structured text or ladder logic. Vention's two physical AI products are GRIP (Generalized Robotics Intelligence Pipeline) and Rapid AI Operator, a modular bin picking application built on top of GRIP. The technology relies on transformer-based foundation models. About François Giguère François Giguère is the CTO of Vention, an industrial automation platform where manufacturers design, program, simulate, and deploy robotic systems entirely online. Employee number four at the company, he has contributed to Vention's growth for over 10 years and leads a team of 95 engineers. He holds a background in electrical engineering and real-time embedded software development. Learn more: https://vention.io Timestamps 0:00 Introduction and welcome 1:00 François Giguère's background and Vention overview 2:20 How AI spans Vention's internal tools and customer products 4:00 Why embedded and robotics coPlayPlay Ep. 255 - From Virtual Design to Physical AI: Vention's Blueprint for Industrial Robotics
• Ep. 254 - From Cost Center to Growth Engine: The AI Future of Manufacturing MaintenanceMar 26, 2026 · 1 hr 4 minAI in manufacturing is no longer a strategy reserved for the boardroom. It is a tool for the technician on the plant floor, and the results are already showing up in real operations worldwide. Most digital transformation strategies in manufacturing are built for desk workers on the carpeted side of the building, not the operators and technicians keeping production running on the concrete floor. AI platforms have historically been designed for white collar knowledge workers with time to navigate complex systems, leaving the frontline worker as an afterthought. Nick Haase recognized this gap when building MaintainX in 2018, and it became the foundational design principle behind everything the company built. The result is a platform now serving nearly 14,000 customers across manufacturing, food and beverage, facilities management, and any industry that depends on physical assets staying operational. The core thesis Nick brings to this conversation is that the person with no purchasing authority and no budget is the single most important factor in whether a digital transformation project succeeds or fails. That person is the frontline technician. Building for that user first required a mobile experience so intuitive that no training was needed, one that met workers in the flow of existing work rather than pulling them out of it. If your team needs a 300 page manual to use the platform, the adoption battle is already lost. The skilled labor shortage in manufacturing is not a forecast. The United States is projected to have more than 3 million manufacturing jobs unfilled by 2030, driven largely by retirement of experienced workers who have spent decades building institutional knowledge. That knowledge cannot be transferred through a job posting. MaintainX attacks this through AI powered voice note capture at work order closeout. Technicians leave a verbal description of what they found and fixed. The platform transcribes it across any language or accent, standardizes it, and builds a living knowledge base that outlasts the retirements of the people who created it. For organizations with similar equipment across dozens of sites, that knowledge becomes portable across locations and years. About Nick Haase Nick Haase is a co-founder of MaintainX, a frontline work execution platform for maintenance, reliability, SOPs, safety, and compliance serving nearly 14,000 customers across manufacturing and other asset-intensive industries. Nick is also the host of The Wrench Factor podcast. Connect with Nick: https://www.linkedin.com/in/nickhaase/ Timestamps 0:00 Introduction 1:30 Nick Haase and MaintainX Background 7:20 Where AI Fits for Frontline Workers 10:00 What Data Foundations Are Needed for AI 13:30 Why Frontline Adoption Determines Digital Transformation Success 16:40 The Skilled Labor Shortage and Retirement Wave 18:30 Voice Notes and AI Powered Knowledge Capture<PlayPlay Ep. 254 - From Cost Center to Growth Engine: The AI Future of Manufacturing Maintenance
• Ep. 253 - How Manufacturers Can Turn Plant Data into AI Powered Insights w/ Konstantin EukodyneMar 19, 2026 · 1 hr 28 minIndustrial AI is getting a lot of attention in manufacturing right now, but one of the biggest questions is still the most practical one. How do you turn plant data, process knowledge, and operational constraints into something that actually creates value? In this episode of Manufacturing Hub, Vlad Romanov and Dave Griffith sit down with Konstantin Paradizov of Eukodyne for a detailed conversation on what industrial AI looks like when it is applied by people who understand manufacturing, MES, process improvement, data architecture, and the realities of the plant floor. What makes this discussion especially valuable is that it does not stay at the surface level. Konstantin shares how his background moved from pharma into food and beverage, how Lean Six Sigma and process thinking shaped his approach, and why many of the best opportunities in manufacturing still begin with understanding the actual workflow before talking about software. The conversation explores a theme that comes up again and again in industrial transformation: the biggest gains often do not come from adding more technology first. They come from understanding the problem clearly, identifying what information matters, validating assumptions with the people doing the work, and then using the right mix of tools to move faster. A major part of this episode focuses on the real use of AI in consulting and discovery. Konstantin explains how his team uses secure transcription workflows, on premises AI infrastructure, cloud models, masking of sensitive information, iterative validation, and ROI driven reporting to create high value outputs in a fraction of the time that would have been required even a year or two ago. This is an important point for manufacturers, system integrators, software teams, and plant leaders. AI is not just something that sits in front of an operator as a chatbot. It can be used behind the scenes to accelerate analysis, strengthen recommendations, shorten discovery, improve documentation, and reduce the cost of getting to a better answer. The technical section of this episode is especially strong for anyone working in industrial automation, OT data systems, or applied AI. The discussion covers on premises compute, Nvidia based edge hardware, Linux environments, Docker containers, RAG workflows, vector databases, knowledge graphs, MQTT pipelines, HiveMQ, Mosquitto, n8n, Claude Code, Cursor, Gemini, OpenRouter, and the tradeoffs between frontier models in the cloud and smaller or open models deployed closer to the process. One of the clearest takeaways is that manufacturers should not start with the biggest model or the most exciting headline. They should start with the problem, the constraints, the data path, and the economics of the solution. Vlad also pushes on an issue that matters to almost every manufacturer trying to prepare for AI. If you collect massive amounts of plant data into historians, cloud platforms, and enterprise systems,PlayPlay Ep. 253 - How Manufacturers Can Turn Plant Data into AI Powered Insights w/ Konstantin Eukodyne
• Ep. 252 - Industrial AI in Manufacturing What Actually Works and What Does Not #industrialautomationMar 12, 2026 · 1 hr 5 minManufacturing Hub is back with Episode 252, where co hosts Vlad Romanov and Dave Griffith break down what an AI survival guide should actually look like for manufacturing and industrial automation professionals. This is not a hype conversation about replacing people with magic software. It is a grounded discussion about what AI tools can do today, where they fail, why context and data quality matter so much, and how industrial teams should think about experimentation without losing sight of real operating constraints. In this episode, Vlad and Dave unpack the evolution many engineers and technical leaders have already felt in real time, from early prompt engineering, to agent based workflows, to MCP servers, skills, context management, and the growing cost of tokens and infrastructure. The conversation moves beyond generic AI commentary and into the reality of plant floor environments, where success depends on process knowledge, data architecture, OT constraints, cybersecurity, governance, and clear business value. One of the strongest themes throughout the episode is that manufacturers cannot skip the hard work of structuring data, understanding workflows, and defining use cases simply because AI tools are moving quickly. Vlad brings a very practical industrial lens to the discussion. Drawing on years of hands on experience across controls, manufacturing systems, plant modernization, and digital transformation, he explains why industrial AI has to start with operational context. A maintenance team, an engineering team, and a quality team do not need the same data, do not ask the same questions, and should not be handed the same AI workflows. That distinction matters. This conversation also highlights why the best industrial AI implementations will likely come from teams that combine domain expertise with strong technical execution, rather than generic AI shops trying to force a solution into environments they do not fully understand. Dave adds an important systems and adoption perspective, especially around cost, scaling, management expectations, and the danger of trying to prompt your way past foundational architecture work. Together, Vlad and Dave explore why manufacturers are interested in AI, why many are afraid of being left behind, and why so many projects still stall once they hit the realities of obsolete equipment, weak data models, fragmented systems, and unclear ownership of information. They also discuss deterministic logic versus LLM behavior, reporting workflows, industrial dashboards, PLC code generation concerns, and the practical question every manufacturer should ask before investing: what problem are we solving, for whom, and what is the measurable return? For those new to Vlad, he is an electrical engineer and manufacturing leader with deep experience across industrial automation, controls, data systems, OT architecture, modernization strategy, and plant operations. Through Joltek, Vlad works with mPlayPlay Ep. 252 - Industrial AI in Manufacturing What Actually Works and What Does Not #industrialautomation
• Ep. 251 - Ignition 8.3 ProveIt How Inductive Automation Scales Multi Site Factories w/ MQTT and UNSMar 5, 2026 · 1 hr 3 minIn this episode of Manufacturing Hub, Vlad and Dave sit down with Travis Cox and Kevin McCluskey from Inductive Automation to unpack what was actually proven at ProveIt and why it matters for teams trying to modernize plants without building a fragile mess of point to point integrations. If you have ever looked at a shiny demo and wondered what the real architecture looks like, how it scales beyond a single line, and what it takes to roll out across multiple sites without turning every change into a high risk event, this conversation is for you. Travis and Kevin walk through their ProveIt Enterprise B build and the thinking behind it. The core idea is simple but powerful: treat the factory like a system that needs a shared digital infrastructure, built on open standards, where data is contextualized and reusable. They break down how they used Ignition Edge close to PLCs for resiliency, local HMIs, and disciplined data modeling, then moved data through MQTT into a Unified Namespace so multiple applications can consume the same trusted signals and context. This is the difference between “we can connect to anything” and “we can scale without rewriting everything every time the business changes.” Open standards show up repeatedly in the conversation because ProveIt is specifically designed to force interoperability and practical implementation tradeoffs. Inductive Automation has also written about ProveIt as a place where MQTT, OPC UA, and SQL show up as real foundations rather than slogans. From there, the episode gets into the part that should make both OT and IT teams pay attention: modern deployment practices applied to industrial applications. Kevin outlines a clear maturity path from a single designer workflow to version control, then to containerized deployments, and finally to full GitOps style promotion across dev, staging, and production using tools like Argo CD, Helm, Kubernetes, and release promotion concepts that look like what the software world has used for years. Argo CD is explicitly built around Git repositories as the source of truth for desired state, which is exactly why it fits this style of deployment. The live portion of the conversation demonstrates how fast this can get when the infrastructure is treated as code: they spin up a brand new “site four” by submitting a form, generating a pull request, merging it, and letting the pipeline do the rest. Timestamps 00:00 Welcome back and why this ProveIt recap matters 01:35 Meet Travis Cox and Kevin McCluskey from Inductive Automation 03:10 What ProveIt is and the key vendor questions it forces 05:20 Enterprise B architecture overview from PLC to Edge to site to enterprise 07:30 HMI walkthrough across liquid processing, filling, packaging, palletizing 09:05 Why deploy Ignition Edge instead of only a centralized site gateway 12:05 Design once, reuse everywhere and what that means for scaling quickly 14:35 On prem realities versus cloud infPlayPlay Ep. 251 - Ignition 8.3 ProveIt How Inductive Automation Scales Multi Site Factories w/ MQTT and UNS
• Ep. 246 A - Factory of the Future Without the Hype: Siemens on Data Transparency, Orchestration, and Trust in AIFeb 12, 2026 · 59 minThis episode wraps up our Technology Modernization theme with a Siemens perspective that feels very grounded in what factories are actually dealing with right now. Brian Albrecht and Louis Hughes from the Siemens XD team walk through what they are seeing in the field across brownfield and greenfield conversations, why executives keep asking for industrial AI before the foundations are ready, and what it really takes to turn messy plant data into something you can trust for analytics, operations, and eventually AI enabled workflows. A big thread in this conversation is that modern manufacturing is not blocked by ambition, it is blocked by readiness. Everyone wants faster decisions, fewer surprises, and higher uptime, but the path there usually starts with boring work that is not optional. Data transparency across machine, plant, MES, and cloud layers. A clear definition of what real time actually needs to mean for a given use case. And a plan to contextualize and orchestrate data so that AI does not get fed junk inputs. Brian and Louis explain how they approach those early customer conversations, how workshops turn vision into prioritized use cases, and why trust, pilots, and repeatability matter more than flashy demos when you are working in regulated or high consequence environments. If you have been hearing nonstop AI buzz but you are still wrestling with legacy controls, inconsistent tags, documentation that no one can find, and seven layers of security constraints, this episode is for you. We get into practical use cases like AI vision and anomaly detection, LLMs for tribal knowledge and troubleshooting workflows, and the idea of fast versus slow AI, meaning AI that must act during production versus AI that can analyze after the fact. Timestamps 00:00 Welcome and why this episode closes the modernization theme 02:10 Meet Brian Albrecht and Louis Hughes from the Siemens XD team 05:25 Vertical differences across oil and gas, discrete, and process manufacturing 07:50 What executives ask for right now beyond AI, factory of the future and data transparency 10:50 Brownfield reality and why most modernization work starts with legacy systems 12:30 The AI conversation when foundations are missing, meeting customers where they are 15:10 Current AI use cases in manufacturing, downtime, throughput, LLMs, and vision 18:10 What it means to be AI ready, data silos, contextualization, and orchestration 23:50 Fast versus slow AI and why production time decisions are different from analytics 25:30 Edge versus cloud architecture, latency, and where the data should live 33:40 Cybersecurity, trust, and why perception can lag behind the technology 36:50 Hallucinations, guardrails, and why recommendations usually come before automation 51:10 Book recommendations, career advice, and future predictions for industrial AI About the hosts Vlad Romanov is an electrical engineer with an MBA from McGill UPlayPlay Ep. 246 A - Factory of the Future Without the Hype: Siemens on Data Transparency, Orchestration, and Trust in AI
• Ep. 246 - Building a Life Sciences Virtual Factory Enterprise C, MQTT, and UNS w/ Amy WilliamsFeb 6, 2026 · 1 hr 4 minIn this special ProveIt edition of Manufacturing Hub, Vlad Romanoff and Dave Griffith sit down with Amy Williams from Skellig Automation to unpack Enterprise C, a life sciences virtual factory built to look and feel like the reality inside many regulated facilities today. If you work around batch processes, compliance, historian projects, electronic batch records, or industrial data architecture, this conversation is a practical walkthrough of what it actually takes to turn raw signals into a story you can defend, improve, and scale. Amy has spent years working exclusively in life sciences manufacturing, starting deep in DeltaV automation for batch pharma and moving into digital transformation projects that focus on open architectures, modern data pipelines, and real operational outcomes. In this episode, she explains what Enterprise C is simulating, why it was designed as an Industry 3.0 style biotech startup, and what kind of data and documentation a vendor would have to wrestle with in the real world. The factory is producing a fictional enzyme using a fed batch fermentation process, and the UNS publishes realistic one second resolution batch data across four pieces of single use equipment including a mixer, a bioreactor, a chromatography skid, and a TFF skid. One of the most valuable parts of this episode is the reminder that data sitting in an MQTT broker is not inherently valuable. The value comes when the data is contextualized enough that different teams can use it without tribal knowledge, and when the resulting traceability helps you answer the questions that matter in life sciences. What happened during the batch, what changed compared to previous runs, what went out of spec, what documentation proves compliance, and what you should do next time to avoid losing a batch that can cost millions. Amy also explains why Enterprise C intentionally includes uncontextualized tags and paper files, because that is exactly where many facilities still are. The hard part is not connecting a sensor, the hard part is governance, agreement, and building a model that humans actually follow. You will also hear the crew dig into Smart Manufacturing Profiles and why standardizing information models is one of the clearest paths toward true interoperability. If you are tired of every site, every integrator, and every project reinventing the same pump, valve, and equipment model from scratch, this is the kind of conversation that helps frame why that problem keeps repeating and what might finally reduce it. The ProveIt format forces the questions that most conferences avoid, including what problem was solved, how it was done, how long it took, and what it cost. That is exactly why this conference has become a magnet for practitioners who care about the difference between a demo and a deployable solution. About the hosts Vlad Romanoff is an industrial automation and manufacturing systems expert and the founder ofPlayPlay Ep. 246 - Building a Life Sciences Virtual Factory Enterprise C, MQTT, and UNS w/ Amy Williams
• Ep. 245 - Modernizing Manufacturing | Data, OEE, Quality Analytics - Everyone Wants the Same SignalsFeb 5, 2026 · 1 hrIn this episode of Manufacturing Hub, Vlad Romanov and Dave Griffith sit down with David for a practical, operator grounded conversation about industrial data, modernization, and what it actually takes to turn plant floor signals into business decisions. David has spent more than two decades in manufacturing across automotive, solar, and electric vehicles, and his story is a familiar one for a lot of us. He walked into a plant thinking he was there for a project, discovered PLCs in real time, and never left the factory world. From early days wiring up a SQL Server to pull line data instead of sending people out with stopwatches, to leading data and analytics and shaping MES and reporting strategy, this conversation stays focused on the messy middle where most factories live. A big theme here is that collecting data is not the same thing as creating information. As tooling has improved, connectivity, historians, SCADA, cloud storage, MQTT, and the modern ecosystem have made it easier to get signals out of machines. The hard part is deciding what matters, aligning stakeholders, and creating context that survives across teams and projects. David breaks down how real progress often starts with simple visibility, what is ruining your day, what is the biggest safety risk, what is the recurring quality miss, what is the downtime story you do not trust, then builds from there using workshops and iterative delivery instead of giant multi year “boil the ocean” programs. We also get into Unified Namespace, why it resonates with people who have been burned by tightly coupled ISA style integrations, and why change management is the hidden cost. If you are exploring UNS, this episode highlights the difference between drawing the box on a whiteboard and getting a whole organization to actually adopt consistent naming, context, and ownership. Then we finish with a grounded take on industrial AI. No hype, no doom. Just a realistic view of where AI helps today, where it breaks, and why context windows, documentation quality, and domain expertise still decide whether results are useful or dangerous. Timestamps 00:00:00 Welcome and the month theme on technology modernization 00:02:10 David’s background from automotive and the Tesla Fremont NUMMI era to data leadership 00:05:10 The moment data became “real” and why proactive visibility drives safety and outcomes 00:07:10 How Kaizen and Toyota Production System style problem solving creates demand for data 00:11:50 Why modern tooling makes collection easier and why budget and commitment still decide success 00:16:10 Starting points that work in the real world and the simplest visibility model that scales 00:18:20 Unified Namespace explained through decoupling, context, and why the first attempt often fails 00:23:50 Who really uses the data, operators, quality, engineering, and the “next factory” teams 00:29:10 Defining KPIs when nobody has answers and using workshops toPlayPlay Ep. 245 - Modernizing Manufacturing | Data, OEE, Quality Analytics - Everyone Wants the Same Signals
• Ep. 244 - How Modern Plants Actually Bridge Legacy Automation and AI w/ Benson HouglandJan 29, 2026 · 1 hr 8 minIn this episode of Manufacturing Hub, Vlad Romanov and Dave Griffith sit down with Benson Hougland from Opto 22 to get brutally practical about what is actually running on shop floors today, and what it takes to move from legacy automation to modern, data ready operations without breaking what already works. If you have ever walked into a plant and seen a mix of decades old controllers, manual processes, islands of automation, and a few shiny modern pockets of connectivity, this conversation will feel very familiar. Benson has spent roughly three decades at Opto 22 and he has seen the full spectrum, from brownfield realities where nothing can go down, to greenfield expansions where teams can finally design with data, security, and integration in mind. A major thread in this discussion is the gap between “the machine runs” and “the business can learn from the machine.” Benson lays out why so many facilities still operate in a world of siloed equipment with minimal visibility, and why digital transformation stalls when the goal is vague or driven by trend chasing. The most actionable insight is simple: start with a real problem, win small, build trust in the data, and only then scale. That approach is how you avoid proof of concept purgatory, and it is also how you get leadership buy in without overpromising. If you are looking at industrial AI, it becomes even more critical, because manufacturing cannot tolerate hallucinated answers. Benson explains why industrial AI starts with sanctity of data, meaning clean, contextualized, trustworthy signals that an organization can actually act on. You will also hear a grounded take on why hardware still matters in 2026. Not because everyone wants to rip and replace working PLCs, but because modern plants need layered edge strategies that can extract the right data, protect legacy assets, and integrate upward using open methods. About the guest Benson Hougland is a long time leader at Opto 22, a US based manufacturer of industrial controllers, edge devices, and IO. He focuses on customer and integrator feedback, product strategy, and the practical challenges teams face when modernizing systems while keeping operations running. Opto 22 is known for building and manufacturing in the United States and for leaning into open connectivity approaches that help reduce lock in and simplify integration. About the hosts Vlad Romanov is an electrical engineer with an MBA from McGill University and over a decade of experience delivering automation and modernization work across high performing manufacturing environments. Through Joltek, Vlad supports manufacturers with plant floor assessments, controls and OT architecture, system modernization planning, integration execution, and technical upskilling so teams can own their systems long term. Vlad’s work consistently sits at the intersection of reliability, operational execution, and the realities of IT and OT convergence, with a focus on wPlayPlay Ep. 244 - How Modern Plants Actually Bridge Legacy Automation and AI w/ Benson Hougland
• Ep. 243 - From Legacy Systems to AI Readiness A Realistic Look at Manufacturing ModernizationJan 22, 2026 · 1 hr 1 minTechnology modernization in manufacturing is not a list of shiny tools. It is a sequencing problem. In this episode of Manufacturing Hub, Vlad Romanov and Dave Griffith break down why the executive vision for AI often collides with the reality of the plant floor, and what a practical path forward actually looks like when you account for data quality, legacy controls, networking, and the true cost of integration. A core theme in this conversation is imperfect information. Leaders often believe the data already exists because reports exist. But a stack of paper, a few spreadsheets, or a single counter value is not the same as contextualized, trustworthy history that can drive decisions or support advanced analytics. Vlad and Dave walk through why foundational work matters, what teams usually miss during modernization, and how quickly the bill grows when you discover your architecture is outdated, undocumented, or full of dependencies you cannot see until you open panels and start tracing signals. You will also hear a grounded debate on how to think about SCADA, MES, historians, dashboards, and what it would actually mean to “feed data into AI” in a manufacturing context. The takeaway is simple. If you want better outcomes, you need a better understanding of your current state, a clear business case, and a roadmap that prioritizes what matters operationally. Modernization is not one big upgrade. It is a series of decisions that either reduce friction or create it. About the hosts Vlad Romanov is an industrial automation and manufacturing expert focused on plant assessments, controls and data architecture, IT and OT integration, and workforce upskilling. Vlad has over 10 years of experience across large manufacturers and complex multi site environments, working from PLC and HMI layers up through SCADA, MES, and ERP integration programs. He is the founder of Joltek, where the mission is to help manufacturers modernize safely, build internal capability, and deliver results that actually survive handoff to operations. Learn more about Joltek https://www.joltek.com https://www.joltek.com/services Dave Griffith is an industrial automation practitioner and consultant who works closely with manufacturers to modernize legacy environments, improve reliability, and build practical systems that operators and maintenance teams can support. Dave brings a strong perspective on what is feasible in real plants, where uptime, risk, budget, and organizational readiness drive every decision. Timestamps 00:00:00 Welcome and why this month is about technology modernization 00:02:10 The real problem with “just add AI” in manufacturing 00:04:15 Quick background on Vlad and Dave and the work they do 00:05:25 The disconnect between the perfect factory vision and the plant floor 00:06:25 Vlad on business cases, integration reality,PlayPlay Ep. 243 - From Legacy Systems to AI Readiness A Realistic Look at Manufacturing Modernization
• Ep. 242 - From Controls to MES Building Manufacturing Systems That Scale Without Breaking OperationsJan 15, 2026 · 58 minIn this episode of Manufacturing Hub, hosts Vlad Romanov and Dave Griffith welcome back Amos Purdy for a wide ranging conversation that connects plant floor reality with SCADA, MES, and the business decisions that actually fund modernization. Amos shares his path from early software and programming work into industrial automation, including building an industrial automation class and lab, leading MES and SCADA efforts, and working across industries where the pace, constraints, and validation expectations can feel like completely different worlds. If you have ever wondered why a solution that looks obvious on a whiteboard takes months or years to land on a production line, this episode breaks down the human, technical, and financial reasons in plain terms. A big thread throughout the conversation is what it takes to build systems that last. The group digs into hiring and mentoring for Ignition based teams, what backgrounds translate well, and why “hobbyist energy” can be a real superpower in interviews and on the job. The practical takeaway is simple: credentials help you get in the door, but projects help you stand out, especially when you can explain the problem, the architecture, and the tradeoffs you made. The conversation also gets real about legacy plants, where the constraint is often not ambition but risk, ROI, and operational disruption. The group frames modernization as a sequence of targeted moves that improve data availability, reduce cybersecurity exposure, and create a foundation for future applications without betting the entire facility on a massive rip and replace. You will also hear a grounded take on AI in industrial settings. The panel separates what is useful today from what is still hype, and explains why industrial AI needs context, standards, and purpose built training data to be trusted. They connect that to the “data transparency” problem: companies want answers faster, but the hard part is making the data accessible, reliable, and safe in the first place. The episode closes with a discussion on EV and battery manufacturing trends, the reality of global standards and certification, and what the next few years could look like as edge devices, connectivity, and power systems evolve. Hosts Vlad Romanov is an industrial automation and manufacturing systems expert focused on SCADA, MES, OT data infrastructure, and modernization strategy. He combines electrical engineering depth with an MBA from McGill University to help manufacturers reduce risk, improve reliability, and turn plant data into decision ready information. He leads Joltek, where he delivers assessments, integration roadmaps, and practical upskilling for engineering and operations teams. Dave Griffith Manufacturing and automation leader focused on bridging business outcomes with engineering execution, change management, and scalable plant systems. Guest AmoPlayPlay Ep. 242 - From Controls to MES Building Manufacturing Systems That Scale Without Breaking Operations
• Ep. 241 - Manufacturing in 2026 AI Reality Cybersecurity Data Careers and What Comes NextJan 8, 2026 · 1 hr 14 minWelcome to Manufacturing Hub and welcome to 2026 . In this kickoff episode, Vlad Romanov and Dave Griffith reset the table for the year and share what the show is really about: practical conversations with people who build, run, secure, and modernize manufacturing systems. If you are new here, this is the perfect starting point because we explain the format, the monthly themes, and the reason we keep coming back to the same hard truth: manufacturing improvement is never just about technology. It is also about people, process, incentives, and change . From there, we get into the big question everyone is asking right now: what actually changes in 2026 for manufacturing and industrial automation. We talk about why AI stopped being a novelty and started becoming a permanent part of the landscape, and we separate the hype from the applications that are starting to look real. We discuss where AI helps today, where it still struggles, and why most teams will not get value until they build stronger fundamentals in data collection, context, and operational ownership . We also connect the dots between AI and the pressure it puts on infrastructure, security posture, and decision making, especially when the plant floor reality is still paper logs, tribal knowledge, and inconsistent system documentation. We also cover what we expect to see across the core pillars of the industrial stack: plant floor data and operations , engineering and commissioning workflows, back office analytics, OT cybersecurity , industrial data platforms, and how the systems integration market is evolving as more work moves upward into analytics, architecture, and long term modernization programs. Finally, we zoom out into careers, acquisitions, private equity activity, and what these shifts mean for engineers, leaders, and teams trying to build durable capability instead of chasing the next shiny tool. If you are planning your year, come meet us in person. We will be at ProveIt in Dallas, Texas February 16 to 20 . We will also be at Automate in Chicago, Illinois June 22 to 26 . And we are expecting to be back at the Ignition Community Conference in Sacramento, California September 22 to 26 . Timestamps 00:00 Welcome to 2026 and why we are back 01:00 What Manufacturing Hub covers and how the show is structured 02:35 Meet the hosts Dave Griffith and Vlad Romanov 04:55 Where to meet us in 2026 ProveIt Automate ICC 07:45 The state of manufacturing and what is changing this year 08:35 AI in manufacturing from curiosity to permanence 12:20 Plant floor data reality and why fundamentals still block progress 18:10 AI in engineering and commissioning where it helps and where it can hurt 2PlayPlay Ep. 241 - Manufacturing in 2026 AI Reality Cybersecurity Data Careers and What Comes Next
• Ep. 236 - How to Deliver Manufacturing Projects That Operations Actually UseDec 4, 2025 · 1 hr 31 minHanding over a project is one of the most underestimated and misunderstood phases in manufacturing and industrial automation. In this episode of Manufacturing Hub, Vlad and Dave sit down to break apart real stories from the field covering MES rollouts, line commissioning, SCADA and ignition development, operational adoption, and the very real consequences of poor knowledge transfer. Most conversations online focus on the technical build, but very few people emphasize the point where engineering lets go and the operations team becomes the true owner of the system. This episode brings forward examples of both well executed handovers and catastrophic failures that every engineer, integrator, or manager can learn from. Vlad begins by walking through his experience building MES and data collection systems for food and beverage facilities where each plant had different architectures, legacy systems, undocumented networks, and obsolete PLCs. These initiatives required deep assessments, phased modernization, server deployments, KPI development, and the long journey from data collection to actual operational use. The most important insight is that success rarely comes from the technology alone. It comes from the extent to which operators, supervisors, and CI teams are trained, empowered, and aligned to use what has been built. Dave then shares a story from a multi year track and trace project that technically worked but failed at the operational handover stage because the one scheduler refused to schedule inside the system. The entire project was mothballed despite millions of dollars invested. The lesson is simple. Technology cannot compensate for missing stakeholder alignment and poor discovery. Human influence can halt even the most well engineered solution. Timestamps 00:00 Welcome and episode setup 01:20 Host introductions and backgrounds 04:00 Vlad’s MES and data rollout projects across multiple plants 18:10 Biggest wins and failures from MES handovers 26:20 Dave’s chocolate factory MES and traceability project 29:30 The scheduler says no and a multi million project gets mothballed 36:40 Lessons learned about scope creep and realistic timelines 42:00 Vlad’s multimillion packaging line rollouts and OEE based handover 49:20 Internal versus external teams and who really owns change 58:50 Connected workforce at an orange juice plant and knowledge capture 01:15:00 Where project handovers are heading in the next three to five years 01:19:00 Career advice, books, and final thoughts Hosts Vladimir Romanov Founder of Joltek. Electrical engineer with an MBA from McGill University. More than a decade of experience across Procter and Gamble, Kraft Heinz, Post Holdings, and multiple systems integration roles. Specializes in OT systems, industrial data architecture, MES, SCADA, modernization, and digital transformation. Works with manufacturers to unlock value throuPlayPlay Ep. 236 - How to Deliver Manufacturing Projects That Operations Actually Use
• Ep. 235 - How to Build and Run a Systems Integration Company in ManufacturingNov 20, 2025 · 1 hr 23 minThis episode takes you inside the reality of becoming a systems integrator and growing a technical services business from the ground up. Vlad and Dave share their personal experiences launching and running integration companies, the lessons they learned as engineers moving into business ownership, and the challenges that come with finding customers, choosing technologies, setting rates, managing cashflow, and hiring the right people. This is a detailed and candid look at what the journey actually requires. It is also a practical conversation that breaks down how technical professionals can evolve beyond pure engineering work in order to build a sustainable integration practice in the world of manufacturing and industrial automation. The episode begins by grounding the definition of a systems integrator in the context of modern industrial environments. Vlad and Dave explore the many different shapes and levels of integrators across the ISA eighty five and ISA ninety five landscape, from controls and PLC programming to SCADA development, MES implementations, and specialized software delivery. They also explain why customers hire integrators, why the most valuable asset is always the people, and why the hardest part of the work is rarely technical. Vlad shares insights from his decade in engineering and operations roles at Procter and Gamble, Kraft Heinz, and Post Holdings, followed by senior engineering and management positions at multiple systems integration firms. Dave brings his experience from aerospace, OEM machine building, distribution, and running his own integration business focused on manufacturing execution systems and ignition development. The conversation then shifts to the earliest stages of starting an integration company. Vlad and Dave describe the moment when most professionals decide to go out on their own, which usually begins with feeling constrained by corporate structures or wanting more autonomy over the projects they work on. They break down the difference between being a contractor and building a long term business and why many technical founders underestimate the reality of sales, marketing, legal administration, cashflow management, and relationship building. The discussion highlights how timing and relationships drive early opportunities far more than technical ability and why every contract carries its own risk profile that needs to be negotiated with care. Listeners are then guided through the real startup requirements for a systems integration company. This includes liability insurance, business registration, accounting and bookkeeping tools, mileage and expense tracking, choosing an internal technology stack, managing licenses, and understanding when to invest in programming software or rely on customer owned licenses. Vlad and Dave explain the role of net thirty, net ninety, and even net one hundred eighty payment terms and why long payment cycles can destroy cashflow if not anticipated correctlPlayPlay Ep. 235 - How to Build and Run a Systems Integration Company in Manufacturing
• Ep. 234 - What Students Learn When They Build Ignition Projects in Seventy Two HoursNov 13, 2025 · 30 minIn this conversation recorded at the Ignition Community Conference, Vlad, Dave, and their guest David Grussenmeyer from Inductive Automation explore one of the most important and inspiring stories in the world of industrial automation education. David leads the Educational Engagement Program at Inductive Automation and has spent the last several years building a global network of universities, colleges, students, and integrators who are working together to bridge the gap between academic theory and real world industrial skills. This episode provides a detailed look at how the Student Buildathon was created, how it works, why it matters, and what it means for the future of the controls and automation workforce. The discussion goes far beyond the event itself. David explains how the industry’s needs for engineering talent have shifted, why many academic institutions struggle to keep pace with modern automation technologies, and how Inductive Automation is supporting both professors and students to meaningfully upgrade the curriculum. The episode also explores the importance of industry partnerships, the challenge of faculty bandwidth, the value of internships and academic co op programs, and the realities of teaching automation in an evolving landscape of legacy systems, modern platforms, and everything in between. Listeners will gain insight into how universities can adopt Ignition, how integrators can help shape the workforce pipeline, how students can develop real industry skills before graduating, and how modern industrial technology can be taught effectively without overwhelming educators. Vlad and Dave also share their own perspectives from years of integration work and reflect on how different their own educational experiences would have been if programs like this had existed earlier. This episode is educational, practical, and inspiring for anyone working in automation, industrial education, system integration, or workforce development. Timestamps 00:00 Introduction to the Ignition Community Conference and the Student Buildathon 01:25 How the Educational Engagement Program at Inductive Automation was created 03:22 The origin story behind the Student Buildathon concept 05:16 How the seventy two hour challenge works for student competitors 06:44 Requirements for student teams and how the selection process works 08:49 Why universities struggle to adopt new technology and how industry partnerships help 10:41 How integrator involvement accelerated program adoption across universities 12:28 The gap between academic theory and real industry practice 14:01 Building a complete lab curriculum for professors using Ignition 17:24 Why students should learn both modern and legacy industrial systems 18:20 Feedback from professors teaching Ignition for the first time 20:59 Understanding the different educator profiles and adoption journeys 23:15 How Inductive Automation built the five lab trainingPlayPlay Ep. 234 - What Students Learn When They Build Ignition Projects in Seventy Two Hours
• Ep. 233 - From Controls to Full-Scale Robotics Integration How Bright IA Leads in AutomationOct 30, 2025 · 1 hr 18 minIn this episode of Manufacturing Hub, hosts Vladimir Romanov and Dave Griffith sit down with Davide (David) Pascucci , founder of Bright IA ( https://brightiatx.com/ ), for an in-depth conversation about what it truly takes to build, grow, and succeed in the world of robotics integration and industrial automation . Davide shares his incredible journey from Italy’s oil and gas sector to leading one of Texas’s most promising automation firms. His story highlights the reality of moving from traditional controls work to full-scale robotics integration. Listeners will learn how his company evolved from small local projects into complex manufacturing solutions involving welding cells, painting robots, and palletizing systems used across multiple industries including food and beverage, fabrication, and renewables. The discussion explores how system integrators can strategically position themselves in the modern automation ecosystem . Davide explains the importance of vendor relationships, revealing how open collaboration with companies like Fanuc and KUKA helped his firm grow while avoiding common pitfalls faced by new integrators. He provides practical insights into how to evaluate robot brands, manage the mechanical design and safety aspects of projects, and find the right balance between in-house engineering and subcontracting work. Listeners will also hear a detailed perspective on the Texas manufacturing landscape , where oil and gas still dominate but are now accompanied by a new wave of innovation from defense, aerospace, semiconductor, and AI-driven industries. Davide explains how these shifts are creating a demand for flexible automation and robotics expertise across the region. A large portion of the conversation focuses on the real-world challenges that come with integrating robots on the factory floor. Davide talks about dealing with customers who insist on collaborative robots when industrial robots are better suited for the job. He describes how simulation and digital twin tools can help demonstrate cycle times and prove system capabilities before implementation. His transparency about pricing, quoting, and project management makes this a must-listen episode for anyone looking to understand the business side of integration, not just the technical aspects. The episode also explores how smaller robotics firms can collaborate with European and Asian OEMs that are entering the North American market. Davide shares the lessons he learned when working with foreign manufacturers, emphasizing that support, spare parts, and local presence are often more valuable than price alone. His advice is invaluable for early-stage integrators trying to evaluate new partnerships or decide which technologies to adoPlayPlay Ep. 233 - From Controls to Full-Scale Robotics Integration How Bright IA Leads in Automation
• Ep. 232 - Future of Automation with Siemens: Industrial AI, Virtual PLCs, and Digital Twin FactoriesOct 23, 2025 · 1 hr 48 minAt Automate 2025, Vlad and Dave take Manufacturing Hub inside the Siemens booth to explore how one of the world’s largest industrial technology companies is shaping the future of manufacturing. From the latest S7-1200 G2 PLC to industrial copilots powered by AI, digital twins that simulate entire factories, and virtual PLCs redefining automation, this episode is packed with insights from Siemens leaders and engineers. In this conversation series, we uncover the evolution of hardware, software, and data-driven manufacturing with experts including Chris Stevens and Anna-Marie Breu on customer experience and digital twins, Bernd Raithel on software-defined automation and IT/OT convergence, Louis Narvaez on the next-generation S7-1200 G2 PLC, Kristen Sanderson on Industrial Copilot and AI agents, Sarah McGee on Sematic AX and modern PLC programming, Kevin Wu on Pick AI Pro, Ivan Hernandez on the G220 drives, and cybersecurity specialists Tilo and Gaurav on securing industrial networks. Throughout the episode, Vlad and Dave discuss how Siemens is transforming plant operations through tools that connect the physical and digital worlds. Topics include co-pilots for engineering and operations, lifecycle management, virtual commissioning, edge computing, harmonics and clean power, and the convergence of IT and OT teams. This conversation is a must-watch for engineers, integrators, plant managers, and decision-makers looking to understand how software-defined automation, AI, and digital twin technologies are merging to create resilient, data-driven factories. Timestamps: 00:00 Siemens at Automate 2025 introduction 02:45 Defining manufacturing resilience and digital twins 09:32 Virtual commissioning and collaborative engineering environments 15:10 Adoption of digital twins in small and medium manufacturers 22:35 Co-pilots and natural language interaction in industrial systems 30:28 Automation lifecycle management and version control for PLCs 36:55 Virtual PLCs, software-defined automation, and IT/OT collaboration 46:40 The new Siemens S7-1200 G2 PLC and migration from G1 57:20 AI copilots, agents, and secure Siemens cloud infrastructure 1:08:05 Somatic AX and modern PLC programming for new engineers 1:17:25 Pick AI Pro and real-world robotic vision applications 1:29:10 G220 drives and clean power innovations 1:35:45 Industrial cybersecurity and vulnerability management 1:43:00 Cinemeric Run My Robot and CNC-robot collaboration 1:50:20 Final reflections on Siemens innovation and future trends References Mentioned: Siemens Digital Industries Siemens Industrial Edge Developer Kit S7-1200 G2 Information Sematic AX <a href="https://www.siPlayPlay Ep. 232 - Future of Automation with Siemens: Industrial AI, Virtual PLCs, and Digital Twin Factories
• Ep. 222 - Pick AI Pro with Kevin Wu | Faster Picking, Higher Reliability, Digital Twin and Vision AIOct 16, 2025 · 16 minModern robotic picking is moving beyond neat rows and perfect lighting conditions. In this Automate 2025 conversation, Vlad and Dave sit down with Kevin Wu from Siemens to explore how Simatic Robot Pick AI Pro is tackling the messy reality of warehouses and factories. They discuss how the new edge architecture with the Simatic IPC BX 59 A and an NVIDIA GPU lifts pick rates to well over one thousand picks per hour, why multiple suction patterns matter for stability on large or flexible items, how camera agnostic support opens the door to new vision hardware, and why transparent objects are no longer a limitation in many applications. This episode also dives into digital thread and digital twin workflows using Siemens Process Simulate. These tools allow teams to test new products and layouts virtually before any hardware changes are made, helping reduce commissioning risk and shorten the path to production. The discussion highlights an on-booth demonstration that combines a robot with a secondary camera and a vision language model to identify products and read packaging details such as expiration dates. It is a clear example of how multimodal AI can complement traditional industrial vision systems. A major theme throughout this conversation is resilience. In real operations, products are rarely placed perfectly. Pallets shift, orientations vary, and lighting changes throughout the day. Traditional rules-based vision systems often struggle when small variances accumulate. Kevin explains how model-free 3D picking localizes unknown objects in clutter, selects stable suction patterns based on measured dimensions, and keeps production moving without forcing operators to maintain perfect alignment. For manufacturers in consumer packaged goods and medical devices, this is a meaningful advancement. It enables greater product variety and frequent SKU changes while maintaining engineering control. The difference is that the picking logic adapts to what the system sees rather than expecting the environment to remain static. We also talk about practical evaluation and proof of concept. Siemens runs application testing at its Berkeley, California lab where customers can send sample parts for quick feasibility checks. A short video of their parts being picked can provide the confidence needed to move forward with a pilot project while minimizing cost and risk. For quality inspection and defect detection, Siemens also offers an Inspector station capable of learning from as few as twenty samples to identify defects in real time. The discussion closes by looking at the future of digital manufacturing. Digital thread tools make it possible to simulate robots from multiple brands, test new configurations, and evaluate throughput virtually. Combined with edge AI and NVIDIA vision language technology, this creates faster experimentation cycles, improved reliability, and measurable gains in uptime and throughput. Kevin’s key messagPlayPlay Ep. 222 - Pick AI Pro with Kevin Wu | Faster Picking, Higher Reliability, Digital Twin and Vision AI
• Ep. 231 - Travis Cox on Ignition 8.3 | ICC 2025 Highlights and the Future of Industrial SoftwareOct 9, 2025 · 51 minICC 2025 was a clear level up for the Ignition community. In this conversation Vlad and Dave share on the ground insights from a week of packed sessions, vendor showcases, and ProveIt demonstrations that brought working integrations to life. They unpack why the move to a larger venue created more chances for deep technical conversations, how the community benefited from hands on demos that connected to a shared data backbone, and what record attendance means for the growth of modern SCADA and manufacturing data platforms. The episode then shifts into a focused discussion with Travis Cox from Inductive Automation on the launch of Ignition 8.3 and what it unlocks for builders who care about reliability, scale, and speed. We discuss how 8.3’s configuration in the file system and the expanded REST API enable real version control and DevOps workflows in day to day projects. We explore practical AI opportunities through MCP servers that can safely expose context and operational data to large language models, with an emphasis on operator augmentation, faster troubleshooting, and responsible guardrails. We connect the dots between OT networking fundamentals and secure architectures by highlighting the growing need for segmentation, deterministic traffic, and resilient data movement. Throughout the episode we keep the focus on what matters in plants today clear outcomes for uptime, quality, and delivery rather than hype. Whether you are an engineer, integrator, or an operations leader, this episode gives you an actionable snapshot of where Ignition and the broader ecosystem are heading. You will hear what the community is building, which 8.3 features are worth testing first, how ProveIt style showcases help end users evaluate technologies, and why investing in networking skills remains one of the highest ROI moves for manufacturers. Timestamps 00:00 Welcome and ICC traditions with stickers and community shoutouts 01:25 What to expect today and why this episode includes a sit down with Travis 02:30 First impressions of ICC 2025 tracks vendor hall and ProveIt showcases 05:55 New Sacramento venue experience and why more space improved conversations 07:25 Walk up tickets record attendance and what that signals about growth 08:45 Why hands on ProveIt demos mattered for real integrations and learning 12:05 Ignition 8.3 launch and what we will cover in more depth later this month 13:25 AI themes across sessions and realistic use cases for builders and operators 16:20 Why OT networking education is now a must have skill set 18:05 DataOps and DevOps directions in Ignition 8.3 and what to trial first 23:10 Travis Cox joins with ICC takeaways and how community scale changes the game 28:35 Ignition 8.3 highlights configuration in files REST API and version control workflows About the hosts Vlad Romanov manufacturing modernization and data strategy consultant co host of Manufacturing Hub and founder ofPlayPlay Ep. 231 - Travis Cox on Ignition 8.3 | ICC 2025 Highlights and the Future of Industrial Software
• Ep. 230 - AI in Manufacturing with Tom Hechtman of Sepasoft | Real ROI, MES on Ignition, Sepa IQSep 25, 2025 · 1 hr 11 minArtificial intelligence is no longer just a buzzword in manufacturing. The pace of adoption has been incredible, yet the reality is far more complex than flashy headlines suggest. In this episode of Manufacturing Hub, Vlad Romanov and Dave Griffith welcome back Tom Hechtman, founder of Sepasoft, to explore how AI is actually being deployed on the plant floor, what barriers remain, and whether we are truly transforming manufacturing or simply tinkering at the edges. Tom brings decades of experience building MES solutions for manufacturers around the globe. From his early days in the Midwest working with Rockwell Automation technology to launching Sepasoft’s Ignition MES modules and now leading the development of Sepa IQ, Tom has been at the forefront of data, analytics, and system integration. His insights bridge the gap between hype and practice, helping us understand where AI creates real ROI, where it still falls short, and how to build the foundations for success. Throughout the conversation we dive into the challenges of quality improvement, predictive maintenance, scheduling optimization, and contextualizing plant data. We discuss the importance of trust in both data and AI-generated outputs, the economics of running LLMs and machine learning models, and why cybersecurity and data governance cannot be an afterthought. Drawing on the recent MIT study that revealed only 5 percent of AI projects make a measurable P&L impact, Tom helps us unpack what manufacturers need to do differently if they want to avoid being part of the 95 percent that fail. We also get an update on Sepa IQ and how customers are using it to connect plant floor data, structure it for AI and analytics, and prepare for advanced scheduling and predictive tools. From lessons learned working with early adopters to practical advice on starting small, Tom makes it clear that manufacturing AI is a journey that requires technical expertise, domain knowledge, and cultural change. Whether you are an executive evaluating AI investments, a controls engineer curious about new tools, or a plant manager wondering how to get real results, this episode delivers a balanced, practical, and in-depth perspective on the future of AI in manufacturing. Timestamps 00:00 Introduction and AI in every manufacturing conversation 03:00 Tom Hechtman background and the origins of Sepasoft 05:00 MES modules, batch processing, and the evolution of Sepa IQ 08:00 Defining manufacturing AI and the role of plant floor data 13:00 Quality improvement and predictive analytics opportunities 20:00 Foundational challenges with legacy systems and data collection 24:00 Insights from the MIT study on AI adoption and ROI 32:00 Training data, context windows, and the economics of LLMs 44:00 Sepa IQ customer feedback and scheduling optimization 50:00 Trust, hallucinations, and cybersecurity considerations 59:00 ICC announcementPlayPlay Ep. 230 - AI in Manufacturing with Tom Hechtman of Sepasoft | Real ROI, MES on Ignition, Sepa IQ
• Ep. 228 - How to Start OT Cybersecurity ICS Security Fundamentals, Managed Switches Risk ManagementSep 11, 2025 · 1 hr 6 minIn this episode of Manufacturing Hub Podcast, hosts Vladimir Romanov and Dave Griffith sit down with Gavin Dilworth to explore the evolving world of ICS and OT cybersecurity. This is a topic that impacts every sector of manufacturing and critical infrastructure, yet many organizations still struggle with where to start, how to assess risk, and how to balance IT and OT responsibilities. Gavin brings decades of experience in automation engineering and cybersecurity, having worked across energy, oil and gas, water, and manufacturing. He shares his unique journey from being an operator and control systems engineer to becoming a specialist in OT cybersecurity. The conversation spans a wide range of issues, from asset inventory and managed switches to people, process, and technology frameworks that help organizations take the first step toward maturity. We discuss why IT and OT teams often clash and what it takes to bridge the gap. Gavin explains the realities of budgets, the challenges of compliance, and why self-reporting frameworks often fail to reflect true maturity. He also highlights the role of legislation in Europe, rising insurance premiums, and how cybersecurity assessments can influence financial and strategic decisions at the executive level. The episode provides clear insights into best practices such as building a proper asset inventory, structuring security awareness training for OT teams, and applying a risk-based approach to patch management. Gavin also outlines the importance of functional safety, process hazard analysis, and the role of frameworks like ISA/IEC 62443. For engineers, leaders, and decision makers, this conversation makes it clear that cybersecurity is not just a technology problem but a people and process challenge that requires long term discipline and investment. If you want to understand what real world OT cybersecurity looks like, what mistakes to avoid, and how to set a path toward resilience, this episode is packed with valuable takeaways. Timestamps 00:00 Introduction and upcoming ICC event 02:20 Gavin’s career journey from operator to cybersecurity expert 06:00 What ICS and OT cybersecurity really mean 09:00 Managed switches, firewalls, and securing industrial devices 11:00 The importance of people, process, and technology in security programs 13:30 Asset inventories and the first practical steps in cybersecurity 17:00 Insurance, legislation, and financial implications of OT risk 23:00 The problem with self reporting and maturity frameworks 27:00 Risk based patching strategies and CVE management 31:00 Physical keys, tokens, and access control challenges 37:00 IT versus OT ownership of cybersecurity 45:00 Certifications, training, and resources for professionals 53:00 Unified Namespace and cybersecurity considerations 58:00 Predictions for the next five years in OT cybersecurity 01:02:00 Career advice forPlayPlay Ep. 228 - How to Start OT Cybersecurity ICS Security Fundamentals, Managed Switches Risk Management
• Ep. 229 - Manufacturing Architecture Explained Every Engineer and Plant Manager Needs to Know TodayAug 29, 2025 · 1 hr 18 minIn this episode of Manufacturing Hub, Vlad and Dave take a deep dive into one of the most critical yet often overlooked aspects of modern manufacturing: network and systems architecture. Too often manufacturers focus on SCADA, MES, and control layers without recognizing that the architecture beneath them is the foundation that determines whether a facility can scale, connect new equipment, and maintain reliability. Architecture touches everything from plant floor PLCs and HMIs to edge devices, managed switches, firewalls, historians, and enterprise-level systems. We begin the conversation by unpacking what “architecture” actually means in manufacturing environments. Is it the hardware, switches, and cables? Is it the way new machines are integrated into existing plants? Or is it the broader strategy of ensuring that data, safety, and scalability are protected? The answer, as both Vlad and Dave explain, is that it is all of these at once. Throughout the discussion, we explore real-world stories where poor architectural decisions led to unplanned downtime, cybersecurity risks, or expensive rework. Vlad shares an example of a palletizer brought online with unmanaged switches and insecure remote access hardware that nearly crippled production until it was properly segmented. Dave recalls his own field experiences, including unusual setups where integrators resorted to improvised remote troubleshooting, highlighting just how creative but fragile some solutions can be. The episode also looks at the evolution of remote access. From the early days of Ewon boxes to modern expectations of secure VPNs, jump boxes, and approved engineering workstations, we discuss what role remote connectivity should play in today’s manufacturing environment. While these solutions can reduce travel time and speed up support, they can just as easily introduce vulnerabilities and trust issues if not carefully managed. From there we move into the technical tradeoffs of device level ring versus star topologies. Vlad explains why he often prefers device level ring to save costs and simplify troubleshooting, while Dave weighs in on the importance of pre-molded cables, managed switches, and long-term maintainability. We also analyze example architectures from Rockwell white papers, pointing out where diagrams align with field best practices and where they differ from what engineers often see in real facilities. Finally, we broaden the perspective by comparing greenfield and brownfield deployments. Greenfield projects allow prime contractors and consultants to design standards up front, but most facilities live in brownfield reality where years of technical debt, unmanaged switches, and ad hoc networks make improvements harder. We also touch on how architecture differs by industry, whether in food and beverage, pharmaceuticals, oil and gas, or distributed environments such as trains or pipelines. The conversation closes with predictions, careerPlayPlay Ep. 229 - Manufacturing Architecture Explained Every Engineer and Plant Manager Needs to Know Today
• Ep. 223 - Inductive Automation Ignition 8.3 New Siemens Driver Kafka Event Streams Historian Kevin MAug 21, 2025 · 1 hr 6 minThis week on Manufacturing Hub, Vlad Romanov and Dave Griffith are joined by Kevin McClusky, Chief Technology Architect at Inductive Automation. Kevin shares his journey from computer engineering into the world of industrial automation, his early experiences as an HMI developer, and his leadership roles at Inductive Automation that shaped the direction of Ignition software. The conversation takes a deep dive into the newly released Ignition 8.3 beta, exploring the core features that matter most for end users, system integrators, and manufacturers. Kevin discusses the new Siemens driver with symbolic addressing, the internal historian powered by QuestDB, the Kafka and Event Streams module, and the new DevOps capabilities with file system storage, Git integration, and automated deployments. These capabilities are set to change how manufacturers design, deploy, and scale automation systems in real-world production environments. We also preview the Ignition Community Conference (ICC), which is moving to a larger venue this year. Kevin outlines new additions such as the Hub, the CoLab, community design challenges, and the continuation of Prove It sessions. The episode also covers the evolution of the Build-On competition, the growing integrator ecosystem, and Inductive Automation’s continued focus on empowering its community through transparency and collaboration. This episode provides both a technical and strategic look at where Ignition is heading and why it matters for the future of industrial automation. If you are working on digital transformation, UNS, DevOps for OT, or enterprise-scale SCADA and MES, you will not want to miss this discussion. Timestamps 00:00 Introduction and welcome with Dave, Vlad, and Kevin 02:00 Kevin’s background and entry into industrial software 05:00 Lessons from early HMI and integrator experiences 07:30 The importance of integrators in Inductive Automation’s go-to-market strategy 09:00 Transition into sales leadership and learnings from global customers 13:00 Ignition 8.3 beta release process and development challenges 18:00 Historian improvements and introduction of QuestDB 21:00 The new Siemens driver and why it matters globally 27:00 Use cases for multiple historians and large-scale data performance 31:00 Kafka integration, Event Streams, and IT-OT convergence 35:00 DevOps capabilities in Ignition including Git and deployment modes 41:00 Preview of the Ignition Community Conference and new venue 44:00 The Hub, CoLab, and community-driven sessions at ICC 50:00 Prove It sessions and exhibitor highlights 56:00 The Build-On competition and its evolution 01:01:00 Predicting the future of ICC and Ignition 01:03:00 Kevin’s career advice for engineers and integrators 01:05:00 How listeners can connect with Inductive Automation References Mentioned in the Episode Inductive Automation: https://inductiveautomation.com/ Ignition 8.3PlayPlay Ep. 223 - Inductive Automation Ignition 8.3 New Siemens Driver Kafka Event Streams Historian Kevin M
• Ep. 216 - Redefining Manufacturing Resilience at Automate 2025 with Digital Twins and Copilot ToolsAug 18, 2025 · 14 minWelcome to our special coverage from Automate 2025, recorded directly at the Siemens booth. In this episode of Manufacturing Hub, hosts Vlad Romanov and Dave Griffith sit down with Chris Stevens and Annemarie Breu from Siemens to explore the evolving landscape of manufacturing resilience, digital twins, and automation lifecycle management. This conversation dives into how manufacturers can prepare for disruptions, scale pilot projects into real business outcomes, and adopt technologies that make factories more flexible and robust. Chris highlights the importance of people and processes in delivering exceptional customer experiences, while Annemarie emphasizes how scaling technology deployments creates measurable business impact. Together, they outline how Siemens is helping manufacturers move from isolated pilots to large scale adoption, ultimately strengthening resilience and competitiveness in today’s uncertain environment. We examine the meaning of manufacturing resilience in practice, including how to withstand supply chain shocks, tariffs, and workforce challenges. The discussion also covers workforce empowerment and the need to make manufacturing attractive again, not only by deploying advanced technologies but also by enabling teams to own solutions from the ground up. A major theme is the role of the digital twin. Chris and Annemarie explain why starting in the virtual world is essential to validate designs, optimize processes, and minimize downtime risks. They address how digital twin adoption is becoming more accessible through as a service delivery models and collaborative environments where end users, system integrators, and technology providers all contribute. We also look at the connection between copilot technologies and both operations and engineering. Natural language copilots are enabling operators to troubleshoot equipment quickly and engineers to interact with simulation environments more intuitively. This shift is accelerating adoption while reducing barriers to advanced tools. Finally, the episode touches on automation lifecycle management, drawing parallels to product lifecycle management. By centralizing and version controlling automation artifacts such as PLC programs, HMI projects, and industrial edge applications, Siemens is paving the way for resilient and adaptable operations. If you are curious about the future of resilient manufacturing, digital twins, and adaptive automation, this episode provides both strategic and practical insights. Timestamps 00:00 Introduction live from Automate 2025 at Siemens booth 01:00 Guest introductions and roles at Siemens 02:00 Defining manufacturing resilience in today’s environment 04:00 Workforce challenges and empowering teams to drive adoption 05:00 Why digital twin is the starting point for resilient operations 07:00 Digital twin adoption for small and medium manufacturers 09:00 Collaborative engineering environPlayPlay Ep. 216 - Redefining Manufacturing Resilience at Automate 2025 with Digital Twins and Copilot Tools
• Ep. 221 - Manufacturing Intelligence: Data Collection, OEE, and Energy Monitoring Case StudiesAug 14, 2025 · 1 hr 9 minIn Episode 221 of Manufacturing Hub, hosts Vlad Romanov and Dave Griffith sit down without a guest to share valuable real-world lessons on data collection, manufacturing intelligence, and implementing solutions that deliver measurable ROI. This episode wraps up the month’s theme on manufacturing intelligence by tying together the insights from previous episodes and putting them into the context of real plant-floor projects. Vlad begins with an in-depth story from his time at Procter & Gamble, where he led an energy monitoring project with the ambitious goal of reducing power consumption by 20 percent. He explains the practical challenges of turning a corporate initiative into an actionable plant-level strategy, from limited baseline data to deciding between standalone meters and integrated monitoring solutions. Vlad shares the lessons learned in balancing cost, data ownership, and scalability, and why a more open solution can sometimes offer greater long-term value than proprietary systems. Dave then takes us into the world of pet food manufacturing, where millions of dollars in raw materials can be lost each year due to inaccurate batching and poor measurement practices. He walks through the process of defining the problem, setting up data collection without overhauling legacy systems, and using that information to identify overages, improve tolerances, and design remediation strategies. The conversation dives into practical engineering decisions, such as when to invest in VFDs for precision dosing, when to redesign process equipment, and how to ensure data insights lead to lasting operational changes. The discussion expands into organizational challenges, including why decision-makers often lack actionable visibility into losses, how to present findings in terms of tangible business impact, and the cultural shift required to actually use the data once it is available. Vlad and Dave also explore examples from discrete manufacturing, where OEE tracking and daily direction setting (DDS) meetings help guide capital allocation, continuous improvement initiatives, and team alignment. They share observations on why some facilities succeed with these systems while others fall back into old habits. Timestamps 00:00 Introduction to Episode 221 and monthly theme recap 02:00 Vlad’s background and approach to modernization projects 04:50 Dave’s background and focus on data-driven manufacturing solutions 06:30 Recap of previous episodes on data collection, historians, and MTP/MCP 07:30 Vlad’s Procter & Gamble energy monitoring project case study 13:40 Addressing power blips, capacitor banks, and ROI considerations 19:10 Choosing between proprietary and open monitoring solutions 23:40 Dave’s pet food manufacturing story and raw material variance 29:50 Methods for data collection without disrupting legacy systems 34:20 Improving accuracy, process changes, and remediation strategies 44:00 OrganizationaPlayPlay Ep. 221 - Manufacturing Intelligence: Data Collection, OEE, and Energy Monitoring Case Studies
• Ep. 220 - Data Foundations and Machine Context Protocol in Modern Manufacturing w/ Caleb EastmanAug 7, 2025 · 1 hr 10 minIn Episode 220 of Manufacturing Hub, we welcome back Caleb Flanigan to explore one of the most critical yet least understood topics in the evolution of smart manufacturing: MTP (Module Type Package) , MCP (Machine Context Protocol) , and how they are becoming essential enablers of safe and scalable AI adoption on the factory floor. Throughout this deep-dive episode, we uncover how these emerging standards form the backbone of adaptive plants: facilities capable of safely orchestrating decisions between humans, machines, and AI models. From OPC UA and AutomationML to edge computing and LLM-driven control systems, Caleb explains the architecture, mindset shifts, and implementation considerations that make this vision a reality. Key topics covered include : Why traditional SCADA and MES architectures are not AI-ready The real-world value of MTP in legacy Brownfield plants How Siemens’ Machine Proxy App and OPC UA servers act as translators between AI models and legacy PLCs Differences between machine states, control interfaces, and orchestrated services in modular manufacturing Why CLI skills and edge computing are foundational for the modern control engineer How to pitch digital transformation and AI investments to hesitant executives We also touch on organizational psychology, how internal champions get ignored without executive alignment, and the grim future for manufacturers still betting on ice cube relays. Whether you’re a plant engineer, systems integrator, or digital transformation leader, this conversation offers a bold but practical look at how to safely integrate AI into manufacturing control environments: starting with protocols and principles, not just hype. 🧠 Resources Mentioned : Siemens Industrial Edge: https://new.siemens.com/global/en/products/automation/industrial-edge.html Machine Context Protocol (MCP): https://www.anthropic.com/news/introducing-the-machine-context-protocol VDI MTP Standard: https://www.vdi.de/ Book Recommendation: How the World Really Works by Vaclav Smil 👤 Guest : Caleb Eastman, Siemens 📌 Theme : Data Foundations and Intelligent Manufacturing 🎙️ Hosts : Vlad Romanov & Dave Griffith ✅ Key Timestamps 00:00 Welcome Back and Wilborn Celebration 03:30 Caleb's Career Journey from Cisco Cert to Siemens 07:40 Why CLI and Networking Skills Matter in OT 10:00 What Is MCP and Why It Matters for Safe AI 13:00 MTP Overview: The USB of Modular Manufacturing 18:00 Why AI Needs Context-Aware Control Layers 21:00 Bridging Human and AI Control Setpoints 24:30 Brownfield Integration with Siemens Machine Proxy 27:00 Making the Case for AI Investment 31:00 The Future of Safe AI in Manufacturing Plants 36:00 Organizational ResisPlayPlay Ep. 220 - Data Foundations and Machine Context Protocol in Modern Manufacturing w/ Caleb Eastman
• Ep. 218 - How Siemens Is Building the Next Generation of PLCs and Edge Control Systems w/ BerndAug 4, 2025 · 21 minIn this episode of Automate 2025, we welcome Bernd Raithel from Siemens back to the show to discuss the evolution of industrial control systems and the future of manufacturing. As the Head of R&D for Siemens Factory Automation in the US, Bernd shares his unique perspective on bridging legacy PLCs with modern IT infrastructure, enabling software-defined automation, and empowering manufacturers with flexible and scalable digital tools. With deep insights into products like the S7-1200, S7-1500, TIA Portal, Sematic X, and Siemens Industrial Edge, Bernd explores how Siemens is supporting everything from small-scale modernization to large-scale transformation. We cover critical trends shaping the next generation of manufacturing, including the rise of virtual PLCs (vPLCs), integration of AI into control systems, the shift from hardware to software-defined automation, and the challenges of IT and OT convergence. Bernd also highlights the importance of version control, DevOps pipelines, and open edge development in making industrial systems more agile. We wrap up by looking at Siemens' global R&D structure, freemium software models for engineers, and how manufacturers can take their first steps into digital transformation—without boiling the ocean. This is a must-watch conversation for engineers, IT leaders, and decision-makers in the automation space looking to understand what the future of control and connectivity looks like. 🔗 Mentioned Tools and Technologies: Siemens S7-1200 and S7-1500 Siemens TIA Portal Siemens Sematic X Siemens Industrial Edge & Edge Developer Kit Siemens Unified vPLC (Virtual PLC) Codesys Git-style source control for automation AI Copilots for engineering and operations 📍 Timestamps: 00:00 Welcome and intro to Bernd Raithel’s new role 02:00 Siemens legacy in Johnson City and product milestones 04:00 Why software-defined automation is gaining traction 06:00 Edge computing, vPLCs, and building flexible architectures 08:00 The real-world challenges of IT and OT integration 10:30 Sematic X, version control, and agile OT tools 13:00 How Siemens runs global R&D across multiple continents 15:00 The future of manufacturing and PLC longevity 17:00 Balancing modern tools with 30-year lifecycle expectations 19:00 Starting points for digital transformation with Industrial Edge 20:00 Siemens freemium strategy and access to tools for engineers 📚 Learn More: Siemens Industrial Edge: https://new.siemens.com/global/en/products/automation/topic-areas/industrial-edge.html TIA Portal: https://new.siemens.com/global/en/products/automation/topic-areas/tia-portal.html Sematic X: https://new.siemens.com/global/en/products/automation/topic-areas/sematic-x.html Siemens Unified: https://new.siemens.com/global/en/products/automation/topic-areas/uPlayPlay Ep. 218 - How Siemens Is Building the Next Generation of PLCs and Edge Control Systems w/ Bernd
• Ep. 219 - Modernizing Industrial Historian for Scalable Manufacturing Data Architecture with JeroenJul 31, 2025 · 58 minWelcome to Episode 219 of Manufacturing Hub. In this episode, we dive into the evolution of industrial data infrastructure with Jeroen Coussement, Founder and CEO of Factry. Factry is building modern historian and MES software platforms that help manufacturers collect, contextualize, and act on operational data at scale. We unpack the critical role of historians in modern manufacturing environments. While traditional historians focused on archiving time-series data, today’s requirements go far beyond that. Jeroen outlines how a modern historian must fulfill three foundational roles: Efficient high-volume time-series data acquisition Contextual modeling across complex factory assets Democratized access and self-service tools for operations teams This episode covers: The differences between SCADA, MES, and historians The evolution from legacy platforms like OSIsoft PI to cloud-native historians Architectures for on-prem, cloud, and hybrid historian deployments Real-world use cases like wind turbine optimization for shadow flicker mitigation Common challenges in digital transformation, including network modernization and change management How manufacturers can scale from data collection to full analytics enablement Jeroen also shares why point solutions often lead to fragmentation, and how building a robust data foundation opens the door to advanced tools like AI, unified namespace, and better decision-making. 📍 Guest: Jeroen Coussement, Founder and CEO at Factry 🌐 https://www.factry.io 📚 Resources Mentioned: Factry Historian: https://www.factry.io/products/factry-historian IT/OT Insider: https://insider.itot.io Canary Historian: https://www.canarylabs.com/ AVEVA PI System: https://www.aveva.com/en/solutions/pi-system/ GE Proficy Historian: https://www.ge.com/digital/applications/historian Joltek Consulting: https://www.joltek.com/ ⏱️ YouTube Timestamps 00:00 Intro and welcome 02:00 Jeroen’s journey from bioscience engineer to founder of Factry 05:00 What is an industrial historian and why it matters 09:00 The relationship between SCADA, MES, and historians 12:00 Legacy historian vendors and what’s changing 15:00 The shift to cloud-native and open data systems 18:00 When and why manufacturers choose to implement a historian 21:00 Software cost vs implementation cost 23:00 Common historian architectures: on-prem, cloud, hybrid 27:00 Regional differences in adoption across US and Europe 30:00 Use case: Wind turbine shadow flicker mitigation via historian 35:00 Can historians ever feed data back into PLCs? 39:00 Change management and user training are key 42:00 Layering MES and quality tools on top of a historian 46:00 Why point solutions fail and unified platforms win 49:00 Empowering domain experts with self-service analytics 52:00 Predictions for the future of historians 54:00 Career advice for those entering tPlayPlay Ep. 219 - Modernizing Industrial Historian for Scalable Manufacturing Data Architecture with Jeroen
• Ep. 217 - Reshaping Manufacturing Data Strategy by Connecting Legacy Equipment to Modern PlatformsJul 24, 2025 · 1 hr 9 minData collection is no longer a back-office task. It is now the foundation of manufacturing intelligence. In this episode of Manufacturing Hub, we are joined by Brian Bribe, founder of Mach Controls, to explore the practical realities of modernizing data infrastructure inside manufacturing facilities. Brian brings a frontline perspective to OT architecture and walks us through what it actually takes to connect legacy equipment, build scalable pipelines, and enable true real-time decision-making. We dive deep into Unified Namespace (UNS) principles, the evolution of MQTT and Kafka in industrial settings, and why so many manufacturers struggle to get ROI from new digital systems. From co-op student to founder of a systems integration firm, Brian shares how his early hands-on experience shaped his understanding of controls, business systems, and the gaps in between. Topics include historian layers, challenges with SCADA-based centralization, how to scope a machine connectivity project, practical change management tips, and the path to flattened architectures using modern pub-sub tools. This is a must-watch for engineers, plant managers, and decision-makers looking to make sense of the data revolution inside their factories. 📌 Episode 217 is the first in our July theme focused on Data Collection for Manufacturing Intelligence. 🔗 Learn more about Manufacturing Hub: https://manufacturinghub.live 🔗 Explore Joltek consulting services: https://www.joltek.com/ ⏱️ Timestamps 00:00 Introduction and Overview of Data Collection Theme 02:00 Brian’s Journey into Controls Engineering and Integration 06:30 What Legacy Manufacturing Equipment Actually Looks Like 10:00 Why Data Collection is Often an Afterthought in Scope 13:50 The Disconnect Between Machines and Business Systems 17:00 Real-World Discovery Process for Machine Connectivity 22:00 Overcoming Internal Resistance to Data-Driven Projects 28:00 Strategies for Extracting Data from Obsolete PLCs 34:30 Direct Sensor to SCADA vs PLC-Driven Design Debate 41:00 Flattening the Architecture and Breaking the Purdue Model 55:00 What Unified Namespace Looks Like in Practice with UMHPlayPlay Ep. 217 - Reshaping Manufacturing Data Strategy by Connecting Legacy Equipment to Modern Platforms
• Ep. 215 - Robotics 2025: Fanuc, KUKA, & the Future of AI-Powered Automation Humanoids CybersecurityJul 17, 2025 · 1 hr 6 minIn this episode of Manufacturing Hub, we welcome back Pawel Krupa, founder of the Future Robotics YouTube channel, to dive deep into the rapidly evolving world of industrial robotics. With over a decade of hands-on experience integrating and programming systems from Fanuc, KUKA, and others, Pawel shares exclusive insights on some of the biggest changes reshaping robotics in 2025. These changes are not just cosmetic updates; they are being driven by new ISO standards and increasing cybersecurity requirements across industrial automation. We explore the hardware and software changes coming to Fanuc’s R-50iA cabinet, including multiple Ethernet ports, enhanced vision systems with built-in lighting, and a groundbreaking integration of Python for native robot programming. KUKA is also undergoing a major transformation with its KC5 slim cabinet and KUKA iiQ OS, a Linux-based control system with new UI, simulation environments, and plug-and-play capabilities. These updates signify a paradigm shift where robots become not only smarter and safer, but far easier to configure, maintain, and upgrade. The conversation expands into one of the most talked-about frontiers in robotics: humanoid robots. Are they just hype or do they have a real role to play in industrial environments? We assess the business case for humanoids, especially in facilities where traditional automation has been financially unjustifiable. From handling tasks like herb sorting in food production to stepping into high-risk environments, humanoids may soon bridge the automation gap in low-throughput, labor-intensive workflows. We also explore how AI is influencing robot deployment, from edge vision systems to cycle time optimization. Pawel outlines how drag-and-drop AI-powered tools are slashing development time for vision systems from hours to minutes, while also lowering the barrier to entry for those without years of machine vision experience. Vision systems that used to require complex calibration and scripting are now being trained on real-time images or CAD models, making robotic integration faster and more accessible than ever. Finally, we close with actionable startup ideas and a bold look into the future of collaborative robots, AI, and hybrid ecosystems of humanoids and industrial arms working side-by-side. If you're in automation, manufacturing, or considering a robotics venture, this episode is packed with strategic insight, technical knowledge, and forward-thinking ideas you won’t want to miss. 🔗 Explore more from Pawel Krupa: https://www.youtube.com/@FutureRobotics 🎙 Manufacturing Hub Archives: https://www.manufacturinghub.live/ 💡 Joltek Consulting Services: https://www.joltek.com/ ⏱️ Timestamps 00:00 – Intro and Overview of Robotics Coverage 03:00 – Pawel Krupa Introduction and Robotics Background 05:00 – Cybersecurity-Driven Changes to Industrial Robots 06:30 – Fanuc R-50iA Cabinet Updates and Python Integration 11:PlayPlay Ep. 215 - Robotics 2025: Fanuc, KUKA, & the Future of AI-Powered Automation Humanoids Cybersecurity
• Ep. 214 - Robotics Rewired: Building Smarter Systems for Tomorrow's FactoryJul 10, 2025 · 1 hr 2 minWelcome to another episode of Manufacturing Hub! In this week’s episode, we dive deep into the evolving world of robotics with returning guest Sean Dotson, now CEO of Elite Robotics. From building large-scale material handling systems to exploring the future of AI-driven robot programming, Sean shares a candid view of what it really takes to modernize factory operations. We explore: What “material handling” really means in practice The real-world complexity of end-of-arm tooling and vision systems Why standardization is critical for both integrators and manufacturers What robotics programming and automation roles will look like in the next five years The practical limits of robots-as-a-service and humanoid hype Using generative AI and GPTs to assist in controls programming Career advice for engineers breaking into robotics and automation Plus, Sean shares some incredible stories from the field, including building a machine for radioactive seed sorting and handling rocket-propelled grenade components safely with robots. 🔥 Whether you're an engineer, systems integrator, or a manufacturing leader, this episode offers tactical insights and thoughtful strategy. 🔗 Learn more about Sean’s company: https://eliterobotics.com 📫 Contact Sean directly: sean@eliterobotics.com 🔗 Connect with Vlad: https://www.linkedin.com/in/vladromanov 🔗 Learn more about Joltek: https://www.joltek.comPlayPlay Ep. 214 - Robotics Rewired: Building Smarter Systems for Tomorrow's Factory
• Ep. 213 - The AI Revolution in Manufacturing: Productivity Gains and Cultural ShiftsJul 3, 2025 · 1 hr 10 minIn this episode of Manufacturing Hub , we welcome back Billy Albritton for a deep dive into the evolving world of artificial intelligence in manufacturing. Billy first joined us on Episode 23, and now almost 200 episodes later, he returns to share his perspective on how far the space has come and what the future holds. Billy walks us through his journey from the military to advanced manufacturing and ultimately to becoming a leading voice in the AI and digital transformation space. We explore how large language models like ChatGPT are already changing how we write code, design solutions, and even train junior engineers. He offers real-world use cases of generative and agentic AI in industrial contexts and explains how tools like Cursor are already being used to automate everything from software development to curriculum generation. We unpack the cultural barriers that prevent AI from being adopted on the plant floor and how forward-looking companies can implement AI safely and ethically. From internal teams building custom tools to small agile firms delivering big results, the conversation highlights the shift in power and opportunity across the ecosystem. Billy also gives us a glimpse into the near future of AI-enhanced humanoid robots, local LLM deployments on the shop floor, and what might happen to traditional job roles as these technologies scale. Whether you are an engineer, developer, plant manager, or simply curious about how AI is impacting the real world, this episode will give you both insights and practical strategies to consider. Stick around until the end to hear Billy’s predictions for the next five, ten, and twenty years in manufacturing. And if you’re wondering how to get started with AI tools, Billy offers concrete advice and resources you can begin exploring today. Timestamps: 00:00 Welcome back Billy Albritton 02:00 Billy’s path into manufacturing and robotics 06:00 How ChatGPT shifted Billy’s perspective 10:00 What is agentic AI and why it matters 15:00 The changing role of junior developers 20:00 AI in traditional enterprise software vs the real factory floor 27:00 Challenges with industrial AI adoption 32:00 Internal vs external development strategies 37:00 Billy’s go-to AI tools and workflows 45:00 Real-time AI assistants and the new software paradigm 53:00 Is there a ceiling to generative AI? 59:00 The future of robotics and humanoids 1:03:00 What happens to work in a post-AI world? 1:06:00 Advice for anyone looking to start with AI today Connect with Billy https://www.linkedin.com/in/billyalbritton/ Follow us Host: https://www.linkedin.com/in/vladromanov/ Show: https://www.manufacturinghub.live/</PlayPlay Ep. 213 - The AI Revolution in Manufacturing: Productivity Gains and Cultural Shifts
• Ep. 212 - Real Applications of AI in Manufacturing and What Still Needs WorkJun 19, 2025 · 1 hr 1 minAI is making headlines across every industry, but how much of it is actually being used on the manufacturing floor? In this episode of Manufacturing Hub, Vlad and Dave return to the whiteboard to explore practical and real-world applications of artificial intelligence in manufacturing. From pre-operations to live production, this session covers how AI is being used today across CAD tools, BOM generation, predictive maintenance, system optimization, and machine vision. We also talk through the risks, the limitations, and what still requires human judgment. We begin with design tools and programming before the machine even starts. Then we move through how AI is being used during operations for tasks like work order creation, failure detection, and PLC coding assistance. We explore real use cases for predictive maintenance and ask the tough question: what value are companies actually getting from this technology? Later in the episode we shift into optimization strategies. How can AI help increase throughput or reduce energy costs based on historical data? What does it take to apply these methods in mid-market factories, not just Fortune 100 environments? We also dive into quality inspection and machine vision. These applications are among the most mature in manufacturing today, and we break down examples like barcode inspection, defect detection, and using AI to adapt based on customer complaints. Throughout the episode we share insights from the field and address audience questions about generative AI, simulation tools, and where human expertise still matters most. Referenced in this episode Phoenix Contact case study from Episode 173: https://www.youtube.com/watch?v=ZoQjowwDi2M Siemens and Microsoft Copilot initiative Emerson, Bentley Nevada, and GE predictive maintenance platforms University of Tennessee Reliability and Maintainability Center: https://www.rmc.utk.edu UR and Spectral vision systems seen at Automate 2025 Teledyne and Cognex AI-based machine vision tools Cone GAVIN and Siemens Process Simulate Joltek – consulting for manufacturing strategy, automation, and digital transformation: https://www.joltek.com/ This is Episode 212 of Manufacturing Hub, your go-to resource for conversations between real practitioners in industrial automation and manufacturing. Join us live every Wednesday at 4 PM Eastern and follow along on YouTube, LinkedIn, and all major podcast platforms.PlayPlay Ep. 212 - Real Applications of AI in Manufacturing and What Still Needs Work
• Ep. 211 - Here's How Manufacturing Industry Leaders Are Actually Building the Factory of the FutureJun 16, 2025 · 2 hr 53 minIn this special edition of Manufacturing Hub, we take you inside one of the most transparent and technically rigorous events in industrial automation: ProveIt 2025 . Created by Walker Reynolds and the team at 4.0 Solutions, ProveIt brings together 36 vendors to solve real manufacturing problems inside a live virtual factory environment. Everything is connected through a Unified Namespace and powered by real-time MQTT infrastructure. Unlike traditional expos, ProveIt is not about product demos. It's about execution. Vendors were given access to production data, a shared namespace, a deadline, and a challenge: prove your solution works—live, with full transparency around time, cost, and outcomes. Featured Guests We speak with industry leaders and innovators including: Walker Reynolds from 4.0 Solutions Travis Cox from Inductive Automation Benson Hougland from Opto 22 Caleb and Sophia from Siemens (WinCC OA and Industrial Edge) Mark and Harry from Tatsoft Frameworks And many more voices from across the Manufacturing Hub community What You'll Learn Why ProveIt is reshaping the way we evaluate industrial tech How Unified Namespace is implemented at scale Real examples of cost, delivery time, and performance data Building resilient MQTT architectures for edge-to-cloud AI and machine learning use cases that go beyond dashboards Why transparency and interoperability matter more than ever Lessons in vendor selection, technical strategy, and scalability How real manufacturers are architecting their next-gen stacks Explore the Technologies Featured ProveIt and 4.0 Solutions https://www.40solutions.com https://www.proveit.live UNS and Industry 4.0 Learning https://www.iiot.university https://www.youtube.com/@4.0Solutions MQTT Infrastructure HiveMQ – https://www.hivemq.com Tatsoft Frameworks – https://tatsoft.com SCADA and Edge Platforms Inductive Automation – https://inductiveautomation.com Opto 22 – https://www.opto22.com Siemens WinCC OA – https://new.siemens.com/global/en/products/automation/industry-software/automation-software/scada/wincc-open-architecture.html Siemens Industrial Edge – https://www.siemens.com/global/en/products/automation/industrial-edge.html Cloud and Data Services Google Cloud for Manufacturing – https://cloud.google.com/solutions/manufacturing Dell NativeEdge – https:/PlayPlay Ep. 211 - Here's How Manufacturing Industry Leaders Are Actually Building the Factory of the Future
• Ep. 210 - Automate 2025: Unified Namespace, Dockerized PLCs, AI & MoreJun 6, 2025 · 1 hr 3 minWelcome back to Manufacturing Hub! In this special episode, we dive into an Automate 2025 preview, joined by Brian Priebe from Mach Controls and James Brown from 4IR Solutions. We break down what to expect at Automate next week in Detroit (May 12 to 15), booth highlights, technology trends, and hands-on insights into cutting-edge industrial solutions like Unified Namespace, Dockerized PLCs, AI applications in manufacturing, and more. Topics discussed: ✅ What's new at Automate 2025 ✅ The Mach Controls ProveIt demo ✅ Building practical data infrastructure for manufacturers ✅ Unified Namespace architecture and UMH ✅ Docker containers in industrial environments ✅ AI's real potential in manufacturing operations ✅ How small to mid-size manufacturers can advance digital maturity ✅ 4IR Solutions’ Factory Stack offerings ✅ Best practices for building scalable, future-proof architectures Guest highlights: 🔹 Brian Priebe, President of Mach Controls 🔹 James Brown, CEO of 4IR Solutions References Automate Show United Manufacturing Hub Inductive Automation Ignition Opto 22 Phoenix Contact Booth locations at Automate 2025: Siemens Booth #3232 Phoenix Contact Booth #5232 Inductive Automation Booth #3452 If you’re attending Automate, be sure to stop by these booths to check out demos, meet the community, and explore how modern architectures are shaping the future of manufacturing! Join the conversation: Are you exploring AI, Unified Namespace, or modern data architectures in your plant? Drop your questions or comments below! Follow us: https://www.manufacturinghub.live Joltek FRAMEPlayPlay Ep. 210 - Automate 2025: Unified Namespace, Dockerized PLCs, AI & More
• Ep. 209 - From PLCs to SCADA and MES Dylan's Real-World Journey Through Modern Manufacturing SystemsMay 23, 2025 · 1 hr 14 minIn Episode 209 of Manufacturing Hub, we sit down with Dylan to explore the full spectrum of automation—from his early hands-on experiences in PLC programming all the way to architecting full-scale SCADA and MES systems. If you're looking to understand what it really takes to grow a career in industrial automation, this conversation delivers raw insights, practical lessons, and battle-tested strategies from the plant floor to the boardroom. Dylan shares how his career evolved from service technician to systems integrator, detailing the learning curve involved in jumping between platforms like Ignition, FactoryTalk, Wonderware, and SQL databases. We dig into real-world project challenges, the importance of simulation and testing, and what it means to deliver systems that operators actually enjoy using. Along the way, Dylan offers valuable advice on how to learn faster, deal with unclear project scopes, and design better user interfaces by borrowing principles from modern UX and UI design. We also examine: Why ownership and internal technical teams are critical for end users The importance of interoperability and avoiding vendor or integrator lock-in How project creep really happens and what you can do about it Visualization trends in SCADA and HMI systems, including practical opinions on high-performance design and AR/VR Data strategies for manufacturing, from pipe-level decisions to planning for future use cases Dylan’s new venture, Abelara, and how it helps manufacturers align executive vision with plant-floor execution This episode is a must-listen for engineers, integrators, and manufacturing leaders looking to modernize their operations while keeping both usability and scalability in mind. Whether you’re early in your automation career or navigating complex transformation efforts, you’ll walk away with insights you can apply immediately. ⏱ Timestamps: 00:00 – Introduction 00:08 – What is Manufacturing Hub? Meet Dylan, our guest 02:00 – Dylan’s career path from tech school to SCADA systems 04:00 – Early project experience and rapid on-the-job learning 06:30 – Moving from PLCs to SCADA and MES development 08:20 – Learning without mentors: forums, support lines, and trial by fire 10:10 – Challenges and opportunities with modern control platforms 12:00 – Vendor openness, interoperability, and practical system limitations 15:00 – Scope creep and how to reduce it with better project planning 17:00 – The role of simulation and show-and-tell in successful startups 20:00 – Getting end user buy-in from operators to executives 22:15 – UI and UX in industrial systems: beyond standards and templates 26:00 – Why most HMI screens are outdated and how to improve them 30:00 – Using consumer design trends in industrial HMI development 33:00 – Ownership vs. partnership: the evolving role of integrators 36:00 – Visualization tools: what's working and whPlayPlay Ep. 209 - From PLCs to SCADA and MES Dylan's Real-World Journey Through Modern Manufacturing Systems
• Ep. 208 - Modernizing Manufacturing: Insights on Cybersecurity, Obsolescence, and AI IntegrationMay 8, 2025 · 1 hr 10 minIn this episode of Manufacturing Hub, co-hosts Vlad and Dave turn the spotlight on themselves and share deeply practical stories from the front lines of industrial transformation. With decades of experience consulting across manufacturing verticals, they unpack some of the most pressing (and often misunderstood) topics shaping the future of factories today—from aging infrastructure and insurance-driven cybersecurity to real-world applications of artificial intelligence and organizational change. If you're a plant manager, controls engineer, systems integrator, or digital transformation leader, this episode delivers grounded, no-fluff advice you can apply right away. 🧠 Key Themes & Topics Covered: 🔐 Cybersecurity as a Financial Decision: Vlad explains how cybersecurity initiatives often originate from IT and are directly influenced by rising insurance premiums, making cyber-risk quantifiable. Learn how assessments now inform insurance underwriting and why updating your legacy OT systems could lower your premiums and risk exposure. 🛠️ Obsolescence Assessments & Risk-Based Planning: Explore the actual workflow of auditing plant-floor systems, from identifying unsupported PLCs (like PLC-5s or Data Highway+) to negotiating priorities between IT directors, engineering teams, and insurance firms. Vlad shares real examples of balancing modernization costs with production constraints and process uptime. 📊 Why Assessments Are Just the Beginning: Understand how post-audit phases translate into strategic proposals that combine low-hanging fruit projects with long-term roadmaps. Learn how organizations build 3–5 year modernization strategies—without bringing operations to a halt. 🤖 AI Strategy in Manufacturing—Beyond the Hype: Dave shares how enterprise leaders—from CEOs to HR and IT departments—are approaching AI with curiosity but confusion. He outlines a clear framework for structuring executive workshops, evaluating tools, and identifying high-impact use cases across functions (from maintenance to HR to accounting). 🧩 AI Agents, Co-Pilots, and the Future of Decision-Making: Explore the evolving role of AI agents and LLM-based tools on the shop floor. Dave breaks down what AI agents are, how they might function in the future (e.g., executive dashboards that talk back), and what security hurdles still block widespread deployment in industrial settings. ⚠️ The Reality of Change Management: Implementing new tech is hard. Dave discusses how real change happens only when frontline champions (not just executives) see personal value in new tools. Hear the story of how one skeptical veteran technician became a project’s biggest advocate—once it solved a pain point he had lived with for decades. 🔁 IT/OT Alignment & Organizational Silos: The hosts discuss why most enterprise-scale modernization efforts stall—not due to technical complexity, but due to siloed budgets, conflicting incentives, aPlayPlay Ep. 208 - Modernizing Manufacturing: Insights on Cybersecurity, Obsolescence, and AI Integration
• Ep. 207 - From Bioreactors to Vaccines: What You Need to Know About Life Sciences AutomationMay 1, 2025 · 1 hr 6 minIn this episode of Manufacturing Hub, we welcome Amy Williams, Systems Architect at Skellig, for a deep dive into the world of life sciences manufacturing, a rarely explored but incredibly complex part of the industrial landscape. From her roots in biomolecular chemical engineering to her hands-on role in Operation Warp Speed, Amy walks us through what it's really like to build and validate manufacturing systems for pharmaceutical and biotechnology applications under FDA regulation. 💊🧪 We explore: What exactly qualifies as "life sciences" in manufacturing Why GMP compliance and validation are critical, and how they slow everything down How Operation Warp Speed succeeded in compressing a 10-year process into months The role of automation, MES, and DCS in life sciences Why paper-based MES is still sometimes the fastest way forward (and why that needs to change) How companies are moving toward digitization, better data exchange, and process analytical technology (PAT) Amy also shares her thoughts on: The importance of cross-functional collaboration in regulated environments Tips for engineers looking to break into the life sciences space Why owning your control code might be more valuable than you think If you're in automation, MES, or engineering leadership, and especially if you work in or around FDA-regulated industries—this episode is a must-listen. 🎧 Subscribe for more practical conversations at the intersection of manufacturing, automation, and strategy. 🔗 Connect with Amy: https://www.linkedin.com/in/amy-williams-automation 📚 Book Recommendation: The Technology FallacyPlayPlay Ep. 207 - From Bioreactors to Vaccines: What You Need to Know About Life Sciences Automation
• Ep. 206 - From Plant Floor to Strategy: Ryan Cahalane on Fixing What Matters in ManufacturingApr 24, 2025 · 1 hr 13 minWe’re kicking off a new theme—Faces You Should Know in Manufacturing—with none other than Ryan Cahalane, Managing Partner at Axiom Manufacturing Systems. Ryan’s path through manufacturing is anything but ordinary: from plant floor engineering at Goodyear, to leadership roles at GE, Rockwell Automation, OSIsoft, and more, Ryan has worked every angle of the manufacturing ecosystem. In this episode, Ryan joins Dave and Vlad to unpack the biggest real challenges manufacturers are facing today—not the buzzwords, not the hype, but the deep, persistent problems slowing progress across the industry. We discuss: Why there’s no one-size-fits-all solution—and why misalignment is more common than we admit The skill gap crisis: it’s not just about training, it’s about pay, experience, and opportunity The AI distraction: why most companies aren’t ready, and how AI is best used today in manufacturing The dangers of LinkedIn echo chambers and shiny object syndrome in tech selection Why engineers struggle to move into consulting—and why they shouldn’t be afraid to try The unique challenges (and hope) in mid-market manufacturing—and how nimble companies can still win The need for a Sherpa, not a savior: how consultants should support, not dictate Ryan’s story is filled with rich personal insights: from trading stocks and working at Deloitte, to recovering from a stroke and launching Axiom, he brings a grounded, field-tested perspective that connects strategy, operations, and technology in ways few others can. If you're a plant manager, engineer, executive, or someone who helps manufacturers grow—this conversation will challenge your assumptions, validate your experiences, and probably make you laugh. This isn’t just another talk about “digital transformation.” It’s a real look at what it takes to lead, adapt, and deliver in a manufacturing world that refuses to sit still.PlayPlay Ep. 206 - From Plant Floor to Strategy: Ryan Cahalane on Fixing What Matters in Manufacturing
• Ep. 205 - What Manufacturers Need to Know About UNS, MQTT, and Ignition After Prove ItApr 17, 2025 · 38 minWelcome back to a special Thursday edition of Manufacturing Hub! In this episode, we dive deep into one of the standout presentations from the Prove It conference — featuring Travis Cox from Inductive Automation and Arlen Nipper from Cirrus Link Solutions. 🎥 We start by reflecting on the Prove It showcase, where Travis and Arlen demonstrated the power of Unified Namespace (UNS) and MQTT across every layer of the solution stack — from Edge devices, to the Ignition Gateway, to the Cloud. ➡️ Watch as we discuss their approach to scalability, ease of deployment, and why Ignition continues to lead the way in industrial digital infrastructure. During the show, we cover: ✅ The real-world adoption of MQTT vs OPC UA in manufacturing environments, and why OPC UA is still dominant in many industries. ✅ Why naming conventions and early standardization are critical for successful UNS architectures. ✅ How to tackle data contextualization and overcome the "tech debt" so common in brownfield facilities. ✅ The importance of leadership-driven digital transformation and true IT/OT convergence. ✅ Why future-ready architectures require blending traditional technologies like OPC UA with MQTT and open standards. ✅ Insights into how small, medium, and enterprise manufacturers should approach digital transformation differently. Travis shares incredible insights on: 🔹 The evolution of Ignition and its role as an IIoT platform 🔹 Why a common digital infrastructure is non-negotiable for scaling 🔹 How even small wins (like energy monitoring) can spark major cultural shifts in manufacturing organizations 🔹 The growing role of IT leaders in successful plant floor modernization efforts 🔹 How AI, ML, and advanced analytics will shape the future of real-time industrial operations We also dive into broader industry trends seen at Prove It, including how other platforms like Frameworks (Tatsoft) and WinCC OA (Siemens) position themselves in the evolving digital manufacturing landscape. Helpful Links: 🔗 Learn more about Inductive Automation: https://inductiveautomation.com 🔗 Manufacturing Hub Podcast Archives: https://manufacturinghub.live Timestamps: 0:00 - Intro and Prove It Recap 5:30 - First impressions of the Inductive Automation session 11:50 - MQTT vs OPC UA in real-world manufacturing 18:10 - Challenges of UNS deployment and the importance of standards 28:40 - IT/OT convergence and building unified teams 38:20 - What sparks digital transformation success? 47:10 - How Ignition fits into modern industrial architectures 55:00 - Closing thoughts on Prove It and the future of manufacturing 🔔 Subscribe for more conversations on industrial automation, digital transformation, and manufacturing leadership every week!PlayPlay Ep. 205 - What Manufacturers Need to Know About UNS, MQTT, and Ignition After Prove It
• Ep. 204 - Making ERP Work in Manufacturing | ERP Deep Dive with GlennApr 13, 2025 · 1 hr 23 minIn Episode 204 of Manufacturing Hub, we wrap up our month-long ERP series with Glenn from Waites. Glenn shares a practical framework for understanding ERP systems—perfect for engineers, plant managers, and anyone who’s struggled with clunky ERP software. We break down key modules like Financials, Supply Chain, MES, and Asset Management, and explore how modern tools are reshaping ERP usability. 🔹 What You’ll Learn: Glenn’s 3-part ERP mental model: Master Data, Transactions, Workflow The difference between push vs. pull supply chain systems (MRP vs. Lean) Why gross margin is the #1 financial metric you need to watch How MES and condition monitoring tools integrate with ERP Practical advice for engineers navigating digital transformation & MBAs 💡 Perfect for anyone struggling to make sense of their ERP, or looking to modernize their stack without losing their sanity. 📘 Recommended Reading: Lessons in Industrial Instrumentation by Tony Kuphaldt – Free online technical resource 👤 Guest: Glenn – Chief Product Officer at Waites and co-founder of a new digital transformation consultancy with Dylan Dufrene 🛠️ Sponsored by Talan Experts in ERP integration across SAP, Microsoft Dynamics, and Oracle Learn more: https://www.talan.com Catch Elvis from Talan in Episode 199 📌 Watch all ERP Month episodes: 199, 201, 203, 204 🔔 Don’t forget to Like, Subscribe & Hit the Bell! #ERP #Manufacturing #MES #DigitalTransformation #IndustrialAutomation #ManufacturingHub #EngineeringLeadership #SCADA #PlantOperations #Waites #Talan ****** Connect with Us Vlad Romanov Dave Griffith Manufacturing Hub SolisPLC JoltekPlayPlay Ep. 204 - Making ERP Work in Manufacturing | ERP Deep Dive with Glenn
• Ep. 203 - From Spreadsheets to Structure: ERP for Machine Builders & SIsApr 10, 2025 · 1 hr 9 minIn this episode, Dave and Vlad are joined by Jay and RJ from Total ETO to explore the often overlooked world of ERP for machine builders and systems integrators. While ERP conversations often focus on large-scale deployments like SAP or Oracle, this episode dives into the day-to-day of smaller, engineer-to-order (ETO) businesses—where spreadsheets still reign and project complexity is high. Jay and RJ share their unique perspectives—Jay coming from 25 years in automation and becoming a Total ETO user-turned-employee, and RJ bringing three decades of software expertise focused specifically on this niche. Together, they break down: The unique ERP needs of custom machine builders and SIs Why project-based workflows don't fit traditional manufacturing ERPs Common pitfalls like spreadsheet reliance and change order chaos The difference between machine builders and system integrators (and how ERP can serve both) How they approach implementation in 4–6 months, not 4–6 years Why people who've used Total ETO often end up joining the company Whether you're managing projects off scratch paper or already in the market for your first ERP, this episode is full of insights on how to bring structure and visibility to custom manufacturing. 💡 Key Topics [00:02:00] Intro to Total ETO and backgrounds of Jay and RJ [00:12:00] The life of a machine builder: high variability, custom BOMs, and the project-first mindset [00:22:00] Why most ETO businesses still run on spreadsheets [00:31:00] The emotional journey from ERP user to ERP evangelist [00:39:00] System integrators vs. machine builders: similar goals, different workflows [00:47:00] Why one-size-fits-all ERP fails for custom equipment manufacturing [00:58:00] Getting buy-in for ERP: from small teams to company-wide rollouts [01:07:00] Implementation: how Total ETO does it in under 6 months [01:18:00] Integration with CAD tools like SolidWorks and Inventor [01:26:00] The future: AI, web platforms, and the changing face of manufacturing software 🧠 Memorable Quotes “Spreadsheets give me nightmares. That’s the main thing.” – Jay “Nothing gets done accidentally. You have to make ERP implementation a priority.” – RJ “We’re often a company’s first ERP—and we aim to be their last.” – RJ “Everything in ETO is dynamic. It’s not static like mass production. And your ERP needs to reflect that.” – Jay 📚 Book & Content Recommendation 📰 Automation AMA – The Automation Navigator by Sean Dotson Recommended by both Jay and RJ as an insightful, down-to-earth read for automation professionals. 🎉 Shoutouts Thanks to TALAN for sponsoring this month’s ERP theme! And a special mention to Taylor Dykstra for supporting Total ETO at ProMat this week! ****** Connect with Us Vlad Romanov <a href="https://www.linkedin.com/in/davegrifPlayPlay Ep. 203 - From Spreadsheets to Structure: ERP for Machine Builders & SIs
• Ep. 202 - Inside Opto 22: Unified Namespace, Edge Computing, and Cybersecurity @ ProveItApr 3, 2025 · 30 minWhat does it take to move from automation hype to practical, scalable solutions on the factory floor? In this deep-dive episode of Manufacturing Hub, recorded live at the ProveIt Conference, we’re joined by Benson Hougland, Vice President at Opto 22—a company that has been quietly shaping the future of industrial automation for over 50 years. Benson walks us through the journey of Opto 22: from its roots as the birthplace of the solid-state relay to becoming a leader in edge-native control platforms with the groov EPIC and groov RIO product lines. More importantly, he reveals how Opto 22 is tackling two of the most critical challenges in modern manufacturing: democratizing OT data and cybersecurity at the edge. We cover: ✅ Who Opto 22 really is and what they set out to "prove" at the ProveIt Conference ✅ The role of the Unified Namespace (UNS) in enabling real-time industrial data architecture ✅ How Opto’s platforms help solve the "dark asset" problem in brownfield facilities ✅ Cybersecurity by design—not just bolted on later ✅ Why the controller of the future is more like a smartphone than a flip phone ✅ Running containers on the edge: what this unlocks for OT teams ✅ Long-term partnerships with companies like Inductive Automation and why that matters ✅ How Opto 22 systems remain IT-friendly, OT-usable, and fully made in the USA ✅ Their collaboration with the State of Indiana to bring energy-focused digital transformation to SMB manufacturers ✅ Lessons from past moonshots—like cellular control systems with Nokia that were ahead of their time ✅ What’s next: ML at the edge, scalable architectures, and more accessible solutions for plants without big digital teams Throughout the conversation, Benson emphasizes a philosophy that will resonate with anyone trying to lead transformation in manufacturing: start small, solve a real problem, and scale with purpose. Whether you're tackling legacy infrastructure, looking to secure your OT layer, or just trying to make sense of the noise in the automation space, this episode will leave you with tangible ideas and a clear-eyed view of what's possible. 🎧 Plus: Why PLCs need to behave more like clients, why MQTT is so central to modern architectures, and how to get buy-in from leadership with energy wins. ****** Connect with Us Vlad Romanov Dave Griffith Manufacturing Hub SolisPLC JoltekPlayPlay Ep. 202 - Inside Opto 22: Unified Namespace, Edge Computing, and Cybersecurity @ ProveIt
• Ep. 201 - ERP in Manufacturing: Strategy, Culture, and Change ManagementMar 30, 2025 · 1 hr 11 minIn Episode 201 of Manufacturing Hub, we sit down with Tim Brown, a veteran leader with over 40 years of experience across manufacturing, construction, and IT. From managing massive ERP transformations to navigating global M&A integrations, Tim shares a masterclass in how to make enterprise software actually work in complex industrial environments. We cover everything from: What it was like managing ERP during Y2K The critical difference between push vs. pull drivers for ERP change How mergers and acquisitions shape ERP strategy Why “people problems” derail ERP more than technology ever does Real tactics for managing global rollouts (including Japan, France, Canada, and the U.S.) His take on embedded AI in ERP platforms (and where it's really going) Governance, risk, and how to actually drive adoption Whether you’re an IT leader, plant manager, systems integrator, or just ERP-curious — this episode offers real-world lessons and practical guidance from someone who’s done it all. 🔹 Thank you to this month’s sponsor: TALAN Helping manufacturers navigate ERP adoption, migration, and integration across SAP, Microsoft Dynamics, Oracle, and more. Meet them at the American Manufacturing Summit in Chicago on March 19–20, or visit their site to learn more. 👇 Drop your questions or share your ERP war stories in the comments — we’d love to hear from you! 📌 Chapters 0:00 Intro 4:00 Tim’s Background & ERP Journey 9:00 Y2K & Early ERP Lessons 15:00 ERP Triggers: Push vs. Pull 22:00 M&A Integrations: How It Actually Happens 30:00 Roadblocks: People, Culture, and “We’re Special” Syndrome 40:00 Standardization vs. Flexibility in Rollouts 48:00 ERP Selection: Process, Partners, and Politics 58:00 Risk Mitigation & Change Management 1:05:00 MES, Data Ownership & Operational Autonomy 1:18:00 AI & the Future of ERP 1:25:00 Career Advice from Tim 1:30:00 Final Thoughts & Book Recommendation 🎧 Listen to Episode 199 with Elvis (Talen) for more on ERP selection 👉 https://youtu.be/YOUR-LINK-HERE 🔗 Follow us on LinkedIn 📬 Never miss an episode — subscribe to the podcast on your favorite platform! ****** Connect with Us Vlad Romanov Dave Griffith Manufacturing Hub SolisPLC JoltekPlayPlay Ep. 201 - ERP in Manufacturing: Strategy, Culture, and Change Management
• Ep. 200 - From Plant Floor to Enterprise: Tatsoft Shows Off Frameworks IIoT PlatformMar 27, 2025 · 38 minIn this episode recorded live at the ProveIt Conference, we sit down with Mark and Harry from Tatsoft, creators of the industrial IIoT platform Frameworks. We dive deep into how Tatsoft is redefining what a true industrial platform should be — built from the ground up for the factory floor, yet scalable across the enterprise. Mark and Harry walk us through: Their platform’s positioning as a SCADA, HMI, MES, and IIoT toolbox — all in one How Frameworks handles real-time data, from connectivity (MQTT, OPC UA, SQL) to transformation and dynamic visualization Why the “extra I in IIoT” matters when building for industrial environments The challenges of IT/OT integration, people gaps, and legacy systems — and how Tatsoft tackles them head-on A demo of their ProveIt solution, showing off auto-recognition of new assets, dynamic UI, and high-performance visualization across devices Whether you’re an end user, system integrator, or OEM, this episode will help you understand how Tatsoft’s Frameworks V10 is enabling fast, scalable, and future-proof industrial applications — without compromise. 🔗 Learn more about Tatsoft: https://www.tatsoft.com 🎥 Live from the show floor at ProveIt 2025. 📅 Watch Manufacturing Hub live every Wednesday at 4PM ET. ****** Connect with Us Vlad Romanov Dave Griffith Manufacturing Hub SolisPLC JoltekPlayPlay Ep. 200 - From Plant Floor to Enterprise: Tatsoft Shows Off Frameworks IIoT Platform
• Ep. 199 - ERP Implementation & Strategy: What Manufacturers Need to KnowMar 20, 2025 · 1 hr 7 minWelcome back to Manufacturing Hub! This March 2025, we’re diving deep into Enterprise Resource Planning (ERP), exploring its critical role in manufacturing, the challenges of implementation, and the future of ERP solutions. This episode is sponsored by Talan, a leading firm specializing in ERP adoption, migration, and integration. Enterprise Resource Planning (ERP) systems have been a cornerstone of manufacturing operations for decades. They provide a centralized platform for managing finance, supply chain, inventory, production, logistics, and human resources. As digital transformation accelerates, ERP systems are evolving with advancements in cloud computing, artificial intelligence (AI), and industrial data analytics. With an increasing number of manufacturers shifting from legacy on-premise systems to cloud-based ERP solutions, the landscape is rapidly changing. Our guest, Elvis Burcul, brings over 30 years of experience in enterprise solutions, asset-intensive industries, and ERP deployments. In this episode, we explore: ✔️ His journey from electrical engineering to enterprise systems ✔️ ERP fundamentals – What it is, why it matters, and key challenges in implementation ✔️ Triggers for ERP investment – When should companies consider upgrading or migrating? ✔️ ERP vendor landscape – From industry giants (SAP, Oracle, Microsoft) to emerging, specialized solutions ✔️ The impact of AI, cloud computing, and data strategy on ERP decision-making ✔️ How to avoid implementation fatigue and ensure a smooth rollout ✔️ The importance of governance, integration, and aligning ERP with business goals Why ERP Matters More Than Ever ERP systems continue to play a fundamental role in manufacturing, with nearly half of all manufacturers actively using or considering ERP solutions. The ERP market has grown significantly in recent years and is expected to nearly double in size over the next decade. As companies look for ways to enhance efficiency and streamline operations, ERP adoption is increasingly seen as a competitive necessity rather than a luxury. However, ERP implementations can be complex and costly, often taking years to fully integrate into a company’s workflow. Implementation fatigue, outdated data governance practices, and the struggle to extract meaningful insights from collected data remain significant barriers. A well-executed ERP strategy requires a clear roadmap, strong leadership support, and ongoing engagement with stakeholders to ensure long-term success. AI, Cloud, and the Future of ERP AI-powered ERP systems are now capable of predictive analytics, anomaly detection, and real-time decision-making, helping manufacturers optimize performance. Cloud-based ERP solutions are also reshaping the industry by providing greater scalability, accessibility, and security. The shift to cloud ERP allows companies to reduce infrastructure costs while improving data-driven decision-making throuPlayPlay Ep. 199 - ERP Implementation & Strategy: What Manufacturers Need to Know