Skip to content
Sign in
Artwork for Manufacturing Hub
TechnologyBusinessManagement

Manufacturing Hub

Vlad Romanov & Dave Griffith

We bring you manufacturing news, insights, discuss opportunities, and cutting edge technologies. Our goal is to inform, educate, and inspire leaders and workers in manufacturing, automation, and related fields.

Play
Open in
  • 21 episodes
  • weekly
  • Avg 1 hr 7 min
  • English

Episodes 21

NewestOldestLongest
All20Unplayed20In progress0Played0
Counted on this page — what you have heard stays on this device, so it is not something the list can be paged by.
  • #258
    Thursday · 1 hr 11 min

    Ep. 271 - Growing an Oil and Gas Plus Mining Systems Integrator in Alberta with JPI Solutions

    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 Symes Dustin 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.ca Timestamps 0:00 Introduction 5:50 Why he started JPI Solutions 10:50 Oil and gas primer: upstream, midstream, downstream 12:50 What makes mining automation different 16:10 Where JPI sits in the automation stack 28:30 Bigger well pads, redundant PLCs and MQTT 41:20 Bringing on partners when nobody recommended it 51:10 Communication as the only consistent complaint 1:04:40 The future of integration, AI and knowledge graphs References Radical Candor by Kim Scott: https://www.amazon.com/Radical-Candor-Kick-Ass-Without-Humanity/dp/1250103509 Creativity, Inc. by Ed Catmull: https://www.amazon.com/Creativity-Inc-Overcoming-Unseen-Inspiration/dp/0812993012 ThredCloud: https://www.thredcloud.com About Your Hosts Vladimir 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-integrators PLC Scan Cycles and SCADA Polling: https://www.joltek.com/blog/plc-scan-cycles-polling-scada-systems-data Dave 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.live LinkedIn: https://www.linkedin.com/company/manufacturing-hub-network YouTube: https://www.youtube.com/@ManufacturingHub

  • #257
    August 20 · 1 hr 15 min

    Ep. 270 - How to Start a Systems Integrator: Scope, Hiring, and the Bottleneck That Is You

    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 DuFresne Dylan 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.com Timestamps 0:00 Introduction 4:30 What a systems integrator actually is 9:00 Why Dylan and Glenn started Abelara 14:00 Following the customer or picking platforms first 20:00 Consulting versus integration work 25:00 Why integrators get brought in too late 32:00 The $30,000 camera and business trade offs 36:30 Scope of work and what does done look like 43:20 Handing projects to the team and subcontractors 52:10 First hires, bottlenecks, and forecasting 57:40 AI and the future of systems integration 1:05:40 Predictions, career advice, and books References The Phantom Pallet by Dylan DuFresne: https://www.amazon.com/Phantom-Pallet-Manufacturing-Fable-Transformation-ebook/dp/B0GGYCK5PR Impro: Improvisation and the Theatre by Keith Johnstone: https://www.amazon.com/Impro-Improvisation-Theatre-Keith-Johnstone/dp/041346430X About Your Hosts Vladimir 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-integrators Consulting, Upskilling, and Systems Integration: https://www.joltek.com/blog/humble-beginnings-consulting-upskilling-systems-integration Dave 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.live LinkedIn: https://www.linkedin.com/company/manufacturing-hub-network YouTube: https://www.youtube.com/@ManufacturingHub

  • #256
    August 13 · 1 hr 13 min

    Ep. 269 - Siemens Xcelerator Marketplace: Digital Transformation SMB Manufacturers Can Afford

    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 Guests Martin 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. Timestamps 0:00 Introduction 2:20 Martin Valkysers on his path to Xcelerator 4:20 Flemming Kongsberg from AWS to Siemens SMB 7:10 Four challenges facing manufacturers 13:40 Why data comes before AI 18:00 What Siemens Xcelerator actually is 22:30 Partner ecosystem: build, service, sell 31:40 Inside the SMB starter package 35:50 What the package costs 38:20 A 24 minute install and non Siemens PLCs 45:50 Redefining what counts as an SMB 53:50 The future of industrial marketplaces References Getting 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 by Siemens 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.com About Your Hosts Vladimir 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-manufacturing Edge Computing and the AI Value of Manufacturing Data: https://www.joltek.com/blog/edge-computing-ai-value-manufacturing-data Dave 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.live LinkedIn: https://www.linkedin.com/company/manufacturing-hub-network YouTube: https://www.youtube.com/@ManufacturingHub

  • #255
    August 6 · 1 hr 8 min

    Ep. 268 - David Nichols of Loupe on Claude Code, AI Retrofits, and the End of the SI Moat

    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 Nichols David 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.team Timestamps 0:00 Introduction 2:45 Loupe, 20 years of controls, and the SASE community 8:40 Carburetors in industrial automation: culture, not technology 11:20 The ChatGPT moment versus the Claude Code moment 20:20 Inside an integrator: six week sprints become two 21:30 Reverse engineering a robotic cell in 30 minutes 26:10 A 100 page ethernet spec turned into working code in a day 27:50 Does this change who gets to be a builder 40:40 AI across the project lifecycle from discovery to handoff 49:00 How to actually get started, and what to prompt 53:20 If software is no longer a moat, what is 57:50 Predict the future, career advice, and the book pick References SASE: https://sase.space Claude: https://claude.ai Claude Code: https://claude.com/claude-code SendCutSend: https://sendcutsend.com Acquired Podcast: https://www.acquired.fm About Your Hosts Vladimir 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-strategy Edge Computing and AI Value from Manufacturing Data: https://www.joltek.com/blog/edge-computing-ai-value-manufacturing-data Dave 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.live LinkedIn: https://www.linkedin.com/company/manufacturing-hub-network YouTube: https://www.youtube.com/@ManufacturingHub

  • #254
    July 30 · 1 hr 2 min

    Ep. 267 - Ujjwal Kumar of Siemens on Deglobalization, Reshoring, and Adaptive Manufacturing

    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 Kumar Ujjwal 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. Timestamps 0:00 Introduction 2:00 Career path from General Motors to Siemens 6:10 What deglobalization means for manufacturing 9:00 COVID, vaccine quotas, and the reshoring trigger 13:05 Labor arbitrage versus automation arbitrage 15:50 Attracting the next generation of factory workers 19:35 Why semiconductor reshoring will take years 23:00 Tribal knowledge and the documentation problem 26:00 Where the investment is going right now 32:30 Adaptive manufacturing and the AI hype question 35:30 Platforms, ecosystems, and Siemens Xcelerator 43:20 Careers, AI, and advice for engineers References Siemens Xcelerator Marketplace: https://xcelerator.siemens.com/global/en.html This episode is sponsored by Siemens 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.com About Your Hosts Vladimir 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-chains Manufacturing Challenges with New Machinery and Plants: https://www.joltek.com/blog/manufacturing-challenges-new-machinery-plant Dave 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.live LinkedIn: https://www.linkedin.com/company/manufacturing-hub-network YouTube: https://www.youtube.com/@ManufacturingHub

  • #253
    July 18 · 1 hr 27 min

    Ep. 266 - Automate 2026 Reality Check: AI, Virtual PLCs, Ignition, and Plant Modernization

    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.

  • #252
    June 18 · 35 min

    Ep. 265 - Automate 2026 Survival Guide: Booths, Networking, and a Production Line Demo #scada #mes

    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. Timestamps 0:00 Welcome and Automate 2026 preview 1:50 First timer tips and arriving early for registration 3:10 Networking events worth attending: A3 and Manufacturing Champions 4:40 Building a trade show checklist to maximize your time 7:00 Manufacturing Hub at the Siemens and Horner booths 9:50 Vlad's live production line demo at the Teguar booth 15:40 The line overview screen and five packaging assets 17:30 Fault handling and finding the bottleneck 20:10 Inside the stack: Ubuntu, Portainer, Ignition, MariaDB 23:50 Random fault simulation and PLC driver options 27:00 Who should come see the demo 29:40 Vendors Vlad is tracking and closing thoughts References Automate 2026: https://www.automate.org Ignition by Inductive Automation: https://inductiveautomation.com Horner Automation: https://hornerautomation.com About Your Hosts Vladimir 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-ignition Manufacturing Line Speed Optimization: https://www.joltek.com/case-study/manufacturing-line-speed-optimization Dave 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.live LinkedIn: https://www.linkedin.com/company/manufacturing-hub-network YouTube: https://www.youtube.com/@ManufacturingHub

  • #251
    June 11 · 1 hr 4 min

    Ep. 264 - Why AI Loves Automation: Siemens on Digital Twins, Guardrails, and Orchestration

    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 Stevens Chris 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 Breu Annemarie 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. Timestamps 0:00 Introduction and Automate 2026 preview 2:50 Meet Chris Stevens and Annemarie Breu 9:30 The first AI question is always ROI 14:00 Workforce gaps and OEE drive the business case 19:30 Energy management and the data center demand surge 23:20 Data, sensors, and contextualization requirements 28:00 Guardrails, hallucinations, and two channel validation 32:40 The digital twin and the human in the loop 37:40 How partners and integrators move up the stack 45:30 What it takes to make AI real on the floor 55:50 Preventive maintenance as a quick win 59:40 Predictions, career advice, and book picks About Your Hosts Vladimir 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-data IT and OT Architecture Integration: https://www.joltek.com/services/service-details-it-ot-architecture-integration Dave 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.live LinkedIn: https://www.linkedin.com/company/manufacturing-hub-network YouTube: https://www.youtube.com/@ManufacturingHub

  • #250
    June 4 · 1 hr 3 min

    Ep. 263 - Why Industrial Protocols Win on Business Not Technical Merit, with Horner Automation

    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 Automation Chuck 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. Timestamps 0:00 Introduction 2:20 Chuck's Background and 36 Years at Horner Automation 9:20 End User Engineer vs OEM Manufacturer Perspective 13:20 New at Automate: HMI Connect and the CPU 151 Edge PLC 21:30 The Fieldbus Wars and the History of Industrial Protocols 24:20 What It Takes to Implement a Protocol Stack 29:30 Why Protocols Win: Commercial Force vs Technical Merit 32:40 Will Industrial Protocols Ever Converge? 40:30 High Speed Motion: EtherCAT, PROFINET IRT, and Ethernet/IP 44:40 FPD-Link: Rugged Remote HMI for Ambulances and Fire Trucks 55:00 PLCs as Data Devices and the Push Toward AI 1:02:40 Cybersecurity Mandates Coming for Application Engineers References Horner Automation: https://www.hornerautomation.com About Your Hosts Vladimir 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-evolved Industrial Ethernet Reliability: https://www.joltek.com/blog/industrial-ethernet-reliability Dave 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.live LinkedIn: https://www.linkedin.com/company/manufacturing-hub-network YouTube: https://www.youtube.com/@ManufacturingHub

  • #249
    May 28 · 1 hr 5 min

    Ep. 262 - The Human Side of Manufacturing Change: Incentives, Pain Points, and Operator Buy In

    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. Timestamps 0:00 Introduction and Automate trade show preview 1:30 Booth commitments: Siemens, Horner, and Tigoor 6:00 Dave's Automate session and 4IR booth duty 8:10 Predictions for Automate: physical AI, cobots, and the AI conversation 13:10 Defining change management in manufacturing 22:30 From P&G IWS to Kraft Heinz: tools versus deployment maturity 28:30 What is in it for the person you are asking to change 35:30 The RCA cascade at P&G compared to no process elsewhere 42:30 The fifty dollar gift card incentive that backfired 46:00 The Joe story: QR codes solving real operator pain 58:30 Reading change management success in the first meeting 1:07:00 Start small: the closing takeaway About Your Hosts Vladimir 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-sigma 7 Different Root Cause Analysis Techniques in Manufacturing: https://www.joltek.com/blog/7-different-root-cause-analysis-techniques-manufacturing Dave 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.live LinkedIn: https://www.linkedin.com/company/manufacturing-hub-network YouTube: https://www.youtube.com/@ManufacturingHub

  • #248
    May 21 · 1 hr 2 min

    Ep. 261 - Change Management in Manufacturing: Operators, Tribal Knowledge, and the Industrial Elder

    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-manufacturing Mastering the Unified Namespace for Manufacturing: https://www.joltek.com/blog/mastering-unified-namespace-uns-a-guide-to-data-driven-manufacturing-transformation Ron 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/ Timestamps 0:00 Welcome and Episode Intro 1:50 Ron's Career: Oil and Gas to Pharma at Regeneron 4:30 Defining Change Management and Its KPIs 8:30 Change Management vs Operational Excellence 11:50 Who Owns Change Management on Industrial Projects 17:00 Negotiating Power: Large vs Small Manufacturers 20:30 Why Capital Projects End Up Mothballed 22:10 Tribal Knowledge and Learning From Operators 26:00 Why Industrial Projects Fail 29:00 The Industrial Elder and Passing Knowledge Through People 31:30 AI Generated Documentation in Manufacturing 35:50 Project Planning and the RFP Process 47:50 A Successful SCADA Deployment and User Story Workshops 54:30 Predictions, Career Advice, and Smart Glasses About Your Hosts Vladimir 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.live LinkedIn: https://www.linkedin.com/company/manufacturing-hub-network YouTube: https://www.youtube.com/@ManufacturingHub

  • #247
    May 14 · 1 hr 10 min

    Ep. 260 - Why Ignition Is Winning: Colby Clegg and Carl Gould on SCADA, Open Access, & Industrial AI

    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 Gould Colby Clegg is the CEO and cofounder of Inductive Automation, the California based company behind Ignition, the cross platform SCADA, MES, and IIoT software used by manufacturers and integrators worldwide. Carl Gould is the CTO and cofounder, leading product and engineering direction across Ignition. Both joined founder Steve Heckman in 2003 and have shaped the platform's open, integrator first philosophy ever since. Inductive Automation: https://www.inductiveautomation.com Timestamps 0:00 Introduction 1:00 Meet Colby Clegg and Carl Gould 2:00 The origins of Inductive Automation in 2003 8:00 Going to market and the Innovator's Dilemma 10:30 Innovation without permission as company culture 18:50 Ignition 8.0 and the leap to Perspective 26:00 The five year journey to 8.3 38:00 The MCP server module and AI in Ignition 45:30 AI in the control plane and guardrails 52:30 Tiger Data and the technology ecosystem 1:02:30 Career advice for the next generation 1:06:40 What is ripe for innovation References Ignition Community Conference: https://icc.inductiveautomation.com About Your Hosts Vladimir 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-8-3 Connecting Allen Bradley PLCs to Ignition: https://www.joltek.com/blog/connecting-allen-bradley-plc-ignition 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. 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.live LinkedIn: https://www.linkedin.com/company/manufacturing-hub-network YouTube: https://www.youtube.com/@ManufacturingHub

  • #246
    May 7 · 1 hr 8 min

    Ep. 259 - Logan Terry of LSI on Change Management: The Soft Side of SCADA, MES, & ERP Projects

    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 Terry Logan Terry leads digital transformation at LSI, a multinational systems integrator with roughly 400 resources across 13 North American locations and offices in Asia Pacific. A mechanical engineer by training, Logan spent a decade in PLC, HMI, and SCADA development before moving into digital transformation consulting and joining LSI in late 2024. His work spans advanced SCADA, MES, analytics, and BI integrations. LSI: https://www.logicalsysinc.com/ Timestamps 0:00 Introduction 2:15 Logan's background and the LSI digital transformation practice 7:25 Defining change management 9:00 Why MES requires the most change management 13:00 How young engineers stumble into change management 24:30 Starting with decisions and workflows before technology 35:00 Internal CI capability as a project gating factor 43:30 OEE dashboard turned off six months after go live 46:30 Behavioral psychology of how operators read numbers 54:50 Modular MES replacing monolithic platforms 58:00 Generative AI and continuous validation 1:11:00 AI assisted prototyping shrinking design cycles About Your Hosts Vladimir 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-manufacturing Manufacturing Execution Systems and Business Strategy: https://www.joltek.com/blog/manufacturing-execution-systems-business-strategy Dave 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.live LinkedIn: https://www.linkedin.com/company/manufacturing-hub-network YouTube: https://www.youtube.com/@ManufacturingHub

  • #245
    April 30 · 1 hr 8 min

    Ep. 258 - Hannover Messe Recap, the State of Industrial AI, and What Comes Next at Automate 2026

    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. Timestamps 0:00 Introduction 1:50 Hannover Messe scale, halls, and country delegations 7:20 Booth diversity from startups to hyperscalers and the German military 12:20 Why end users have stopped asking, do you have AI 19:00 The 1% on the bleeding edge versus the rest of industry 25:50 End users sending boilerplate PLC code through ChatGPT 29:20 Data governance on the OT side 32:50 AI inside systems integration workflows 39:50 Workforce shifts: UPS buyouts, FAANG layoffs, and reskilling 47:20 Hardware innovation, Moore's Law, and the industrial side 59:50 SCADA, MES, ERP, and AI generated dashboards 1:03:30 Upcoming shows: Automate 2026, ICC, and more References Hannover Messe: https://www.hannover-messe.de Automate 2026: https://www.automateshow.com Ignition Community Conference: https://icc.inductiveautomation.com Rockwell Automation Fair: https://www.rockwellautomation.com/automationfair About Your Hosts Vladimir 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-data Systems Integrators in Manufacturing: https://www.joltek.com/blog/system-integrators Dave 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/

  • #244
    April 9 · 1 hr 9 min

    Ep. 256 - Why Machine Learning Still Outperforms LLMs for Manufacturing Process Control

    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 Vora Virag Vora is a solutions professional at Twin Thread, a platform that combines data centric digital twins with machine learning to optimize manufacturing processes. With a background in chemical engineering, Virag began his career deploying MES and DCS systems in biotech and pharma before joining Tulip and then Twin Thread. He helps manufacturers connect their existing data infrastructure to AI powered optimization across batch, continuous, and hybrid processes. Timestamps 0:00 Introduction 1:20 Virag's background in chemical engineering and industrial software 6:30 Moving up the ISA 95 stack from DCS to MES and applications 9:00 How AI reinvents digital twin, golden batch, and SPC concepts 12:20 What a data centric digital twin actually looks like 21:40 Where digital twins deliver the most value in manufacturing 27:00 Seasonality, segmentation, and model training strategies 36:00 Data prerequisites for deploying industrial AI 41:40 Flavors of AI in manufacturing: ML, LLMs, and agentic workflows 50:40 Closed loop AI control at Hills Pet Nutrition 53:10 Personal project: Family Graph using knowledge graphs 56:20 Prediction: operators as human digital twins References Twin Thread: https://twinthread.com This episode is sponsored by MaintainX 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.com About Your Hosts Vladimir 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-data Digital Transformation in Manufacturing: https://www.joltek.com/blog/digital-transformation-in-manufacturing Dave 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.live LinkedIn: https://www.linkedin.com/company/manufacturing-hub-network YouTube: https://www.youtube.com/@ManufacturingHub

  • #243
    April 2 · 1 hr 4 min

    Ep. 255 - From Virtual Design to Physical AI: Vention's Blueprint for Industrial Robotics

    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 Giguère François Giguère is the CTO of Vention, an industrial automation platform where manufacturers design, program, simulate, and deploy robotic systems entirely online. Employee number four at the company, he has contributed to Vention's growth for over 10 years and leads a team of 95 engineers. He holds a background in electrical engineering and real-time embedded software development. Learn more: https://vention.io Timestamps 0:00 Introduction and welcome 1:00 François Giguère's background and Vention overview 2:20 How AI spans Vention's internal tools and customer products 4:00 Why embedded and robotics code is harder for AI to generate 7:00 Design, automate, simulate: Vention's three-stage AI workflow 13:50 Motion streaming: one unified controller for all robot brands 18:20 Defining physical AI versus agentic AI 20:10 GRIP pipeline and Rapid AI Operator 22:40 Case study: MacAlpine Plumbing bin picking with foundation models 39:40 Nvidia GTC impressions: agentic AI eclipsing physical AI 46:20 Edge versus cloud: why real-time inference stays on-prem 56:10 Predictions: physical AI roadmap and the VLA timeline This 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.com About Your Hosts Vladimir 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-robotics Edge Computing and AI Value in Manufacturing Data: https://www.joltek.com/blog/edge-computing-ai-value-manufacturing-data Dave 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.live LinkedIn: https://www.linkedin.com/company/manufacturing-hub-network YouTube: https://www.youtube.com/@ManufacturingHub

  • #242
    March 26 · 1 hr 4 min

    Ep. 254 - From Cost Center to Growth Engine: The AI Future of Manufacturing Maintenance

    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 Haase Nick Haase is a co-founder of MaintainX, a frontline work execution platform for maintenance, reliability, SOPs, safety, and compliance serving nearly 14,000 customers across manufacturing and other asset-intensive industries. Nick is also the host of The Wrench Factor podcast. Connect with Nick: https://www.linkedin.com/in/nickhaase/ Timestamps 0:00 Introduction 1:30 Nick Haase and MaintainX Background 7:20 Where AI Fits for Frontline Workers 10:00 What Data Foundations Are Needed for AI 13:30 Why Frontline Adoption Determines Digital Transformation Success 16:40 The Skilled Labor Shortage and Retirement Wave 18:30 Voice Notes and AI Powered Knowledge Capture 25:30 Overcoming Change Management and AI Skepticism 34:50 Guardrails and Safe AI for Industrial Environments 45:10 Embedding AI in the Flow of Work 48:30 AI Agents for Parts Forecasting and Automation 55:50 Predict the Future: Maintenance as a Growth Center References MaintainX: https://www.maintainx.com The Wrench Factor Podcast: https://podcasts.apple.com/us/podcast/the-wrench-factor/id1809000028 Origins of Efficiency by Brian Potter: https://www.amazon.com/dp/B0FJG6ZKKJ Inductive Automation Ignition: https://inductiveautomation.com This episode is sponsored by MaintainX Technicians 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.com About Your Hosts Vladimir 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-manufacturing Joltek: https://www.joltek.com/blog/root-causes-downtime-industrial-automation Dave 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.live LinkedIn: https://www.linkedin.com/company/manufacturing-hub-network YouTube: https://www.youtube.com/@ManufacturingHub

  • #241
    March 19 · 1 hr 28 min

    Ep. 253 - How Manufacturers Can Turn Plant Data into AI Powered Insights w/ Konstantin Eukodyne

    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/services https://www.joltek.com/services/service-details-it-ot-architecture-integration Connect with our guest: Konstantin Paradizov https://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. Timestamps 00:00 Welcome and introduction to industrial AI applications 01:50 Konstantin’s background from pharma to manufacturing 05:30 Why food and beverage offered major process improvement opportunities 08:10 How to identify the right manufacturing opportunities to pursue 13:10 Using AI to accelerate discovery, documentation, and customer value 21:20 The on premises AI hardware stack and model selection strategy 30:10 Why iterative validation still matters more than a first AI answer 39:00 Claude Code, developer workflows, and practical AI tool stacks 48:20 On premises versus cloud AI and how to think about the tradeoff 54:10 Small models, low cost hardware, and edge deployment realities 01:05:00 Plant data, historians, filtering, and separating signal from noise 01:14:50 Predictions for industrial AI, career advice, and final recommendations References and resources mentioned in the episode MaintainX https://www.maintainx.com/ Solve for Happy https://www.mogawdat.com/books George Orwell 1984 https://www.penguinrandomhouse.com/books/326569/1984-by-george-orwell/ George Orwell Animal Farm https://www.penguinrandomhouse.com/books/561805/animal-farm-by-george-orwell/

  • #240
    March 12 · 1 hr 5 min

    Ep. 252 - Industrial AI in Manufacturing What Actually Works and What Does Not #industrialautomation

    Manufacturing Hub is back with Episode 252, where co hosts Vlad Romanov and Dave Griffith break down what an AI survival guide should actually look like for manufacturing and industrial automation professionals. This is not a hype conversation about replacing people with magic software. It is a grounded discussion about what AI tools can do today, where they fail, why context and data quality matter so much, and how industrial teams should think about experimentation without losing sight of real operating constraints. In this episode, Vlad and Dave unpack the evolution many engineers and technical leaders have already felt in real time, from early prompt engineering, to agent based workflows, to MCP servers, skills, context management, and the growing cost of tokens and infrastructure. The conversation moves beyond generic AI commentary and into the reality of plant floor environments, where success depends on process knowledge, data architecture, OT constraints, cybersecurity, governance, and clear business value. One of the strongest themes throughout the episode is that manufacturers cannot skip the hard work of structuring data, understanding workflows, and defining use cases simply because AI tools are moving quickly. Vlad brings a very practical industrial lens to the discussion. Drawing on years of hands on experience across controls, manufacturing systems, plant modernization, and digital transformation, he explains why industrial AI has to start with operational context. A maintenance team, an engineering team, and a quality team do not need the same data, do not ask the same questions, and should not be handed the same AI workflows. That distinction matters. This conversation also highlights why the best industrial AI implementations will likely come from teams that combine domain expertise with strong technical execution, rather than generic AI shops trying to force a solution into environments they do not fully understand. Dave adds an important systems and adoption perspective, especially around cost, scaling, management expectations, and the danger of trying to prompt your way past foundational architecture work. Together, Vlad and Dave explore why manufacturers are interested in AI, why many are afraid of being left behind, and why so many projects still stall once they hit the realities of obsolete equipment, weak data models, fragmented systems, and unclear ownership of information. They also discuss deterministic logic versus LLM behavior, reporting workflows, industrial dashboards, PLC code generation concerns, and the practical question every manufacturer should ask before investing: what problem are we solving, for whom, and what is the measurable return? For those new to Vlad, he is an electrical engineer and manufacturing leader with deep experience across industrial automation, controls, data systems, OT architecture, modernization strategy, and plant operations. Through Joltek, Vlad works with manufacturers on digital transformation, IT OT architecture and integration, modernization planning, operational improvement, and technical workforce enablement. Learn more here: Joltek: https://www.joltek.com IT OT Architecture and Integration: https://www.joltek.com/services/service-details-it-ot-architecture-integration If you are a plant leader, controls engineer, systems integrator, OT architect, SCADA or MES practitioner, or simply someone trying to separate useful AI workflows from noise, this episode will give you a much more realistic framework for thinking about industrial AI adoption. Timestamps 00:00 Welcome back and why this episode matters 01:00 Setting up the industrial AI theme for the coming weeks 03:10 From prompt engineering to structured AI workflows 05:30 AI agents, parallel workflows, tokens, and context windows 09:00 MCP tools, Playwright, and what new integrations unlock 16:20 How Vlad researches AI and where useful information actually lives 22:00 Real manufacturing problems versus AI in search of a problem 29:40 Why industrial data architecture is harder than most people think 37:00 OT expertise, workforce enablement, and who should build solutions 45:40 Practical advice for manufacturers starting the AI journey 50:30 Data governance, hallucinations, infrastructure, and cybersecurity 57:20 What looks promising today in reporting, dashboards, and industrial applications

  • #239
    March 5 · 1 hr 3 min

    Ep. 251 - Ignition 8.3 ProveIt How Inductive Automation Scales Multi Site Factories w/ MQTT and UNS

    In this episode of Manufacturing Hub, Vlad and Dave sit down with Travis Cox and Kevin McCluskey from Inductive Automation to unpack what was actually proven at ProveIt and why it matters for teams trying to modernize plants without building a fragile mess of point to point integrations. If you have ever looked at a shiny demo and wondered what the real architecture looks like, how it scales beyond a single line, and what it takes to roll out across multiple sites without turning every change into a high risk event, this conversation is for you. Travis and Kevin walk through their ProveIt Enterprise B build and the thinking behind it. The core idea is simple but powerful: treat the factory like a system that needs a shared digital infrastructure, built on open standards, where data is contextualized and reusable. They break down how they used Ignition Edge close to PLCs for resiliency, local HMIs, and disciplined data modeling, then moved data through MQTT into a Unified Namespace so multiple applications can consume the same trusted signals and context. This is the difference between “we can connect to anything” and “we can scale without rewriting everything every time the business changes.” Open standards show up repeatedly in the conversation because ProveIt is specifically designed to force interoperability and practical implementation tradeoffs. Inductive Automation has also written about ProveIt as a place where MQTT, OPC UA, and SQL show up as real foundations rather than slogans. From there, the episode gets into the part that should make both OT and IT teams pay attention: modern deployment practices applied to industrial applications. Kevin outlines a clear maturity path from a single designer workflow to version control, then to containerized deployments, and finally to full GitOps style promotion across dev, staging, and production using tools like Argo CD, Helm, Kubernetes, and release promotion concepts that look like what the software world has used for years. Argo CD is explicitly built around Git repositories as the source of truth for desired state, which is exactly why it fits this style of deployment. The live portion of the conversation demonstrates how fast this can get when the infrastructure is treated as code: they spin up a brand new “site four” by submitting a form, generating a pull request, merging it, and letting the pipeline do the rest. Timestamps 00:00 Welcome back and why this ProveIt recap matters 01:35 Meet Travis Cox and Kevin McCluskey from Inductive Automation 03:10 What ProveIt is and the key vendor questions it forces 05:20 Enterprise B architecture overview from PLC to Edge to site to enterprise 07:30 HMI walkthrough across liquid processing, filling, packaging, palletizing 09:05 Why deploy Ignition Edge instead of only a centralized site gateway 12:05 Design once, reuse everywhere and what that means for scaling quickly 14:35 On prem realities versus cloud infrastructure in the ProveIt environment 17:10 MCP, n8n workflows, and bringing live operational context into AI 20:40 i3X style API access to models, history, and alarms for interoperability 23:15 GitHub, Docker Compose, Helm, Kubernetes, Argo CD, Cargo and GitOps promotion 36:55 Spinning up a new site live and what it changes for multi site rollouts About the hosts Vlad Romanov is an electrical engineer and MBA who has spent over a decade building and modernizing manufacturing systems across industrial automation, controls, and plant operations. Through Joltek, Vlad works with manufacturers to assess current state OT foundations, reduce modernization risk, improve reliability, and build internal capability through practical training and standards that stick. Dave Griffith co hosts Manufacturing Hub and brings a practitioner lens focused on what works on the plant floor, how architectures survive real constraints, and how industrial teams can modernize without breaking production. About the guests Travis Cox is Chief Technology Evangelist at Inductive Automation and has spent over two decades helping customers and partners design scalable architectures, apply best practices, and deliver real solutions with Ignition. Kevin McCluskey is Chief Technology Architect at Inductive Automation and works with organizations on architecture decisions, platform direction, and enabling the next generation of industrial applications. Learn more about Joltek https://www.joltek.com/services https://www.joltek.com/book-a-modernization-consultation

Showing 1–20 of 21 episodes