Manufacturing Hub copertina

Manufacturing Hub

Manufacturing Hub

Di: Vlad Romanov & Dave Griffith
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 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.© 2026 Vlad Romanov & Dave Griffith Economia Gestione e leadership Management
Episodi
  • Ep. 246 A - Factory of the Future Without the Hype: Siemens on Data Transparency, Orchestration, and Trust in AI

    Ep. 246 A - Factory of the Future Without the Hype: Siemens on Data Transparency, Orchestration, and Trust in AI
    Feb 12 2026
    This episode wraps up our Technology Modernization theme with a Siemens perspective that feels very grounded in what factories are actually dealing with right now. Brian Albrecht and Louis Hughes from the Siemens XD team walk through what they are seeing in the field across brownfield and greenfield conversations, why executives keep asking for industrial AI before the foundations are ready, and what it really takes to turn messy plant data into something you can trust for analytics, operations, and eventually AI enabled workflows.A big thread in this conversation is that modern manufacturing is not blocked by ambition, it is blocked by readiness. Everyone wants faster decisions, fewer surprises, and higher uptime, but the path there usually starts with boring work that is not optional. Data transparency across machine, plant, MES, and cloud layers. A clear definition of what real time actually needs to mean for a given use case. And a plan to contextualize and orchestrate data so that AI does not get fed junk inputs. Brian and Louis explain how they approach those early customer conversations, how workshops turn vision into prioritized use cases, and why trust, pilots, and repeatability matter more than flashy demos when you are working in regulated or high consequence environments.If you have been hearing nonstop AI buzz but you are still wrestling with legacy controls, inconsistent tags, documentation that no one can find, and seven layers of security constraints, this episode is for you. We get into practical use cases like AI vision and anomaly detection, LLMs for tribal knowledge and troubleshooting workflows, and the idea of fast versus slow AI, meaning AI that must act during production versus AI that can analyze after the fact.Timestamps00:00 Welcome and why this episode closes the modernization theme02:10 Meet Brian Albrecht and Louis Hughes from the Siemens XD team05:25 Vertical differences across oil and gas, discrete, and process manufacturing07:50 What executives ask for right now beyond AI, factory of the future and data transparency10:50 Brownfield reality and why most modernization work starts with legacy systems12:30 The AI conversation when foundations are missing, meeting customers where they are15:10 Current AI use cases in manufacturing, downtime, throughput, LLMs, and vision18:10 What it means to be AI ready, data silos, contextualization, and orchestration23:50 Fast versus slow AI and why production time decisions are different from analytics25:30 Edge versus cloud architecture, latency, and where the data should live33:40 Cybersecurity, trust, and why perception can lag behind the technology36:50 Hallucinations, guardrails, and why recommendations usually come before automation51:10 Book recommendations, career advice, and future predictions for industrial AIAbout the hostsVlad Romanov is an electrical engineer with an MBA from McGill University and over a decade of experience in manufacturing and industrial automation. He has worked across large scale environments including Procter and Gamble, Kraft Heinz, and Post Holdings, and he now leads Joltek, helping manufacturers modernize systems, improve reliability, strengthen IT and OT architecture, and upskill technical teams through practical training and on site enablement.Dave Griffith is the cohost of Manufacturing Hub and an industrial automation practitioner who focuses on how modern technologies translate into real factory outcomes, from controls and data foundations to scalable implementation strategies.About the guestsBrian Albrecht started in electrical engineering and spent about a decade in systems integration in Oklahoma City focused on oil and gas, building SCADA, networking, and automation solutions and leading teams delivering real world projects. He now works with Siemens customers on building relationships and delivering solutions that create measurable value.Louis Hughes has roughly 20 years of manufacturing experience, starting in software development for manufacturing and engineering applications, then moving into solution architecture, services delivery, and experience center leadership. He now leads a smart manufacturing team, bringing a software and systems view into automation conversations focused on solving customer problems, not just deploying tools.Joltek Services - https://www.joltek.com/servicesContact Joltek - https://www.joltek.com/contactReferenced in the episodeProveIt Conference - https://www.proveitconference.com/Siemens - https://www.siemens.com/Crossing the Chasm by Geoffrey A Moorehttps://en.wikipedia.org/wiki/Crossing_the_ChasmExtreme Ownership by Jocko Willink and Leif Babinhttps://en.wikipedia.org/wiki/Extreme_Ownership
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    59 min
  • Ep. 246 - Building a Life Sciences Virtual Factory Enterprise C, MQTT, and UNS w/ Amy Williams

    Ep. 246 - Building a Life Sciences Virtual Factory Enterprise C, MQTT, and UNS w/ Amy Williams
    Feb 6 2026
    In this special ProveIt edition of Manufacturing Hub, Vlad Romanoff and Dave Griffith sit down with Amy Williams from Skellig Automation to unpack Enterprise C, a life sciences virtual factory built to look and feel like the reality inside many regulated facilities today. If you work around batch processes, compliance, historian projects, electronic batch records, or industrial data architecture, this conversation is a practical walkthrough of what it actually takes to turn raw signals into a story you can defend, improve, and scale.Amy has spent years working exclusively in life sciences manufacturing, starting deep in DeltaV automation for batch pharma and moving into digital transformation projects that focus on open architectures, modern data pipelines, and real operational outcomes. In this episode, she explains what Enterprise C is simulating, why it was designed as an Industry 3.0 style biotech startup, and what kind of data and documentation a vendor would have to wrestle with in the real world. The factory is producing a fictional enzyme using a fed batch fermentation process, and the UNS publishes realistic one second resolution batch data across four pieces of single use equipment including a mixer, a bioreactor, a chromatography skid, and a TFF skid.One of the most valuable parts of this episode is the reminder that data sitting in an MQTT broker is not inherently valuable. The value comes when the data is contextualized enough that different teams can use it without tribal knowledge, and when the resulting traceability helps you answer the questions that matter in life sciences. What happened during the batch, what changed compared to previous runs, what went out of spec, what documentation proves compliance, and what you should do next time to avoid losing a batch that can cost millions. Amy also explains why Enterprise C intentionally includes uncontextualized tags and paper files, because that is exactly where many facilities still are. The hard part is not connecting a sensor, the hard part is governance, agreement, and building a model that humans actually follow.You will also hear the crew dig into Smart Manufacturing Profiles and why standardizing information models is one of the clearest paths toward true interoperability. If you are tired of every site, every integrator, and every project reinventing the same pump, valve, and equipment model from scratch, this is the kind of conversation that helps frame why that problem keeps repeating and what might finally reduce it. The ProveIt format forces the questions that most conferences avoid, including what problem was solved, how it was done, how long it took, and what it cost. That is exactly why this conference has become a magnet for practitioners who care about the difference between a demo and a deployable solution.About the hostsVlad Romanoff is an industrial automation and manufacturing systems expert and the founder of Joltek. He has over a decade of experience modernizing control systems, data infrastructure, and plant operations across regulated and high throughput manufacturing environments.Dave Griffith is the cohost of Manufacturing Hub and a long time practitioner in industrial automation and manufacturing technology, focused on practical deployment and what actually works on the plant floor.About the guestAmy Williams works with Skellig Automation and has spent years in life sciences manufacturing, from DeltaV batch automation to digital transformation initiatives that focus on open architectures, data contextualization, and scalable modernization strategies.Timestamps 00:00 ProveIt edition intro and why this month is technology modernization 01:40 Who is Amy Williams and why Enterprise C matters this year 02:10 Amy’s background in life sciences, DeltaV, and digital transformation 03:30 Unified Namespace explained in plain language for life sciences 05:10 What Enterprise C publishes and what you will see in the MQTT broker 07:10 Why UNS in life sciences is about use cases, not buzzwords 10:10 Smart Manufacturing Profiles and reducing data model reinvention 11:10 What outcomes to expect including compliance and golden batch analysis 12:10 Enterprise C process overview from mixer to bioreactor to downstream 14:10 Bioreactor instrumentation and what operators still do manually 19:40 Why Enterprise C data is intentionally not contextualized 22:10 The real work of mapping signals to compliance stories and governance 25:10 What SM Profiles enable and why schema matters before data arrives 31:30 Why cost and time questions change everything at ProveIt 36:10 Cell counter files, batch records, and paper driven reality in many sites 45:10 What life sciences attendees should ask during Q and A 58:30 Vendors the team is excited to see and why non traditional players matter 01:02:20 Where to find Skellig at the conference and what they are bringingReferences and links mentioned Skellig Automation https://...
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    1 ora e 5 min
  • Ep. 245 - Modernizing Manufacturing | Data, OEE, Quality Analytics - Everyone Wants the Same Signals

    Ep. 245 - Modernizing Manufacturing | Data, OEE, Quality Analytics - Everyone Wants the Same Signals
    Feb 5 2026
    In this episode of Manufacturing Hub, Vlad Romanov and Dave Griffith sit down with David for a practical, operator grounded conversation about industrial data, modernization, and what it actually takes to turn plant floor signals into business decisions. David has spent more than two decades in manufacturing across automotive, solar, and electric vehicles, and his story is a familiar one for a lot of us. He walked into a plant thinking he was there for a project, discovered PLCs in real time, and never left the factory world. From early days wiring up a SQL Server to pull line data instead of sending people out with stopwatches, to leading data and analytics and shaping MES and reporting strategy, this conversation stays focused on the messy middle where most factories live.A big theme here is that collecting data is not the same thing as creating information. As tooling has improved, connectivity, historians, SCADA, cloud storage, MQTT, and the modern ecosystem have made it easier to get signals out of machines. The hard part is deciding what matters, aligning stakeholders, and creating context that survives across teams and projects. David breaks down how real progress often starts with simple visibility, what is ruining your day, what is the biggest safety risk, what is the recurring quality miss, what is the downtime story you do not trust, then builds from there using workshops and iterative delivery instead of giant multi year “boil the ocean” programs.We also get into Unified Namespace, why it resonates with people who have been burned by tightly coupled ISA style integrations, and why change management is the hidden cost. If you are exploring UNS, this episode highlights the difference between drawing the box on a whiteboard and getting a whole organization to actually adopt consistent naming, context, and ownership. Then we finish with a grounded take on industrial AI. No hype, no doom. Just a realistic view of where AI helps today, where it breaks, and why context windows, documentation quality, and domain expertise still decide whether results are useful or dangerous.Timestamps00:00:00 Welcome and the month theme on technology modernization00:02:10 David’s background from automotive and the Tesla Fremont NUMMI era to data leadership00:05:10 The moment data became “real” and why proactive visibility drives safety and outcomes00:07:10 How Kaizen and Toyota Production System style problem solving creates demand for data00:11:50 Why modern tooling makes collection easier and why budget and commitment still decide success00:16:10 Starting points that work in the real world and the simplest visibility model that scales00:18:20 Unified Namespace explained through decoupling, context, and why the first attempt often fails00:23:50 Who really uses the data, operators, quality, engineering, and the “next factory” teams00:29:10 Defining KPIs when nobody has answers and using workshops to force prioritization00:34:20 What rollouts actually take, machine states, data structures, controls changes, and iteration00:40:10 Industrial AI reality check, where it helps today and why it is not running your factory00:51:10 Predicting the next few years, consolidation, pricing, and better integration with agentsAbout the hostsVlad Romanov is an industrial automation and manufacturing leader with over a decade of plant floor experience across major manufacturers. He is the founder of Joltek, where he helps teams modernize operations through IT and OT architecture, integration, reliability focused execution, and practical upskilling that actually sticks. Joltek works with manufacturers who need real outcomes, not buzzwords, and the work spans controls, data, networking, and operational performance.Dave Griffith is the co host of Manufacturing Hub and works at the intersection of manufacturing operations, technology modernization, and practical delivery. He focuses on helping teams bridge the gap between “we want data” and “we can run this plant better next quarter.”About the guestDavid has 25 plus years of manufacturing experience spanning automotive, solar manufacturing, and EVs. He started in plant floor automation and conveyance projects, then moved deeper into industrial data, MES, and analytics leadership. His recent work includes leading data and analytics, defining KPI strategy, and building the layers required to turn raw plant signals into usable business information.Links from Joltekhttps://www.joltek.com/blog/mastering-unified-namespace-uns-a-guide-to-data-driven-manufacturing-transformationhttps://www.joltek.com/blog/ultimate-guide-mqtt-manufacturingSubscribe for more conversations on manufacturing modernization, industrial data architecture, MES realities, and what works on the plant floor when the budget, people, and legacy systems are all real.
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    1 ora e 1 min
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