Manufacturing Hub

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  Ep. 273 - How to Build a Systems Integration Company: Positioning, Money and Procurement 10.09.2026 1t 22min

  Most conversations about starting a systems integrator skip the parts that sink people. Dave and Vlad spend this one on insurance, licenses and procurement.After a month of founder interviews, Dave and Vlad close the series with their own experience. Vlad started at plant level with Procter and Gamble and Kraft Heinz, deciding how outside integrators would execute, before crossing over to work for an integrator across food and beverage and CPG packaging. Dave came from aviation and aerospace through a German machine builder and a distributor, then ran a small integration company doing MES, OEE and track and trace. Both reached the same conclusion. Integration starts after the requirements are written, so you quote to a spec and a budget, build the thing, and real handover rarely follows.Blame does not sit in one place. Vlad puts it plainly: people resent a solution that has not actually solved something for them. But end users say they do not need training and ask for the lowest number, and training is the first line cut. Dave counters that if a customer wants five dashboards on an ugly six inch HMI that has sat in the plant for fifteen years, that is the job. Vlad's answer is that your time is finite, and a year on work you cannot show anyone positions you as the person who does that work.The technical centerpiece is a migration that sounds nearly free. Moving from RSView 32 to FactoryTalk View gets justified because conversion tools exist. Then come the undocumented Visual Basic scripts written around tag limits on old controllers, which no conversion tool touches. Then the PLCs will not support the new terminals and servers, so the controllers go too. Then the networks underneath, often Data Highway Plus. Then servers, remote racks, IO, sensors and drives. Vlad argues these decisions get made by people who never price the second and third order effects.An integration firm is a service firm, billing time and materials or a fixed fee, with a markup on hardware and software. Vlad quotes roughly $200 a month for $2 million of liability coverage, a capable laptop, and software licenses reaching tens of thousands of dollars per seat without preferential pricing, usually several across PLC and HMI programming. Then procurement, which nobody warns new integrators about. Dave has cleared it in twenty minutes and has waited seven months, three or four of those with lawyers arguing over a master service agreement.Vlad closes on complexity. Industrial equipment no longer ships with a full schematic and a six dollar replacement sensor, so ramp up time climbs while the population who understand electrical, mechanical and process together shrinks as the best of them retire. Dave sees it from the other side. Entry now takes an LLC, a laptop and a phone, and he expects private equity to keep buying medium and large integrators over the next five years.Timestamps0:00 Introduction10:30 Vlad and Dave's paths into integration18:40 Why integrators start after the requirements are written23:40 Who is to blame when training gets cut30:00 RSView 32 migrations and the hidden cascade36:40 Choosing where you sit on the integration spectrum42:20 How integrators make money and what it costs to start48:40 Procurement and getting paid53:10 The future of integration and rising complexity1:01:40 Career advice1:13:20 The industrial app marketplaceReferencesThe Little Red Book of Selling by Jeffrey Gitomer: https://www.amazon.com/Little-Red-Book-Selling-Principles/dp/0743572548Influence, New and Expanded by Robert Cialdini: https://www.amazon.com/Influence-New-Expanded-Psychology-Persuasion/dp/0062937650About Your HostsVladimir Romanov is a co-host of The Manufacturing Hub Podcast and the founder of Joltek, an independent manufacturing and industrial automation consulting firm specializing in modernization strategy, digital transformation, and workforce development. Joltek works with manufacturers and investors to de-risk modernization and build the internal capability to sustain results.Connect with Vlad: https://www.linkedin.com/in/vladromanov/Want to go deeper? Vlad and the team at Joltek have covered related topics here:System Integrators: https://www.joltek.com/blog/system-integratorsRockwell PLC Lifecycle and Migration Guide: https://www.joltek.com/blog/rockwell-plc-lifecycle-migration-guideDave Griffith is a co-host of The Manufacturing Hub Podcast and founder of Capelin Solutions, an industrial automation firm helping manufacturers adopt smart manufacturing technology. He brings 15 years of experience in industrial automation and digital transformation.Connect with Dave: https://www.linkedin.com/in/davegriffith23/Subscribe to Manufacturing Hub: https://www.manufacturinghub.liveLinkedIn: https://www.linkedin.com/company/manufacturing-hub-networkYouTube: https://www.youtube.com/@ManufacturingHub
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  Ep. 272 - Systems Integration Careers: OEM, Distributor, Machine Builder and Business Owner 03.09.2026 1t 28min

  Most people ask how to start a systems integrator. Rich Kuechenmeister has effectively built one five times, and the lesson is that the parent business decides what you become.Rich is owner and partner at Fishbone Technical Services. Before that he built automation groups inside a semiconductor equipment OEM, an automation components manufacturer, a products distributor, and a custom machine builder where he stood up a UL 508A panel shop from nothing. Each of those businesses sold something different, and that changed the engineering. At a machine builder the machine is the dog and the controls are the tail. At a distributor you build toolkits so somebody else can build the solution, handcuffed to the lines you carry. Rich argues that constraint is what made him good, because a single vendor solution is easy while four component areas from four vendors is where real integration lives.His definition of a control systems integrator stays traditional. SCADA and below, field instrumentation through PLC and HMI, bridging a little into MES. Fishbone works line control, process control on boilers, pumps and valves, and material handling where suppliers ship a motor and a few sensors and nothing more.The business advice is specific. He would rather have one $100,000 project than ten $10,000 projects, because that is one project management cycle instead of ten. He cautions against mixing maintenance work and capital projects without a plan, since context switching between a vision system callout and a pump control program burns budget on both. Dave adds the pattern he keeps seeing: come in at the bottom and you get saved in the phone as the maintenance guy, never the capital project guy. Rich hires on desire, attitude and aptitude, and admits he was once the bottleneck himself.Looking ahead, he expects acquisitions to keep rolling up integrators and leaving a void underneath, since a twenty person firm will not get out of bed for the projects a five person firm lived on. On AI he is practical. He turned three day estimates into eight estimates in a single day, but insists code writing is a subset of the job. He is also still doing a PLC-5 conversion and a DeviceNet upgrade.About Rich KuechenmeisterRich Kuechenmeister is owner and partner at Fishbone Technical Services, a nationwide remote technical services company he co-founded in 2021 with business partner Robert Summers. Fishbone is based in Texas and covers plant engineering and control systems integration from field instrumentation through PLC, HMI and SCADA, with some MES. Rich began his career in the United States Navy working on radars, servos and guidance systems, then spent three decades in industrial automation building engineering groups before starting Fishbone.https://fishbonetechnical.comTimestamps0:00 Introduction2:20 Inside Fishbone Technical Services5:20 From the Navy to OEMs, distributors and machine builders9:00 Becoming unafraid and starting a company15:40 What a control systems integrator actually is20:40 How the parent business shapes the work31:40 Filling the sales hopper and qualifying projects36:40 Maintenance work versus capital projects43:00 Hiring for desire, attitude and aptitude48:20 Letting go of the client relationship56:20 Distributors, acquisitions and the void they leave1:04:40 AI, estimating and reverse engineering PLC codeReferencesPrOTect IT All by Aaron Crow: https://www.amazon.com/PrOTect-All-Plain-Spoken-Cybersecurity-Protecting/dp/B0HBM3F4XSISA/IEC 62443 Series of Standards: https://www.isa.org/standards-and-publications/isa-standards/isa-iec-62443-series-of-standardsAbout Your HostsVladimir Romanov is a co-host of The Manufacturing Hub Podcast and the founder of Joltek, an independent manufacturing and industrial automation consulting firm specializing in modernization strategy, digital transformation, and workforce development. Joltek works with manufacturers and investors to de-risk modernization and build the internal capability to sustain results.Connect with Vlad: https://www.linkedin.com/in/vladromanov/Want to go deeper? Vlad and the team at Joltek have covered related topics here:System Integrators: https://www.joltek.com/blog/system-integratorsEngineer to Entrepreneur in Manufacturing Technology: https://www.joltek.com/blog/engineer-entrepreneur-technology-business-manufacturingDave Griffith is a co-host of The Manufacturing Hub Podcast and founder of Capelin Solutions, an industrial automation firm helping manufacturers adopt smart manufacturing technology. He brings 15 years of experience in industrial automation and digital transformation.Connect with Dave: https://www.linkedin.com/in/davegriffith23/Subscribe to Manufacturing Hub: https://www.manufacturinghub.liveLinkedIn: https://www.linkedin.com/company/manufacturing-hub-networkYouTube: https://www.youtube.com/@ManufacturingHub
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  Ep. 271 - Growing an Oil and Gas Plus Mining Systems Integrator in Alberta with JPI Solutions 27.08.2026 1t 11min

  Oil and gas automation runs on royalty accounting as much as process control. Dustin Symes explains how that shapes every SCADA decision JPI Solutions makes.Canadian oil and gas is structured differently than most assume. In the US mineral rights usually sit with individuals, so custody transfer draws a hard line between upstream and midstream. In Canada the provinces hold most rights, so a producer can gather 100 wells into one plant and sell to a pipeline company there. That lands on the automation: much of the SCADA data collection exists to answer who is paying whom and how much royalty is owed. Once a well is drilled, automation might find 5 to 10 percent off nameplate, so the work protects a long production tail rather than chasing throughput.Mining behaves nothing like it. Thinner margins, $100 million capital projects, an hour long elevator ride down, underground space running 20 miles across. Those are small cities: control systems cover substations, air monitoring and lighting as well as conveyors and pumps. Mining clients want programmers on site rather than remote, and they buy for continuity: a major vendor PLC paired with their DCS, meant to last 20 years. Horizontal drilling has rescaled oil and gas, from one well and a dozen sensors to a 32 well pad carrying 300 IO, pushing designs toward redundant PLCs and ring networks. The genuinely new technology lands on the data layer, where MQTT and report by exception are displacing polled Modbus.Dustin set two gates before his first hire: enough cash banked to make that person whole for a month or two, and enough overload to have work worth delegating. He hired out of the instrumentation program at SAIT rather than a 15 year instrument mechanic. When he weighed taking on partners, dozens of people advised against it. He brought in Dan and Brent Lawther anyway in 2018, went from five people that spring to ten by the fall, and says JPI would not exist without them.His hardest won lesson is unglamorous. Communication is the only consistent complaint he has ever had from a customer. Nobody complains about the code. They complain that nobody told them it was finished. On AI, JPI is decompiling Rockwell files into shutdown keys and landing 85 to 90 percent of the way there on a good prompt, and running log analysis across FactoryTalk directory, HMI and historian logs to find real root causes. He expects PLC code to become text so it can be version controlled like software, and customers to treat that as baseline within five years.About Dustin SymesDustin Symes is Chief Technology Officer at JPI Solutions, a Calgary based systems integrator serving oil and gas and mining clients across North America from four offices in Alberta, BC and Saskatchewan. A Red Seal journeyman electrician who moved into automation, he founded JPI in 2017. JPI covers process control from the sensor to the HMI, then up into SCADA and corporate data.https://www.jpisolutions.caTimestamps0:00 Introduction5:50 Why he started JPI Solutions10:50 Oil and gas primer: upstream, midstream, downstream12:50 What makes mining automation different16:10 Where JPI sits in the automation stack28:30 Bigger well pads, redundant PLCs and MQTT41:20 Bringing on partners when nobody recommended it51:10 Communication as the only consistent complaint1:04:40 The future of integration, AI and knowledge graphsReferencesRadical Candor by Kim Scott: https://www.amazon.com/Radical-Candor-Kick-Ass-Without-Humanity/dp/1250103509Creativity, Inc. by Ed Catmull: https://www.amazon.com/Creativity-Inc-Overcoming-Unseen-Inspiration/dp/0812993012ThredCloud: https://www.thredcloud.comAbout Your HostsVladimir Romanov is a co-host of The Manufacturing Hub Podcast and the founder of Joltek, an independent manufacturing and industrial automation consulting firm specializing in modernization strategy, digital transformation, and workforce development. Joltek works with manufacturers and investors to de-risk modernization and build the internal capability to sustain results.Connect with Vlad: https://www.linkedin.com/in/vladromanov/Want to go deeper? Vlad and the team at Joltek have covered related topics here:System Integrators: https://www.joltek.com/blog/system-integratorsPLC Scan Cycles and SCADA Polling: https://www.joltek.com/blog/plc-scan-cycles-polling-scada-systems-dataDave Griffith is a co-host of The Manufacturing Hub Podcast and founder of Capelin Solutions, an industrial automation firm helping manufacturers adopt smart manufacturing technology. He brings 15 years of experience in industrial automation and digital transformation.Connect with Dave: https://www.linkedin.com/in/davegriffith23/Subscribe to Manufacturing Hub: https://www.manufacturinghub.liveLinkedIn: https://www.linkedin.com/company/manufacturing-hub-networkYouTube: https://www.youtube.com/@ManufacturingHub
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  Ep. 270 - How to Start a Systems Integrator: Scope, Hiring, and the Bottleneck That Is You 20.08.2026 1t 15min

  Most people who start a systems integrator expect to keep doing the engineering. Dylan DuFresne explains why that stops being true inside two years.Ask ten people what a systems integrator is and you get ten answers, so Dylan DuFresne starts from first principles: a third party that connects systems which used to sit isolated. The market then splits in two. One is the generalist who has seen a hundred platforms across a thousand facilities and knows how they behave together. The other is the specialist who lives inside one or two stacks. If you know what you are building, hire the specialist. If you are still deciding, the generalist saves you money.Abelara exists because of a pattern Dylan hit repeatedly during more than a decade inside other integrators. By the time a client calls, the platform is chosen, the budget is set, and the outcome is locked in, even when that platform cannot deliver it. His answer was to move upstream into architecture, change management, and business process work with VPs and C suite sponsors. His first question is always why. Why this site, why this machine, why this platform, and what outcome is attached to it.With no clear scope of work, Abelara declines to bid or sells the consulting engagement that produces one. When scope is fuzzy but workable he prices it all in and writes explicit exclusions and assumptions up front. His test before a proposal is one question: what does done look like. A striking number of buyers cannot answer it. He also corrects an instinct: a $200 sensor may beat a $30,000 camera technically and still be the wrong call, because the expensive option is a known quantity and carries less risk.Scaling gets treated as line balancing applied to a company. Find the bottleneck, find the gap in skills or availability, and staff it. Each hire moves the constraint somewhere new, and the hardest part is emotional: letting go of work you enjoy and are good at. On AI, Dylan predicts integration goes back to being integration. A generation of integrators drifted into custom coding, with companies of 400 and 500 people building MES and SCADA stacks from scratch, and he expects code generation to strip that work away. Writing a tool that pulls PLC data to the cloud is easy. Running it reliably and securely 24/7 for a year is not.About Dylan DuFresneDylan DuFresne is co founder and lead architect at Abelara, a manufacturing transformation firm that works with plants as coach, consultant, and integrator. He spent more than a decade inside systems integrators covering robotics, PLCs, SCADA, HMI, recipe management, and ERP integration before starting Abelara with co founder Glenn. He also wrote The Phantom Pallet, a manufacturing fable about data, trust, and transformation.https://abelara.comTimestamps0:00 Introduction4:30 What a systems integrator actually is9:00 Why Dylan and Glenn started Abelara14:00 Following the customer or picking platforms first20:00 Consulting versus integration work25:00 Why integrators get brought in too late32:00 The $30,000 camera and business trade offs36:30 Scope of work and what does done look like43:20 Handing projects to the team and subcontractors52:10 First hires, bottlenecks, and forecasting57:40 AI and the future of systems integration1:05:40 Predictions, career advice, and booksReferencesThe Phantom Pallet by Dylan DuFresne: https://www.amazon.com/Phantom-Pallet-Manufacturing-Fable-Transformation-ebook/dp/B0GGYCK5PRImpro: Improvisation and the Theatre by Keith Johnstone: https://www.amazon.com/Impro-Improvisation-Theatre-Keith-Johnstone/dp/041346430XAbout Your HostsVladimir Romanov is a co-host of The Manufacturing Hub Podcast and the founder of Joltek, an independent manufacturing and industrial automation consulting firm specializing in modernization strategy, digital transformation, and workforce development. Joltek works with manufacturers and investors to de-risk modernization and build the internal capability to sustain results.Connect with Vlad: https://www.linkedin.com/in/vladromanov/Want to go deeper? Vlad and the team at Joltek have covered related topics here:System Integrators: https://www.joltek.com/blog/system-integratorsConsulting, Upskilling, and Systems Integration: https://www.joltek.com/blog/humble-beginnings-consulting-upskilling-systems-integrationDave Griffith is a co-host of The Manufacturing Hub Podcast and founder of Capelin Solutions, an industrial automation firm helping manufacturers adopt smart manufacturing technology. He brings 15 years of experience in industrial automation and digital transformation.Connect with Dave: https://www.linkedin.com/in/davegriffith23/Subscribe to Manufacturing Hub: https://www.manufacturinghub.liveLinkedIn: https://www.linkedin.com/company/manufacturing-hub-networkYouTube: https://www.youtube.com/@ManufacturingHub
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  Ep. 269 - Siemens Xcelerator Marketplace: Digital Transformation SMB Manufacturers Can Afford 12.08.2026 1t 13min

  Siemens says a small manufacturer can start production optimization for $2,000 a year. Martin Valkysers and Flemming Kongsberg explain what that buys you.Most digital transformation advice assumes a budget and an engineering bench most plants do not have. Flemming Kongsberg, who runs the SMB focus inside the Siemens CTO organization, discards the usual revenue and headcount definitions: an SMB is any manufacturer without the skills to absorb a complex digital change, and that includes some very large companies. He describes one customer running 900 devices across 17 locations where 90 percent of the machines are 30 years or older with zero connectivity. Siemens research also found 40 percent of SMB customers have no IT department.Martin Valkysers frames Siemens Xcelerator as the open digital business platform tying hardware, software, data, and services together, with more than 600 partners today. The SMB starter package is where that becomes concrete. Instead of asking a plant with no IT staff to assemble something from hundreds of apps, Siemens curated roughly 10 to 12 into one bundle covering device connectivity, Performance Insight dashboards for OEE and quality, and a slice of Mendix. A partner installed it in a lab in 24 minutes on an ordinary Windows machine, against the roughly 60 hours a traditional Industrial Edge deployment takes. It is $2,000 per year for three machines with the first three months free, and PROFINET, Ethernet/IP, and the standard protocols are supported, so competitor PLCs connect too.The most useful argument here has nothing to do with buying anything. Flemming makes the case that reaching for AI before you own your data is a losing move, because a model built on information everyone else can reach produces no strategic advantage. You also do not need AI to build a Pareto chart of where your quality losses sit. Martin adds the discipline that gets skipped most: be clear about the problem before you pick the tool.About the GuestsMartin Valkysers is Head of US Market Launch and Growth for Siemens Xcelerator, Siemens' open digital business platform spanning industrial, building, grid, and manufacturing sectors. He has been with Siemens roughly 12 years, previously leading a US operations consulting team focused on lean manufacturing.Flemming Kongsberg leads Global Technology Partners at Siemens Digital Industries Software and runs the company's SMB focus in the US. Before Siemens he spent nearly eight years at Amazon Web Services building partner infrastructure and strategic ISV alliances.Timestamps0:00 Introduction2:20 Martin Valkysers on his path to Xcelerator4:20 Flemming Kongsberg from AWS to Siemens SMB7:10 Four challenges facing manufacturers13:40 Why data comes before AI18:00 What Siemens Xcelerator actually is22:30 Partner ecosystem: build, service, sell31:40 Inside the SMB starter package35:50 What the package costs38:20 A 24 minute install and non Siemens PLCs45:50 Redefining what counts as an SMB53:50 The future of industrial marketplacesReferencesGetting Started with Production Optimization: https://www.siemens.com/en-us/products/industrial-edge/production-optimization-get-started/Operational Efficiency Pack for Small Manufacturers: https://news.siemens.com/en-us/siemens-small-manufacturers-operational-efficiency-pack/This episode is sponsored bySiemens is a global technology company operating across industrial automation, digital software, smart infrastructure, and mobility. Siemens Xcelerator is its open digital business platform and marketplace.https://www.siemens.comAbout Your HostsVladimir Romanov is a co-host of The Manufacturing Hub Podcast and the founder of Joltek, an independent manufacturing and industrial automation consulting firm specializing in modernization strategy, digital transformation, and workforce development. Joltek works with manufacturers and investors to de-risk modernization and build the internal capability to sustain results.Connect with Vlad: https://www.linkedin.com/in/vladromanov/Want to go deeper? Vlad and the team at Joltek have covered related topics here:Digital Transformation in Manufacturing: https://www.joltek.com/blog/digital-transformation-in-manufacturingEdge Computing and the AI Value of Manufacturing Data: https://www.joltek.com/blog/edge-computing-ai-value-manufacturing-dataDave Griffith is a co-host of The Manufacturing Hub Podcast and founder of Capelin Solutions, an industrial automation firm helping manufacturers adopt smart manufacturing technology. He brings 15 years of experience in industrial automation and digital transformation.Connect with Dave: https://www.linkedin.com/in/davegriffith23/Subscribe to Manufacturing Hub: https://www.manufacturinghub.liveLinkedIn: https://www.linkedin.com/company/manufacturing-hub-networkYouTube: https://www.youtube.com/@ManufacturingHub
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  Ep. 268 - David Nichols of Loupe on Claude Code, AI Retrofits, and the End of the SI Moat 06.08.2026 1t 8min

  David Nichols of Loupe explains what actually changed in automation engineering this year, and why control retrofits just got far cheaper.Nearly twenty years into building high performance controls, David Nichols is blunt about what AI did to his business: what used to take six weeks now takes two, and his team ships roughly five times more software per sprint. An engineer dropped the raw documentation from a failing robotic cell into a folder, asked Claude for a state diagram, and got a reverse engineered flow chart in thirty minutes that beat anything the customer had. The error recovery gap causing the downtime was visible right there in the chart. A SASE member handed a model a hundred page ethernet specification and got working code for every function, plus tests, on the first try. That was a six week project. It took a day.The implication is the sharpest part of the conversation. Software rewrites used to be the dumbest thing an engineer could propose, because software was expensive and full of unknowns. That logic has inverted. If a rewrite takes a week and produces better documentation, better tests, and better coverage, then brownfield modernization stops being a risk calculation. His words: open season on old controllers. For an industry sitting on Windows 7 machines and undocumented cells one PC failure away from stopping a line, that is a different economic picture entirely.Vlad walks David through the full project lifecycle, and the answers stay practical. Discovery becomes a context gathering exercise where interview transcripts and a drawer full of legacy PDFs turn into control diagrams and proposals in days. Development becomes worth treating as a real software engineering project, because source control, digital twins, and automated testing are exactly what these models are fluent in. David is equally direct about platforms: the bottleneck in automation was never technical, it is cultural. His analogy is a shop that insists on carburetors because that is what the technicians know. The close tackles the chat's harder questions, including what is left of a software moat once building software is trivial. His book pick is Richard Rhodes and The Making of the Atomic Bomb.About David NicholsDavid Nichols is co-founder of Loupe, a West Coast automation engineering and systems integration company he started in 2007. Loupe does high performance controls work across aerospace, semiconductors, and metal cutting, built largely on the B&R Industrial Automation platform. He also founded SASE, the Society of Automation Software Engineers, a free community of roughly two thousand engineers. This is his fourth appearance on Manufacturing Hub, following episodes 29, 53, and 127.https://loupe.teamTimestamps0:00 Introduction2:45 Loupe, 20 years of controls, and the SASE community8:40 Carburetors in industrial automation: culture, not technology11:20 The ChatGPT moment versus the Claude Code moment20:20 Inside an integrator: six week sprints become two21:30 Reverse engineering a robotic cell in 30 minutes26:10 A 100 page ethernet spec turned into working code in a day27:50 Does this change who gets to be a builder40:40 AI across the project lifecycle from discovery to handoff49:00 How to actually get started, and what to prompt53:20 If software is no longer a moat, what is57:50 Predict the future, career advice, and the book pickReferencesSASE: https://sase.spaceClaude: https://claude.aiClaude Code: https://claude.com/claude-codeSendCutSend: https://sendcutsend.comAcquired Podcast: https://www.acquired.fmAbout Your HostsVladimir Romanov is a co-host of The Manufacturing Hub Podcast and the founder of Joltek, an independent manufacturing and industrial automation consulting firm specializing in modernization strategy, digital transformation, and workforce development. Joltek works with manufacturers and investors to de-risk modernization and build the internal capability to sustain results.Connect with Vlad: https://www.linkedin.com/in/vladromanov/Want to go deeper? Vlad and the team at Joltek have covered related topics here:Control System Modernization Strategy: https://www.joltek.com/blog/control-system-modernization-strategyEdge Computing and AI Value from Manufacturing Data: https://www.joltek.com/blog/edge-computing-ai-value-manufacturing-dataDave Griffith is a co-host of The Manufacturing Hub Podcast and founder of Capelin Solutions, an industrial automation firm helping manufacturers adopt smart manufacturing technology. He brings 15 years of experience in industrial automation and digital transformation.Connect with Dave: https://www.linkedin.com/in/davegriffith23/Subscribe to Manufacturing Hub: https://www.manufacturinghub.liveLinkedIn: https://www.linkedin.com/company/manufacturing-hub-networkYouTube: https://www.youtube.com/@ManufacturingHub
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  Ep. 267 - Ujjwal Kumar of Siemens on Deglobalization, Reshoring, and Adaptive Manufacturing 30.07.2026 1t 2min

  Deglobalization is rewriting where factories get built, and Ujjwal Kumar of Siemens explains what has to change on the plant floor before reshoring actually works.For thirty years the manufacturing playbook was labor arbitrage. Move high volume, low mix production to wherever disciplined labor was cheapest, then ship it back. Ujjwal Kumar, President of Automation for Siemens Digital Industries in the Americas, argues that model has quietly stopped making sense. Demand has fragmented into high mix, lower volume, regionally specific production, and the factories in Suzhou running on robots and autonomous systems no longer carry a cost advantage over the same operation in Chicago. When the labor content collapses, the business case for distance collapses with it. That single shift explains more about the current reshoring wave than any tariff headline.The trigger was not one event. Supply chain disruption after COVID proved that geographic proximity to supply was a profitability advantage, not a nice to have. Then came the political shock: vaccine access turned out to be governed by country of citizenship rather than global distribution, and leaders across every region started sorting industries into a folder marked critical. That folder now holds semiconductors, steel, power generation, defense, space, and life sciences. Ujjwal walks through where the money is actually landing right now, including AI data centers in remote locations that demand autonomous and remote operations, power generation across fossil, renewable, nuclear, and hydro, and a level of greenfield life sciences investment in the United States he has not seen in decades. The life sciences point is the sharpest one in the episode. Drug manufacturing left as mass produced batch operations and is returning as cell and gene therapy, personalized medicine, and precision biologics, which means lot sizes of one and R&D sitting physically next to production. The design it here, build it there model taught in business schools simply does not survive that.About Ujjwal KumarUjjwal Kumar is President of Automation for Siemens Digital Industries in the Americas. A mechanical engineer by training with an MBA from the Michigan Ross School of Business, he began his career at General Motors in Detroit and went on to spend ten years at GE and seven years at Honeywell Process Solutions before leading Teradyne Robotics, one of the largest physical AI based robotics platforms. He oversees the Siemens automation portfolio spanning discrete, process, and intralogistics automation, and he continues to mentor MBA students at Michigan Ross.Timestamps0:00 Introduction2:00 Career path from General Motors to Siemens6:10 What deglobalization means for manufacturing9:00 COVID, vaccine quotas, and the reshoring trigger13:05 Labor arbitrage versus automation arbitrage15:50 Attracting the next generation of factory workers19:35 Why semiconductor reshoring will take years23:00 Tribal knowledge and the documentation problem26:00 Where the investment is going right now32:30 Adaptive manufacturing and the AI hype question35:30 Platforms, ecosystems, and Siemens Xcelerator43:20 Careers, AI, and advice for engineersReferencesSiemens Xcelerator Marketplace: https://xcelerator.siemens.com/global/en.htmlThis episode is sponsored bySiemens is a technology company focused on industry, infrastructure, transport, and healthcare, and it supplies industrial automation hardware and industrial software to manufacturers worldwide. Its Digital Industries business covers discrete automation, process automation, intralogistics, and the Siemens Xcelerator platform.https://www.siemens.comAbout Your HostsVladimir Romanov is a co-host of The Manufacturing Hub Podcast and the founder of Joltek, an independent manufacturing and industrial automation consulting firm specializing in modernization strategy, digital transformation, and workforce development. Joltek works with manufacturers and investors to de-risk modernization and build the internal capability to sustain results.Connect with Vlad: https://www.linkedin.com/in/vladromanov/Want to go deeper? Vlad and the team at Joltek have covered related topics here:Understanding Supply Chains: https://www.joltek.com/blog/understanding-supply-chainsManufacturing Challenges with New Machinery and Plants: https://www.joltek.com/blog/manufacturing-challenges-new-machinery-plantDave Griffith is a co-host of The Manufacturing Hub Podcast and founder of Capelin Solutions, an industrial automation firm helping manufacturers adopt smart manufacturing technology. He brings 15 years of experience in industrial automation and digital transformation.Connect with Dave: https://www.linkedin.com/in/davegriffith23/Subscribe to Manufacturing Hub: https://www.manufacturinghub.liveLinkedIn: https://www.linkedin.com/company/manufacturing-hub-networkYouTube: https://www.youtube.com/@ManufacturingHub
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  Ep. 266 - Automate 2026 Reality Check: AI, Virtual PLCs, Ignition, and Plant Modernization 18.07.2026 1t 27min

  After several weeks away from the podcast, Dave Griffith and Vladimir Romanov return to Manufacturing Hub to unpack their experiences at Automate 2026 and discuss what the event revealed about the current state of industrial automation.Automate showcased an enormous range of robotics, industrial AI, machine vision, software, cloud connectivity, and emerging automation technology. However, some of the most revealing conversations were not about futuristic factories. They were about PLC 5 migrations, aging SLC systems, obsolete PanelView terminals, industrial networks, basic data collection, and how platforms such as Ignition actually connect to plant floor equipment.Vlad shares what he learned from demonstrating a complete packaging line environment built around a CompactLogix PLC, an industrial computer, Ignition, and production performance data. The demonstration was designed to show how manufacturers can use OEE, downtime information, and machine states to identify production bottlenecks and determine where capital investment could deliver the greatest return. Instead, many attendees wanted to understand the underlying architecture, where Ignition runs, how it connects to PLCs, what protocols are required, and whether it can replace traditional HMI and SCADA platforms.Dave discusses his experience inside the Ignition ecosystem booth, the FactoryStack cloud demonstration, the advantages of MQTT in a difficult trade show network environment, and his Automate panel on software defined automation and the factory of the future. He also introduces Elephant, an industrial log analysis and contextualization tool being developed to help users identify meaningful patterns across Ignition gateways, reduce system noise, compare facilities, and diagnose intermittent problems.The conversation then moves across the industrial automation stack. Dave and Vlad examine virtual PLCs from Siemens, Phoenix Contact, and other vendors, including where software based control may provide value and where it may add unnecessary organizational complexity. They discuss AI generated PLC code, the limitations of translating functional specifications into reliable control applications, and why tools that produce 80 or 90 percent of an automation solution still require experienced engineers to validate the final result.They also explore AI assisted HMI and SCADA development, Ignition 8.3, MCP servers, high performance HMI design, and the risks of providing AI agents with uncontrolled access to production systems. At the MES layer, they question whether manufacturers should build custom applications through vibe coding or focus instead on creating clean, contextualized, well governed data that can support many future applications.The central conclusion is that AI tools, virtual controllers, cloud platforms, and dynamically generated applications will continue to improve. However, manufacturers still need reliable controls, secure networks, maintainable architectures, experienced people, and ownership of their operational data. The companies that establish those foundations today will have the greatest freedom to adopt whatever technologies emerge next.Dave and Vlad also preview the 2026 Ignition Community Conference in Sacramento, upcoming Manufacturing Hub conversations, new demonstrations, and several projects the community will see throughout the remainder of the year.Join us for a detailed and candid discussion about Automate 2026, Ignition, industrial AI, virtual PLCs, HMI and SCADA development, MES, MQTT, data architecture, and what manufacturers should prioritize next.
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  Ep. 265 - Automate 2026 Survival Guide: Booths, Networking, and a Production Line Demo #scada #mes 18.06.2026 35min

  Automate 2026 lands in Chicago next week, and Dave and Vlad break down how to work the show floor, where to network, and what to expect from their live booth demos.Automate is the largest automation trade show in North America, and a four day event rewards preparation. Dave and Vlad share tactics refined over five years of attending together. The floor opens at 10:00 AM on Monday, and registration lines have swung from a five minute wait to nearly two hours, so arriving early matters. Monday morning and Thursday are the quietest days to reach specific vendors, while Tuesday and Wednesday draw the heaviest crowds. The hosts also favor the official show app over a paper map for finding booths and session rooms across multiple halls.The real value of a show like Automate often lives in the networking. Dave points to the A3 networking event on Monday, a ticket of roughly 45 dollars, and the Manufacturing Champions happy hour on Tuesday organized by Chris Luckey and Jake Hall. Vlad's advice is structural: build a checklist before you arrive. He researches each company, finds the booth number, and tracks every connection in a spreadsheet so the week becomes a series of deliberate meetings instead of aimless wandering. For anyone with ten or more booths on their list, setting up meetings in advance is the highest leverage move you can make.The centerpiece of the conversation is the live demo Vlad built for the Teguar booth. It pairs a Rockwell CompactLogix PLC with an Ignition gateway running on a Teguar industrial PC, and it simulates a food and beverage packaging line with five assets: filler, capper, labeler, case packer, and palletizer. The line overview screen shows real machine states including faulted, starved, backed up, and running, and the whole point is to make the bottleneck visible. When the case packer needs six bottles from the labeler but the labeler cannot keep pace, you watch the downstream asset flip between starved and running in real time. It is a practical illustration of why line balancing and constraint analysis drive real ROI on a production floor.Under the hood the stack is modern. The Teguar IPC runs Ubuntu with Portainer managing containers for Ignition 8.3, Ignition 8.1, and a MariaDB database for alarm history. Ignition 8.3 ships new drivers for Rockwell, Siemens, Mitsubishi, and Omron controllers along with OPC and MQTT, and each asset carries ten randomized faults written in both Ignition and PLC logic. Vlad built it for everyone from engineers to the decision makers running SCADA and MES projects. Dave and Vlad will also shoot content at the Siemens booth on Tuesday and the Horner Automation booth on Wednesday, and Dave is moderating a Wednesday session on software defined automation and the factory of the future.Timestamps0:00 Welcome and Automate 2026 preview1:50 First timer tips and arriving early for registration3:10 Networking events worth attending: A3 and Manufacturing Champions4:40 Building a trade show checklist to maximize your time7:00 Manufacturing Hub at the Siemens and Horner booths9:50 Vlad's live production line demo at the Teguar booth15:40 The line overview screen and five packaging assets17:30 Fault handling and finding the bottleneck20:10 Inside the stack: Ubuntu, Portainer, Ignition, MariaDB23:50 Random fault simulation and PLC driver options27:00 Who should come see the demo29:40 Vendors Vlad is tracking and closing thoughtsReferencesAutomate 2026: https://www.automate.orgIgnition by Inductive Automation: https://inductiveautomation.comHorner Automation: https://hornerautomation.comAbout Your HostsVladimir Romanov is a co-host of The Manufacturing Hub Podcast and the founder of Joltek, an independent manufacturing and industrial automation consulting firm specializing in modernization strategy, digital transformation, and workforce development. Joltek works with manufacturers and investors to de-risk modernization and build the internal capability to sustain results.Connect with Vlad: https://www.linkedin.com/in/vladromanov/Want to go deeper? Vlad and the team at Joltek have covered related topics here:Connecting an Allen Bradley PLC to Ignition: https://www.joltek.com/blog/connecting-allen-bradley-plc-ignitionManufacturing Line Speed Optimization: https://www.joltek.com/case-study/manufacturing-line-speed-optimizationDave Griffith is a co-host of The Manufacturing Hub Podcast and founder of Capelin Solutions, an industrial automation firm helping manufacturers adopt smart manufacturing technology. He brings 15 years of experience in industrial automation and digital transformation.Connect with Dave: https://www.linkedin.com/in/davegriffith23/Subscribe to Manufacturing Hub: https://www.manufacturinghub.liveLinkedIn: https://www.linkedin.com/company/manufacturing-hub-networkYouTube: https://www.youtube.com/@ManufacturingHub
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  Ep. 264 - Why AI Loves Automation: Siemens on Digital Twins, Guardrails, and Orchestration 11.06.2026 1t 4min

  AI can finally write back to the plant floor, but only if you can trust it. Chris Stevens and Annemarie Breu of Siemens explain how orchestration makes that safe.Industrial AI has reached a turning point. Manufacturers can already collect data, contextualize it, and surface insights, but the hardest step has always been turning insight into action on real control equipment. Chris Stevens and Annemarie Breu of Siemens explain how an orchestration layer finally closes that loop. Annemarie frames the tension clearly. Automation depends on determinism, while large language models are probabilistic by design, so the goal is to bring that discipline into AI and validate any suggestion before it changes a set point.Most executive conversations start with return on investment, and two forces are making the case easier to prove. The workforce shortage has stretched the expected payback window from 18 months toward 36 months, and when a line cannot run for lack of people every idle minute costs thousands of dollars. The other driver is overall equipment effectiveness, since most plants run near 70 percent OEE and even a fraction of a percent of gain can justify a project. Energy is a standout case too. A BorgWarner sustainability effort used a digital twin to flatten demand peaks and reportedly paid for itself in under six months, even as data center growth pushes electricity demand higher through 2040.On trust and safety, Annemarie borrows a principle from industrial safety. Just as fail safe IO modules rely on two channel evaluation, every AI suggestion is validated against a state machine, a workflow, or a physics based digital twin before the orchestration layer passes it to a controller. With virtual commissioning and soft PLCs a change can be tested virtually, approved by a human in the loop, and only then written to control, an approach PepsiCo and NVIDIA echoed at CES when they called the digital twin a must have. Making AI real, the pair argue, comes down to discipline, clear scope, acceptance criteria, and focused 90 day challenges, plus the change management and user experience that drive adoption. Their favorite quick win is preventive maintenance driven by machine data, which both BorgWarner and Maersk tied to millions in savings.About Chris StevensChris Stevens is President of US Automation at Siemens, where he leads a roughly one billion dollar business spanning software, services, and hardware. He brings more than 25 years across Siemens Digital Industries, starting in the field selling assembly and test equipment, moving into the software and digital twin world, and returning to automation to bring the hardware and software sides of the business together.About Annemarie BreuAnnemarie Breu is a senior technology leader at Siemens Digital Industries focused on automation software deployment and customer technology partnerships in the US. She began at Siemens about a decade ago as a systems engineer in the San Francisco Bay Area, working with consumer electronics manufacturers on virtual commissioning and digital twins. Her work today centers on bringing the determinism and reliability of automation into industrial AI.Timestamps0:00 Introduction and Automate 2026 preview2:50 Meet Chris Stevens and Annemarie Breu9:30 The first AI question is always ROI14:00 Workforce gaps and OEE drive the business case19:30 Energy management and the data center demand surge23:20 Data, sensors, and contextualization requirements28:00 Guardrails, hallucinations, and two channel validation32:40 The digital twin and the human in the loop37:40 How partners and integrators move up the stack45:30 What it takes to make AI real on the floor55:50 Preventive maintenance as a quick win59:40 Predictions, career advice, and book picksAbout Your HostsVladimir Romanov is a co-host of The Manufacturing Hub Podcast and the founder of Joltek, an independent manufacturing and industrial automation consulting firm specializing in modernization strategy, digital transformation, and workforce development. Joltek works with manufacturers and investors to de-risk modernization and build the internal capability to sustain results.Connect with Vlad: https://www.linkedin.com/in/vladromanov/Want to go deeper? Vlad and the team at Joltek have covered related topics here:Edge Computing and the Value of AI in Manufacturing Data: https://www.joltek.com/blog/edge-computing-ai-value-manufacturing-dataIT and OT Architecture Integration: https://www.joltek.com/services/service-details-it-ot-architecture-integrationDave Griffith is a co-host of The Manufacturing Hub Podcast and founder of Capelin Solutions, an industrial automation firm helping manufacturers adopt smart manufacturing technology. He brings 15 years of experience in industrial automation and digital transformation.Connect with Dave: https://www.linkedin.com/in/davegriffith23/Subscribe to Manufacturing Hub: https://www.manufacturinghub.liveLinkedIn: https://www.linkedin.com/company/manufacturing-hub-networkYouTube: https://www.youtube.com/@ManufacturingHub
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  Ep. 263 - Why Industrial Protocols Win on Business Not Technical Merit, with Horner Automation 04.06.2026 1t 3min

  Industrial network protocols decide whether a machine talks or stays silent. Chuck from Horner Automation breaks down how they win, fade, and converge.Chuck has spent 36 years at Horner Automation and lived through what the industry once called the fieldbus wars. Before Horner became known for its all in one controllers, it spent a decade building specialty IO modules for GE Fanuc during the era of DeviceNet, SDS, InterBus S, PROFIBUS, and CANopen. His core argument is that most of those early protocols were technically fine. The ones that became standards won on the commercial weight of the companies backing them, not on superior specifications, with EtherCAT a rare exception that succeeded largely on technical merit.Trust is the recurring theme. Industry adopts slowly, and for years Ethernet was dismissed as too unreliable and not deterministic enough for control until Ethernet/IP, PROFINET, and Modbus TCP proved themselves. Today the market has settled around a big four set of protocols, and Chuck does not expect it to narrow further. For high speed motion he points to EtherCAT and PROFINET IRT as the implementations he most respects, since both step away from standard Ethernet at the device level to reach submillisecond timing.The episode is also a reality check on building your own hardware. Chuck and Dave describe how custom development routinely costs teams hundreds of thousands to millions of dollars, and how the real trap is obsolescence and maintenance rather than the first build. On the product side, the standout is FPD-Link, a serialization technology borrowed from automotive that carries video, touch, and power over one coaxial cable. Working with Safe Fleet, a maker of ambulances and fire trucks, Horner now mounts rugged displays up to seven meters from the PLC while still programming everything as one device.Looking ahead, Chuck argues that every PLC should now be treated as a data device first, because digitizing the process is the prerequisite for doing anything useful with AI. He also flags cybersecurity as the next burden for application engineers, with new mandates forcing both manufacturers and integrators to implement protections that were once optional. At Automate, Horner is showing HMI Connect and a 300 dollar CPU 151 that packs 18 IO points, wireless connectivity, and edge capability into a micro PLC.About Chuck and Horner AutomationChuck is a technical brand ambassador at Horner Automation, where he has spent 36 years across applications, product management, and education. An electrical engineer who started in the automotive industry, he now produces in depth tutorials on industrial protocols for the Horner APG YouTube channel. Horner Automation is a privately held controls manufacturer best known for its all in one PLC and HMI controllers, edge ready PLCs, and rugged hardware for industrial and mobile applications.Timestamps0:00 Introduction2:20 Chuck's Background and 36 Years at Horner Automation9:20 End User Engineer vs OEM Manufacturer Perspective13:20 New at Automate: HMI Connect and the CPU 151 Edge PLC21:30 The Fieldbus Wars and the History of Industrial Protocols24:20 What It Takes to Implement a Protocol Stack29:30 Why Protocols Win: Commercial Force vs Technical Merit32:40 Will Industrial Protocols Ever Converge?40:30 High Speed Motion: EtherCAT, PROFINET IRT, and Ethernet/IP44:40 FPD-Link: Rugged Remote HMI for Ambulances and Fire Trucks55:00 PLCs as Data Devices and the Push Toward AI1:02:40 Cybersecurity Mandates Coming for Application EngineersReferencesHorner Automation: https://www.hornerautomation.comAbout Your HostsVladimir Romanov is a co-host of The Manufacturing Hub Podcast and the founder of Joltek, an independent manufacturing and industrial automation consulting firm specializing in modernization strategy, digital transformation, and workforce development. Joltek works with manufacturers and investors to de-risk modernization and build the internal capability to sustain results.Connect with Vlad: https://www.linkedin.com/in/vladromanov/Want to go deeper? Vlad and the team at Joltek have covered related topics here:Understanding Plant Networks: https://www.joltek.com/blog/understanding-plant-networks-how-industrial-connectivity-evolvedIndustrial Ethernet Reliability: https://www.joltek.com/blog/industrial-ethernet-reliabilityDave Griffith is a co-host of The Manufacturing Hub Podcast and founder of Capelin Solutions, an industrial automation firm helping manufacturers adopt smart manufacturing technology. He brings 15 years of experience in industrial automation and digital transformation.Connect with Dave: https://www.linkedin.com/in/davegriffith23/Subscribe to Manufacturing Hub: https://www.manufacturinghub.liveLinkedIn: https://www.linkedin.com/company/manufacturing-hub-networkYouTube: https://www.youtube.com/@ManufacturingHub
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  Ep. 262 - The Human Side of Manufacturing Change: Incentives, Pain Points, and Operator Buy In 28.05.2026 1t 5min

  Change management is the reason most manufacturing improvement projects quietly stall, even when the technical work is sound and the tools are right.Vlad Romanov and Dave Griffith unpack their own change management war stories from across two decades in industrial automation. Vlad frames change management as understanding risk to the business and to every stakeholder, then putting the process in place that lets the organization absorb that risk. Technical feasibility is the easy half of any project. Getting humans to consistently work the new way is the half that wins or loses the budget.Vlad joined Procter & Gamble at a site rated four on P&G's Integrated Work Systems maturity scale, the highest in North America at the time. Every loss event triggered a structured root cause analysis cascade. Operator, mechanic, operations engineer, and only then the engineering department. He later moved to Kraft Heinz, which had purchased the same IWS toolkit from P&G. The tools were on the shelf. The site rating was effectively zero. He had spent his early career learning to use the tools without having to deploy them, and that gap is where most transformation programs die.Dave's lens is more political. Change management starts with one question engineers rarely ask. What is in it for the person you are asking to change? He tells the Joe story, a lead operator with more than 35 years on the floor who interrupted a connected workforce rollout meeting to point out that his team had cycled through every methodology fad of the last two decades. None had stuck. Dave's team asked what hurt the most. Joe kept training new operators who left for a dollar an hour more down the street. The fix was QR codes on equipment linked to procedures Joe recorded once. Joe went from skeptic to evangelist in one session. Find the operator with the deepest tenure, solve their pain, and let them carry the change.The episode is also honest about what well intentioned incentives do when they miss the mark. Vlad walks through an RCA rollout where management offered a fifty dollar gift card to whoever submitted the most reports each week. The team got a stack of paper. None of it shortened downtime. When real process change goes through a plant, throughput typically drops twenty to thirty percent for weeks or months. That cost has to be visible to leadership before the project starts.Two practical heuristics close the episode. As a systems integrator deploying MES and SCADA across food and beverage plants, Vlad could often predict success within the first demo by how the room reacted. Continuous improvement teams leaned in. Whiteboard sites pushed back. Dave reinforces that change has to start at the top. If the executive sponsor blows off steering meetings, the floor reads that signal. Change management is a habit, not a project, and habits are built small. Pick one workflow, prove it works, and let the next one earn its slot.Timestamps0:00 Introduction and Automate trade show preview1:30 Booth commitments: Siemens, Horner, and Tigoor6:00 Dave's Automate session and 4IR booth duty8:10 Predictions for Automate: physical AI, cobots, and the AI conversation13:10 Defining change management in manufacturing22:30 From P&G IWS to Kraft Heinz: tools versus deployment maturity28:30 What is in it for the person you are asking to change35:30 The RCA cascade at P&G compared to no process elsewhere42:30 The fifty dollar gift card incentive that backfired46:00 The Joe story: QR codes solving real operator pain58:30 Reading change management success in the first meeting1:07:00 Start small: the closing takeawayAbout Your HostsVladimir Romanov is a co-host of The Manufacturing Hub Podcast and the founder of Joltek, an independent manufacturing and industrial automation consulting firm specializing in modernization strategy, digital transformation, and workforce development. Joltek works with manufacturers and investors to de-risk modernization and build the internal capability to sustain results.Connect with Vlad: https://www.linkedin.com/in/vladromanov/Want to go deeper? Vlad and the team at Joltek have covered related topics here:Lean Six Sigma: https://www.joltek.com/blog/lean-six-sigma7 Different Root Cause Analysis Techniques in Manufacturing: https://www.joltek.com/blog/7-different-root-cause-analysis-techniques-manufacturingDave Griffith is a co-host of The Manufacturing Hub Podcast and founder of Capelin Solutions, an industrial automation firm helping manufacturers adopt smart manufacturing technology. He brings 15 years of experience in industrial automation and digital transformation.Connect with Dave: https://www.linkedin.com/in/davegriffith23/Subscribe to Manufacturing Hub: https://www.manufacturinghub.liveLinkedIn: https://www.linkedin.com/company/manufacturing-hub-networkYouTube: https://www.youtube.com/@ManufacturingHub
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  Ep. 261 - Change Management in Manufacturing: Operators, Tribal Knowledge, and the Industrial Elder 21.05.2026 1t 2min

  Change management in manufacturing breaks down at the people layer, not the technology layer. This episode explains how engineering leaders actually drive adoption.Ronald Sherrod is a Staff Automation Engineer at Regeneron deploying a global event based architecture and Unified Namespace rollout across pharmaceutical operations. Ron, Vlad Romanov, and Dave Griffith dig into the parts of change management that rarely make it onto vendor decks. Subscribe to Manufacturing Hub for weekly conversations with industrial automation practitioners.Want to go deeper? Vlad and the team at Joltek have covered related topics here:Digital Transformation in Manufacturing: https://www.joltek.com/blog/digital-transformation-in-manufacturingMastering the Unified Namespace for Manufacturing: https://www.joltek.com/blog/mastering-unified-namespace-uns-a-guide-to-data-driven-manufacturing-transformationRon makes a point that is rarely stated this directly. The organization implementing the change is the one responsible for it. OEMs and system integrators deliver the box. Consultants help interpret it. Auditors do not call the machine builder when something goes wrong on the floor of a regulated pharmaceutical plant. They walk into the manufacturer and ask whether the audit trails hold up, whether the predicate rule was met, and whether the product is safe for patients. That responsibility cannot be outsourced, even when the technical work is.That framing changes how engineering managers should think about RFP scope. If the scope is loose, the integrator absorbs the risk and prices accordingly. If the scope is rigorous, bids come back tight and comparable. Negotiating power changes with the size of the buyer. A large pharmaceutical company can dictate hypercare windows, on site commissioning support, and structured training. A small to mid sized manufacturer often cannot, and the result is the metaphorical Ferrari on the plant floor that only ever gets used for grocery runs. Capital was deployed. The technology works. The operation never adopted it.The episode also goes deep on tribal knowledge and the industrial elder, the technical anchor who carries the institutional history of a unit or process and is often more valuable than the Excel file on a network drive. Senior operators know why a pipe was rerouted fifteen years ago and why a procedure looks irrational on paper but works perfectly in practice. With 59 percent of frontline skilled workers over 55 planning to retire within five years per the Schneider Electric 2024 workforce survey, capturing that knowledge is now a leadership priority, not an engineering task.On planning, Ron walks through how he runs user story workshops with operators, manufacturing leaders, engineers, and developers in the same room, producing a shared data contract that defines what information moves where, who needs it, and why. He cites a successful SCADA deployment that worked because the organization had inertia, operators had asked for the problem to be solved, and the team was closing a real gap rather than chasing a trend.Ronald Sherrod is a Staff Automation Engineer at Regeneron, a chemical engineer by training who moved from oil and gas into pharma and now works on event driven architecture, UNS, and robotics initiatives. Ron: https://www.linkedin.com/in/rdsherrod/Timestamps0:00 Welcome and Episode Intro1:50 Ron's Career: Oil and Gas to Pharma at Regeneron4:30 Defining Change Management and Its KPIs8:30 Change Management vs Operational Excellence11:50 Who Owns Change Management on Industrial Projects17:00 Negotiating Power: Large vs Small Manufacturers20:30 Why Capital Projects End Up Mothballed22:10 Tribal Knowledge and Learning From Operators26:00 Why Industrial Projects Fail29:00 The Industrial Elder and Passing Knowledge Through People31:30 AI Generated Documentation in Manufacturing35:50 Project Planning and the RFP Process47:50 A Successful SCADA Deployment and User Story Workshops54:30 Predictions, Career Advice, and Smart GlassesAbout Your HostsVladimir Romanov is a cohost of The Manufacturing Hub Podcast and the founder of Joltek, an independent manufacturing and industrial automation consulting firm specializing in modernization strategy, digital transformation, and workforce development.Connect with Vlad: https://www.linkedin.com/in/vladromanov/Dave Griffith is a cohost of The Manufacturing Hub Podcast and founder of Capelin Solutions, an industrial automation firm helping manufacturers adopt smart manufacturing technology.Connect with Dave: https://www.linkedin.com/in/davegriffith23/Subscribe to Manufacturing Hub: https://www.manufacturinghub.liveLinkedIn: https://www.linkedin.com/company/manufacturing-hub-networkYouTube: https://www.youtube.com/@ManufacturingHub
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  Ep. 260 - Why Ignition Is Winning: Colby Clegg and Carl Gould on SCADA, Open Access, & Industrial AI 14.05.2026 1t 10min

  Inductive 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 GouldColby 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.Inductive Automation: https://www.inductiveautomation.comTimestamps0:00 Introduction1:00 Meet Colby Clegg and Carl Gould2:00 The origins of Inductive Automation in 20038:00 Going to market and the Innovator's Dilemma10:30 Innovation without permission as company culture18:50 Ignition 8.0 and the leap to Perspective26:00 The five year journey to 8.338:00 The MCP server module and AI in Ignition45:30 AI in the control plane and guardrails52:30 Tiger Data and the technology ecosystem1:02:30 Career advice for the next generation1:06:40 What is ripe for innovationReferencesIgnition Community Conference: https://icc.inductiveautomation.comAbout Your HostsVladimir Romanov is a cohost of The Manufacturing Hub Podcast and the founder of Joltek, an independent manufacturing and industrial automation consulting firm specializing in modernization strategy, digital transformation, and workforce development. Joltek works with manufacturers and investors to reduce the risk of modernization and build the internal capability to sustain results.Connect with Vlad: https://www.linkedin.com/in/vladromanov/Want to go deeper? Vlad and the team at Joltek have covered related topics here:Colby Clegg on Ignition 8.3 and Industrial Automation: https://www.joltek.com/blog/industrial-automation-colby-clegg-ignition-8-3Connecting Allen Bradley PLCs to Ignition: https://www.joltek.com/blog/connecting-allen-bradley-plc-ignitionDave Griffith is a cohost of The Manufacturing Hub Podcast and founder of Capelin Solutions, an industrial automation firm helping manufacturers adopt smart manufacturing technology. He brings 15 years of experience in industrial automation and digital transformation.Connect with Dave: https://www.linkedin.com/in/davegriffith23/Subscribe to Manufacturing Hub: https://www.manufacturinghub.liveLinkedIn: https://www.linkedin.com/company/manufacturing-hub-networkYouTube: https://www.youtube.com/@ManufacturingHub
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  Ep. 259 - Logan Terry of LSI on Change Management: The Soft Side of SCADA, MES, & ERP Projects 07.05.2026 1t 8min

  Change 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 TerryLogan 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 integrations.LSI: https://www.logicalsysinc.com/Timestamps0:00 Introduction2:15 Logan's background and the LSI digital transformation practice7:25 Defining change management9:00 Why MES requires the most change management13:00 How young engineers stumble into change management24:30 Starting with decisions and workflows before technology35:00 Internal CI capability as a project gating factor43:30 OEE dashboard turned off six months after go live46:30 Behavioral psychology of how operators read numbers54:50 Modular MES replacing monolithic platforms58:00 Generative AI and continuous validation1:11:00 AI assisted prototyping shrinking design cyclesAbout Your HostsVladimir Romanov is a co-host of The Manufacturing Hub Podcast and the founder of Joltek, an independent manufacturing and industrial automation consulting firm specializing in modernization strategy, digital transformation, and workforce development. Joltek works with manufacturers and investors to de-risk modernization and build the internal capability to sustain results.Connect with Vlad: https://www.linkedin.com/in/vladimirromanov/Want to go deeper? Vlad and the team at Joltek have covered related topics here:Digital Transformation in Manufacturing: https://www.joltek.com/blog/digital-transformation-in-manufacturingManufacturing Execution Systems and Business Strategy: https://www.joltek.com/blog/manufacturing-execution-systems-business-strategyDave Griffith is a co-host of The Manufacturing Hub Podcast and founder of Capelin Solutions, an industrial automation firm helping manufacturers adopt smart manufacturing technology. He brings 15 years of experience in industrial automation and digital transformation.Connect with Dave: https://www.linkedin.com/in/davegriffith23/Subscribe to Manufacturing Hub: https://www.manufacturinghub.liveLinkedIn: https://www.linkedin.com/company/manufacturing-hub-networkYouTube: https://www.youtube.com/@ManufacturingHub
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  Ep. 258 - Hannover Messe Recap, the State of Industrial AI, and What Comes Next at Automate 2026 30.04.2026 1t 8min

  Industrial 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.Timestamps0:00 Introduction1:50 Hannover Messe scale, halls, and country delegations7:20 Booth diversity from startups to hyperscalers and the German military12:20 Why end users have stopped asking, do you have AI19:00 The 1% on the bleeding edge versus the rest of industry25:50 End users sending boilerplate PLC code through ChatGPT29:20 Data governance on the OT side32:50 AI inside systems integration workflows39:50 Workforce shifts: UPS buyouts, FAANG layoffs, and reskilling47:20 Hardware innovation, Moore's Law, and the industrial side59:50 SCADA, MES, ERP, and AI generated dashboards1:03:30 Upcoming shows: Automate 2026, ICC, and moreReferencesHannover Messe: https://www.hannover-messe.deAutomate 2026: https://www.automateshow.comIgnition Community Conference: https://icc.inductiveautomation.comRockwell Automation Fair: https://www.rockwellautomation.com/automationfairAbout Your HostsVladimir Romanov is a co-host of The Manufacturing Hub Podcast and the founder of Joltek, an independent manufacturing and industrial automation consulting firm specializing in modernization strategy, digital transformation, and workforce development. Joltek works with manufacturers and investors to de-risk modernization and build the internal capability to sustain results.Connect with Vlad: https://www.linkedin.com/in/vladimirromanov/Want to go deeper? Vlad and the team at Joltek have covered related topics here:Edge Computing, AI, and the Value of Manufacturing Data: https://www.joltek.com/blog/edge-computing-ai-value-manufacturing-dataSystems Integrators in Manufacturing: https://www.joltek.com/blog/system-integratorsDave Griffith is a co-host of The Manufacturing Hub Podcast and founder of Capelin Solutions, an industrial automation firm helping manufacturers adopt smart manufacturing technology. He brings 15 years of experience in industrial automation and digital transformation.Connect with Dave: https://www.linkedin.com/in/davegriffith23/
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  Ep. 256 - Why Machine Learning Still Outperforms LLMs for Manufacturing Process Control 09.04.2026 1t 9min

  Digital 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 VoraVirag 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.Timestamps0:00 Introduction1:20 Virag's background in chemical engineering and industrial software6:30 Moving up the ISA 95 stack from DCS to MES and applications9:00 How AI reinvents digital twin, golden batch, and SPC concepts12:20 What a data centric digital twin actually looks like21:40 Where digital twins deliver the most value in manufacturing27:00 Seasonality, segmentation, and model training strategies36:00 Data prerequisites for deploying industrial AI41:40 Flavors of AI in manufacturing: ML, LLMs, and agentic workflows50:40 Closed loop AI control at Hills Pet Nutrition53:10 Personal project: Family Graph using knowledge graphs56:20 Prediction: operators as human digital twinsReferencesTwin Thread: https://twinthread.comThis episode is sponsored byMaintainX is an AI powered maintenance and operations platform that helps technicians get the answers they need instantly so they can focus on getting assets back online. Learn more about how MaintainX supports frontline manufacturing teams.https://maintainx.comAbout Your HostsVladimir Romanov is a co-host of The Manufacturing Hub Podcast and the founder of Joltek, an independent manufacturing and industrial automation consulting firm specializing in modernization strategy, digital transformation, and workforce development. Joltek works with manufacturers and investors to de-risk modernization and build the internal capability to sustain results.Connect with Vlad: https://www.linkedin.com/in/vladimirromanov/Want to go deeper? Vlad and the team at Joltek have covered related topics here:Edge Computing, AI, and the Value of Manufacturing Data: https://www.joltek.com/blog/edge-computing-ai-value-manufacturing-dataDigital Transformation in Manufacturing: https://www.joltek.com/blog/digital-transformation-in-manufacturingDave Griffith is a co-host of The Manufacturing Hub Podcast and founder of Capelin Solutions, an industrial automation firm helping manufacturers adopt smart manufacturing technology. He brings 15 years of experience in industrial automation and digital transformation.Connect with Dave: https://www.linkedin.com/in/davegriffith23/Subscribe to Manufacturing Hub: https://www.manufacturinghub.liveLinkedIn: https://www.linkedin.com/company/manufacturing-hub-networkYouTube: https://www.youtube.com/@ManufacturingHub
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  Ep. 255 - From Virtual Design to Physical AI: Vention's Blueprint for Industrial Robotics 02.04.2026 1t 4min

  Physical 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 GiguèreFrançois 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.ioTimestamps0:00 Introduction and welcome1:00 François Giguère's background and Vention overview2:20 How AI spans Vention's internal tools and customer products4:00 Why embedded and robotics code is harder for AI to generate7:00 Design, automate, simulate: Vention's three-stage AI workflow13:50 Motion streaming: one unified controller for all robot brands18:20 Defining physical AI versus agentic AI20:10 GRIP pipeline and Rapid AI Operator22:40 Case study: MacAlpine Plumbing bin picking with foundation models39:40 Nvidia GTC impressions: agentic AI eclipsing physical AI46:20 Edge versus cloud: why real-time inference stays on-prem56:10 Predictions: physical AI roadmap and the VLA timelineThis episode is sponsored by:MaintainX helps maintenance and operations teams work smarter by putting critical information directly in the hands of technicians. According to MaintainX, technicians spend up to 40 percent of their time searching for answers and responding to radio calls rather than fixing assets.https://www.maintainx.comAbout Your HostsVladimir Romanov is a co-host of The Manufacturing Hub Podcast and the founder of Joltek, an independent manufacturing and industrial automation consulting firm specializing in modernization strategy, digital transformation, and workforce development.Connect with Vlad: https://www.linkedin.com/in/vladromanov/Want to go deeper? Vlad and the team at Joltek have covered related topics here:Industrial Robotics: https://www.joltek.com/blog/industrial-roboticsEdge Computing and AI Value in Manufacturing Data: https://www.joltek.com/blog/edge-computing-ai-value-manufacturing-dataDave Griffith is a co-host of The Manufacturing Hub Podcast and founder of Capelin Solutions, an industrial automation firm helping manufacturers adopt smart manufacturing technology. He brings 15 years of experience in industrial automation and digital transformation.Connect with Dave: https://www.linkedin.com/in/davegriffith23/Subscribe to Manufacturing Hub: https://www.manufacturinghub.liveLinkedIn: https://www.linkedin.com/company/manufacturing-hub-networkYouTube: https://www.youtube.com/@ManufacturingHub
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  Ep. 254 - From Cost Center to Growth Engine: The AI Future of Manufacturing Maintenance 26.03.2026 1t 4min

  AI 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 HaaseNick 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/Timestamps0:00 Introduction1:30 Nick Haase and MaintainX Background7:20 Where AI Fits for Frontline Workers10:00 What Data Foundations Are Needed for AI13:30 Why Frontline Adoption Determines Digital Transformation Success16:40 The Skilled Labor Shortage and Retirement Wave18:30 Voice Notes and AI Powered Knowledge Capture25:30 Overcoming Change Management and AI Skepticism34:50 Guardrails and Safe AI for Industrial Environments45:10 Embedding AI in the Flow of Work48:30 AI Agents for Parts Forecasting and Automation55:50 Predict the Future: Maintenance as a Growth CenterReferencesMaintainX: https://www.maintainx.comThe Wrench Factor Podcast: https://podcasts.apple.com/us/podcast/the-wrench-factor/id1809000028Origins of Efficiency by Brian Potter: https://www.amazon.com/dp/B0FJG6ZKKJInductive Automation Ignition: https://inductiveautomation.comThis episode is sponsored by MaintainXTechnicians spend up to 40 percent of their time looking for answers rather than fixing equipment. MaintainX puts AI powered knowledge tools directly in the flow of work so frontline teams get the right information in seconds.https://www.maintainx.comAbout Your HostsVladimir Romanov is a co-host of The Manufacturing Hub Podcast and the founder of Joltek, an independent manufacturing and industrial automation consulting firm specializing in modernization strategy, digital transformation, and workforce development. Joltek works with manufacturers and investors to de-risk modernization and build the internal capability to sustain results.Connect with Vlad: https://www.linkedin.com/in/vladimirromanov/Joltek: https://www.joltek.com/blog/digital-transformation-in-manufacturingJoltek: https://www.joltek.com/blog/root-causes-downtime-industrial-automationDave Griffith is a co-host of The Manufacturing Hub Podcast and founder of Capelin Solutions, an industrial automation firm helping manufacturers adopt smart manufacturing technology. He brings 15 years of experience in industrial automation and digital transformation.Connect with Dave: https://www.linkedin.com/in/davegriffith23/Subscribe to Manufacturing Hub: https://www.manufacturinghub.liveLinkedIn: https://www.linkedin.com/company/manufacturing-hub-networkYouTube: https://www.youtube.com/@ManufacturingHub
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  Ep. 253 - How Manufacturers Can Turn Plant Data into AI Powered Insights w/ Konstantin Eukodyne 19.03.2026 1t 28min

  Industrial 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, is that enough to create value later? Konstantin’s answer is thoughtful and realistic. More data alone does not automatically lead to better outcomes. You still need filtering, context, prioritization, architecture, and a disciplined way to separate signal from noise.Learn more about Joltek here:https://www.joltek.com/serviceshttps://www.joltek.com/services/service-details-it-ot-architecture-integrationConnect with our guest:Konstantin Paradizovhttps://www.linkedin.com/in/konstantin-paradizov/Learn more about Eukodyne:https://eukodyne.com/Follow Manufacturing Hub for more conversations on industrial AI, digital transformation, OT architecture, SCADA, MES, industrial data strategy, systems integration, and the future of manufacturing technology.Timestamps00:00 Welcome and introduction to industrial AI applications01:50 Konstantin’s background from pharma to manufacturing05:30 Why food and beverage offered major process improvement opportunities08:10 How to identify the right manufacturing opportunities to pursue13:10 Using AI to accelerate discovery, documentation, and customer value21:20 The on premises AI hardware stack and model selection strategy30:10 Why iterative validation still matters more than a first AI answer39:00 Claude Code, developer workflows, and practical AI tool stacks48:20 On premises versus cloud AI and how to think about the tradeoff54:10 Small models, low cost hardware, and edge deployment realities01:05:00 Plant data, historians, filtering, and separating signal from noise01:14:50 Predictions for industrial AI, career advice, and final recommendationsReferences and resources mentioned in the episodeMaintainXhttps://www.maintainx.com/Solve for Happyhttps://www.mogawdat.com/booksGeorge Orwell 1984https://www.penguinrandomhouse.com/books/326569/1984-by-george-orwell/George Orwell Animal Farmhttps://www.penguinrandomhouse.com/books/561805/animal-farm-by-george-orwell/