Ep. 243 - From Legacy Systems to AI Readiness A Realistic Look at Manufacturing Modernization скачать в хорошем качестве

Ep. 243 - From Legacy Systems to AI Readiness A Realistic Look at Manufacturing Modernization

Technology modernization in manufacturing is not a list of shiny tools. It is a sequencing problem. In this episode of Manufacturing Hub, Vlad Romanov and Dave Griffith break down why the executive vision for AI often collides with the reality of the plant floor, and what a practical path forward actually looks like when you account for data quality, legacy controls, networking, and the true cost of integration. A core theme in this conversation is imperfect information. Leaders often believe the data already exists because reports exist. But a stack of paper, a few spreadsheets, or a single counter value is not the same as contextualized, trustworthy history that can drive decisions or support advanced analytics. Vlad and Dave walk through why foundational work matters, what teams usually miss during modernization, and how quickly the bill grows when you discover your architecture is outdated, undocumented, or full of dependencies you cannot see until you open panels and start tracing signals. You will also hear a grounded debate on how to think about SCADA, MES, historians, dashboards, and what it would actually mean to “feed data into AI” in a manufacturing context. The takeaway is simple. If you want better outcomes, you need a better understanding of your current state, a clear business case, and a roadmap that prioritizes what matters operationally. Modernization is not one big upgrade. It is a series of decisions that either reduce friction or create it. About the hosts Vlad Romanov is an industrial automation and manufacturing expert focused on plant assessments, controls and data architecture, IT and OT integration, and workforce upskilling. Vlad has over 10 years of experience across large manufacturers and complex multi site environments, working from PLC and HMI layers up through SCADA, MES, and ERP integration programs. He is the founder of Joltek, where the mission is to help manufacturers modernize safely, build internal capability, and deliver results that actually survive handoff to operations. Learn more about Joltek https://www.joltek.com https://www.joltek.com/services Dave Griffith is an industrial automation practitioner and consultant who works closely with manufacturers to modernize legacy environments, improve reliability, and build practical systems that operators and maintenance teams can support. Dave brings a strong perspective on what is feasible in real plants, where uptime, risk, budget, and organizational readiness drive every decision. Timestamps 00:00:00 Welcome and why this month is about technology modernization 00:02:10 The real problem with “just add AI” in manufacturing 00:04:15 Quick background on Vlad and Dave and the work they do 00:05:25 The disconnect between the perfect factory vision and the plant floor 00:06:25 Vlad on business cases, integration reality, and infrastructure gaps 00:09:05 Dave on imperfect information and why reports are not data 00:14:35 What executives actually want from AI and why it is often about people constraints 00:20:25 How to get there, hardware first, data normalization, and context 00:22:05 Vlad on assessments, legacy hardware, and why upgrades get complicated fast 00:39:00 New facility planning mistakes and why early decisions lock you in 00:45:10 You have the data, now what, OEE baselines, bottlenecks, and root causes 00:58:10 Final takeaways, inventory your architecture and treat data like an asset References and links mentioned Manufacturing Hub Podcast https://www.manufacturinghub.live ProveIt Conference https://www.proveitconference.com Automate Show https://www.automateshow.com Ignition Community Conference https://icc.inductiveautomation.com If you are watching on YouTube, subscribe so you do not miss the rest of this month’s deep dives on hardware, data teams, and practical applications that actually work on real plant floors.