AI in Manufacturing
AI in Manufacturing is an Industry40.tv podcast hosted by Kudzai Manditereza. It features conversations with industry leaders, technologists, and practitioners about how AI is built and applied in industrial operations. The show examines architectures and real-world implementations across connectivity, industrial data infrastructure, semantic technologies, data platforms, AI agents, and operational applications. It is aimed at manufacturing engineers, architects, and technology leaders working to turn industrial data and AI into measurable operational impact.
Episodes
Time-Series Data Quality and Reliability for Manufacturing AI: Bert Baeck - Timeseer.AI
Most data-quality initiatives focus on things like freshness or schema. That works for IT data, but not for sensor data. Sensor data is different. It reflects physics. To trust it, you need contextual, physics-aware checks. That means spotting: → Impossible jumps → Flatlines (long quiet periods) → Oscillations → Broken causal patterns (e.g., valve opens → flow should increase) It’s no surprise tha
AI Agents for Industrial Sales and Application Engineers: Fay Goldstein - Co-Founder and CEO, Folio
Industrial teams still rely on fragmented and manual processes to match complex product specs with use-case-specific needs.
Take this example:
You're selling a vision sensor to a factory. To get it right, you need to know:
⇨ What’s the size and speed of the conveyor line?
⇨ Is the plant located in Munich or Arizona?
⇨ Will this sensor withstand that temperature range?
⇨ What PLC is the customer
Real-Time Industrial Process Optimization and Control with AI: Aldo Ferrante- Sorbotics LLC
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Driving Operational Excellence in Manufacturing with Practical AI: Mickey Shaposhnik - Next Plus
Traditional MES platforms were built for a manufacturing world that no longer exists.They assume stable product lines.They assume you have time for lengthy implementations, tolerance for complexity, and operators who can navigate digital forms while running production. But here's the challenge. Today's manufacturing reality is different:⇨ Markets demand the flexibility to shift from 1.5-liter bott
Autonomous AI Agents for Industrial Process Optimization: Bryan DeBois - RoviSys
Can AI agents really make decisions in high-stakes industrial environments? Generative AI agents, on their own, do not have a robust understanding of cause-and-effect for real-world decision-making. However, when combined with Deep Reinforcement Learning, AI agents gain the ability to reason, learn from interaction, and make decisions that solve operational problems in complex, real-world environm
Causal Models and Agentic AI in Manufacturing: Michael Carroll - LNS Research
# AI in Manufacturing Podcast — Episode Show Notes ## Episode Details- **Podcast Name:** AI in Manufacturing Podcast (Industry40.tv)- **Episode Title:** Unlocking Productivity With Casual Models and Agentic AI in Manufacturing- **Host:** Kudzai Manditereza- **Guest:** Michael Carroll- **Guest Title/Role:** Strategic Advisor & Fellow COO Council at LNS Research; Chief Strategy Officer at Trek A
Ep 28 Predictive Analytics in Manufacturing - Maciek Wasiak, CEO Xpanse AI
I invited Maciek Wasiak for a podcast conversation on Predictive Analytics in Manufacturing and he delivered a masterclass.
Maciek is the CEO and Founder of Xpanse AI, a company that develops technology that rapidly accelerates Data Science delivery by replacing manual data science with AI-driven processing
Here's the outline of our conversation:
✅ Xpanse AI
✅ Introduction to Predictive Anal
Ep 42 Data Driven Optimization in Process Industries - Jim Gavigan, President, Industrial Insight
Had the pleasure of hosting Jim Gavigan on my latest podcast episode, where we deep-dived into "Data-Driven Optimization in Process Industries."We discussed leveraging data for efficiency, the challenges of data quality, and choosing between foundational principles and cutting-edge ML algorithms.Jim also highlighted the significance of tools and strategies in this sphere, emphasizing the urgency o
Scaling Industrial Intelligence with I3X Common API: Matthew Parris - GE Appliances
# AI in Manufacturing Podcast — Show Notes## Episode: Scaling Industrial Intelligence with the I3X Common API **Podcast Name:** AI in Manufacturing Podcast (Industry40.tv)**Episode Title:** Scaling Industrial Intelligence with the I3X Common API**Guest Name:** Matthew Parris**Guest Title/Role:** Director of Quality Test Systems, GE Appliances; Leading Contributor to the I3X Specification**Host:**
Context Engineering for Building Reliable Industrial AI Agents: Zach Etier - Flow Software
Podcast Name: AI in Manufacturing Podcast (Industry40.tv)Episode Title: Context Engineering Techniques for Building Reliable Industrial AI AgentsGuest: Zach Etier, VP of Architecture at Flow SoftwareHost: Kudzai Manditereza Episode SummaryThis episode explores context engineering — the discipline of curating and managing the information supplied to AI agents — and why it is the key to building rel
Software Defined Control , UNS and AI-Optimization in Process Industries : Huize Zhang - FreezoneX
Imagine a control system that learns, optimizes in real-time, and integrates seamlessly with both field assets and cloud-native AI platforms. This is the next chapter of industrial process automation.Already implemented at the largest Oil refinery in the world, Software-defined control systems break the traditional link between hardware and logic.This separation allows for dynamic control, central
Real-Time Quality Control Using AI-Powered Visual Inspection : Priyansha Bagaria, PhD - Loopr AI
As manufacturing demands increase, integrating AI-powered visual systems into quality inspection processes becomes increasingly beneficial.While traditional inspection methods have been the cornerstone of quality control in manufacturing, they come with limitations such as subjectivity, fatigue, and scalability challenges.AI-powered visual inspection systems address these issues.Leveraging advance
Vector Databases and Data Structure for Industrial AI Agents : Humza Akhtar, PhD - MongoDB
Modern manufacturing environments generate a staggering amount of data from machines, processes, quality checks, logistics, and inventory. And yet, most of it goes unseen, unused, and unanalyzed.Why?Because the data is too vast, too fast, and too fragmented for any human to handle in real-time.Even the best engineers can’t monitor thousands of variables 24/7.And failing to harness this data has re
Using AI and Digital Twins For Manufacturing Workflow Efficiency: Andrew Scheuermann - Arch Systems
While the promise of AI is immense, many manufacturers find themselves stuck in pilot projects, unable to unlock its full potential.The key lies in addressing foundational challenges and adopting a clear, phased strategy to transform operations.Fundamentally, AI offers manufacturers a pathway to achieving operational excellence by moving through the four stages of analytics maturity: 1️⃣ Descripti
Generative AI Use Cases in Engineering and Manufacturing: Vlad Larichev - Accenture Industry X
While large language models hold immense potential, there's a significant gap between what these tools offer out of the box and what the manufacturing industry needs.Manufacturing presents unique challenges that generic AI solutions often can't effectively address. However, by customizing Generative AI systems to meet industry-specific requirements, this gap can be effectively bridged: - Tailoring
Modernizing Your Industrial Data Architecture for AI Readiness: Jonathan Wise - CESMII
In this episode, I had the pleasure of interviewing Jonathan Wise, Chief Technology Architect at CESMII (Smart Manufacturing Institute).We discussed how you can modernize your industrial data architecture to harness the full potential of AI, enhancing both production efficiency and innovation.Jonathan highlighted three key pillars essential for AI readiness:Data Accessibility - You can’t train AI
Data Modelling and Manufacturing Ontologies for Digital Twins: Erich Barnstedt - Microsoft
Digital transformation in manufacturing fundamentally involves transforming unprocessed data into valuable insights to guide business decisions through automated systems or human intervention.Consequently, implementing a well-thought-out data modelling strategy is key to successful digital transformation as it helps to express the meaning of the data to digital systems.To learn more about Data mod
Open Platform Strategy & Industrial Data Spaces for Industry4.0 - Sandeep Sreekumar - IndustryApps
In the face of a rapidly evolving industrial landscape, agility and innovation have emerged as core drivers of growth. It is essential for manufacturers to adapt swiftly to changes, harnessing new technologies and embracing new processes that fuel their development. But achieving this level of agility and innovation is not without its challenges. So how do organizations successfully navigate these
Time-Series Databases for IIoT [ InfluxDB ] - Brian Gilmore, InfluxData
By nature, industrial facilities consist of physical assets and processes that evolve through time. Therefore, each data point generated by such systems is essentially a snapshot of events at that particular point in time. By extension, this data wants to be stored in a way that reflects the sequential order of events, so that it can be rapidly queried and analysed, among many other reasons. But y
The Seven Core Capabilities of an Industrial Data Platform: David Ariens - The IT/OT Insider.
The industrial data stack was never built for enterprise-wide intelligence. It was built in silos, optimized for local decisions.As a result, it is not designed to support unified, contextualized, and scalable data management across an organization.And that’s why Industrial Data Platforms are essential for scaling digital transformation. To help organizations understand what makes such a platform
Ep 30 Fundamentals of OPC UA Information Modelling - [ Jouni Aro - CTO, Prosys OPC ]
When you look around a factory, you are likely to see objects interacting with other objects. And there are specific things that each object can do.
It, therefore, makes sense that, in order to build autonomously reconfiguring factories, each object needs to be able to describe its capabilities to other objects so that they can interact with no human intervention.
OPC UA Information Modelling
Practical Applications of AI in Manufacturing: Markus Guerster - Founder and CEO, MontblancAI
In this episode, we explore how artificial intelligence is transforming manufacturing from the ground up. We dive into cutting-edge applications and discuss the benefits and challenges AI introduces to the industry.
Here’s a sneak peek at what we cover:
1. Predictive Maintenance for Machinery
AI helps manufacturers predict equipment failures before they happen, reducing downtime and saving costs.
AI Assistants for Advanced Manufacturing Data Analytics: Stefan Suwelack- Co-Founder & CEO, Renumics
Today's manufacturing industry faces significant challenges in managing its data environment.
Vast amounts of unorganized data collected from various sources often become "data swamps," making it difficult to extract meaningful insights and generate value.
This overwhelming complexity hinders decision-making and slows down innovation.
Additionally, the analytics tools currently available are often
Automating Material Handling with AI-Powered Robots: Arshan Poursohi - CEO, Third Wave Automation
In the latest episode of the AI in Manufacturing podcast on Industry 4.0 TV, host Kudzai Manditereza sits down with Ashan Posohi, CEO and co-founder of Third Wave Automation, to explore how AI-powered robots are transforming material handling. The focus is on autonomous forklifts and their impact on productivity, safety, and the future of manufacturing.
Arshan Poursohi brings a rich background in
Agentic AI Framework for Manufacturing Operations: Gilad Langer - Tulip Interfaces
Agentic AI Framework for Manufacturing Operations AI in Manufacturing Podcast Show NotesEpisode Guest: Gilad Langer, Head of Digital Transformation Practice at Tulip Interfaces Host: Kudzai Manditereza Publication Date: [Insert Date] Episode SummaryManufacturing systems are complex adaptive systems that require a fundamentally different approach to AI implementation than traditional monolithic arc
Multi-Agent Based Quality Control in Manufacturing: Wilhelm Klein - Zetamotion
# AI in Manufacturing Podcast — Show Notes ## Episode: How to Reduce Waste and Improve Efficiency with AI-Powered Quality Control **Podcast Name:** AI in Manufacturing Podcast (Industry 4.0 TV)**Episode Title:** How to Reduce Waste and Improve Efficiency with AI-Powered Quality Control**Guest:** Willem Klein, CEO & Co-Founder, Zetamotion**Host:** Kudzai Manditereza**Target Audience:** Manufact
Ep 18: Edge Computing for Industrial IoT - Dominik Pilat & John Kalfayan( Hivecell)
Another year has come and gone, and still, almost every IIoT use case in manufacturing requires some sort of compute capability near the source of the data in order to solve some of the toughest challenges in Manufacturing Digital Transformation.
But yet, the currently dominant model for Industrial IoT is the Cloud-Based Platform-As-A-Service.
The issue is, while Edge Computing architectures do
Reinforcement Learning Agents for Industrial Plant Optimization: Kyrill Schmid - MaibornWolff GmbH
Most industrial processes still run on the same foundation: - Hard-coded logic in PLCs that follows predefined rules. - The intuition of process and plant engineers, built from years of experience. This combination has powered industry for decades, but it has limits. When the challenge involves many interacting variables, unknown relationships, and non-linear effects, traditional control starts to
Transforming Manufacturing Operations with AI on Snowflake: Pugal Janakiraman - Snowflake
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Ep 33 Unified Namespace for Industrial IoT: The Masterclass - [ Walker D Reynolds, 4.0 Solutions ]
Digital transformation of a manufacturing enterprise is a complex process that goes far beyond simply sending data to the cloud and implementing “predictive maintenance”.
It requires a strategic architectural approach that effectively utilizes your data ecosystem to make informed decisions in real-time and drive innovation at every level of your organization.
While there are various architectural
Connectivity for Enabling AI In Manufacturing Use Cases : Prof Dr Bernd Hafenrichter - soffico GmbH,
AI’s success in manufacturing depends on the ability to seamlessly integrate data from machines and systems across the factory floor and supply chain.Without strong connectivity, AI remains underutilized, limited by data silos, and inconsistent integration.Connectivity isn’t just about linking devices; it’s about creating a unified data environment where AI can operate at its full potential—poweri
Standardizing Industrial Data Architecture with ISA-95: Jeroen Janssen - MES/MOM Consultant, Rhize
SA-95 is a standard that’s often misunderstood, but incredibly powerful.
While many think ISA-95 is rigid or overly complex, it actually enables flexibility by:
⇨ 𝐃𝐞𝐟𝐢𝐧𝐢𝐧𝐠 𝐚 𝐬𝐡𝐚𝐫𝐞𝐝 𝐯𝐨𝐜𝐚𝐛𝐮𝐥𝐚𝐫𝐲 for manufacturing concepts, creating a true ontology for your data.
⇨ 𝐂𝐫𝐞𝐚𝐭𝐢𝐧𝐠 𝐬𝐜𝐚𝐥𝐚𝐛𝐥𝐞 𝐩𝐥𝐚𝐜𝐞𝐡𝐨𝐥𝐝𝐞𝐫𝐬 for every type of data, so you can start small and add new use cases later without rebuilding everything
Building a Knowledge Graph Context Layer for Industrial A: Bob van de Kuilen - Director, Thred
Context isn't static.
It's a living layer of knowledge built through problem-solving, conversation, and understanding the complex relationships on the factory floor.
This simple truth is often overlooked in industrial data strategies.
We’ve been conditioned to believe that context can be predefined; baked into standards, taxonomies, and hierarchies.
But in real-world manufacturing, things
Ep 12: Embedded Machine Learning for IIoT - Zin Kyaw ( Senior User Success Engineer, Edge Impulse )
The success of a fully realised Industry4.0 lies in the democratisation of intelligence and the capacity for Industrial "Things" to autonomously act based on the knowledge they have.
Effectively, turning each and every factory into a computer that is made up of modular processes within, in the form of Cyber-Physical systems.
And central to that success, is the ease with which Industrial things l
Ep 29 Manufacturing Execution Systems for Data-Driven Manufacturing - Kevin Jones, CEO Ectobox
Gaining competitive advantage is the main driver of innovation in nature as much as it is in technology. And the manufacturing ecosystem is no different.
In manufacturing, this manifests in the deployment of production automation systems on the shop floor, and enterprise planning systems on the top floor.
But yet, there's a grey area in between that has, for the most part, remained underutilis
Ep 31 Architecting IIoT Solutions Using Unified Namespace - [ David Schultz, G5 Consulting ]
The Unified Namespace has countless advantages over traditional architectural approaches when it comes to IIoT implementation in manufacturing.
Some of these are:
👉 More efficient communication and data sharing between different devices and systems.
👉 Improved scalability due to a unified interface that is consistent across the entire enterprise network.
But how do you go actually go about bui
Industrial Intelligence Solutions with Causal AI : Daniele Gamba - CEO, AISent Srl
For decades, manufacturers have relied on traditional analytics—correlations, trendlines, dashboards—to make operational decisions. But there's a limit:
Correlation ≠ Causation
Just because two variables move together doesn’t mean one causes the other.
This blind spot can lead to poor decisions and surface-level fixes that don’t solve the real issue.
For example, a machine’s temperature spikes of
Transforming Manufacturing Data Into Actions with Agentic AI - Yousef Mohassab, CEO of Facilis.AI
In this episode, I sat down with Yousef Mohassab, CEO of Facilis.ai, to explore how Agentic AI is transforming the manufacturing industry. If you're looking for practical insights on scaling AI and boosting operational efficiency, this is the episode you can't miss!
Here are the key takeaways:
The Shift from Centralized to Agentic AI Manufacturers can no longer afford to rely on centralized data
Building Intelligent Digital Twins with Generative AI : Pieter Van Schalkwyk - CEO, XMPRO
In my latest AI in Manufacturing podcast episode, I had the pleasure of interviewing Peter, CEO of XMPRO where we discussed How to Build Intelligent Digital Twins with Generative AI.
Here are five key takeaways:
1. Digital Twins Are Evolving: What was once just a static data model has now become anticipatory. Digital twins are now being embedded with AI, moving from being reactive (responding to
Ep 27 First Principles : First Principles of Smart Manufacturing - Conrad Levia, CESMII
Whenever you're faced with information overload on any subject matter, as is the case with many manufacturers considering Smart Manufacturing, it's important to take a step back and understand its first principles.
Without which it would be difficult and costly to realise the vision of Smart Manufacturing.
To help bring the First Principles of Smart Manufacturing to light, I invited Conrad Lei
Information Management and AI in Modern Manufacturing: Jeff Knepper - President, Flow Software
Is the Timebase free historian getting an AI-Native DataOps component with Knowledge Graphs capability? You’ll hear it here first.
In the latest episode of the AI in Manufacturing podcast, I sit down with Jeff Knepper, President at Flow Software Inc., to discuss the intersection of Information Management and AI in modern manufacturing, plus the exciting announcement of Timebase Atlas launch.
Her
Ep 39 DataOps for Digital Transformation In Manufacturing - [ Aron Semle, CTO Highbyte]
DataOps for Digital Transformation In Manufacturing. In this episode, Kudzai Manditereza interviews Aron Semle, the CTO of Highbyte. HighByte is an industrial software company founded in 2018 with headquarters in Portland, Maine USA. The company builds solutions that address the data architecture and integration challenges created by Industry 4.0. HighByte Intelligence Hub, the company’s award-win
Superintelligence for Oil, Gas and Petrochemicals: Callum Adamson - Co-Founder and CEO, Orbital
The first foundation model purpose-built for refining and petrochemicals?
Here's the thing.
The oil, gas, and petrochemical industry is under pressure like never before.
⇨ Demand is set to double in 15 years
⇨ Facilities are shutting down
⇨ Energy transition is colliding with operational cost realities
At the same time, companies are being told AI will solve it all.
But here’s the truth.
Mos
Ep 32 Low Foot Print OPC UA Over TSN for Real-Time Communication - [ Melvin Francis, Be Services ]
In this latest episode, I explore the capabilities of OPC UA PubSub and how it can be integrated with Time Sensitive Networking (TSN) to standardize industrial field-level data transfer.
I speak with Melvin Francis, the Project Manager for OPC UA and TSN-related services at BE.services GmbH, to discuss the challenges faced in developing related applications due to the lack of ready-made OPC UA + T
Visual Intelligence Applications in Manufacturing: Cyrus Shaoul - CEO, Leela AI
In our latest podcast episode, I had the pleasure of speaking with Cyrus Shaoul, CEO of Leela AI, about visual intelligence and its transformative impact on manufacturing operations.
Here are some Key Takeaways:
1️⃣ Beyond Traditional Machine Vision
Unlike traditional machine vision systems that focus on product inspection, visual intelligence looks at the entire manufacturing process. It h
Ep 38 LoRaWAN for Industrial IoT Applications - [ Wienke Giezeman, The Things Industries]
As companies with industrial operations struggle to economically access data from intelligent devices located in remote and challenging environments, LoRaWAN presents itself as a cost-effective solution.
With the capacity to locally integrate industrial data and transfer it via a private LoRaWAN network over vast distances, LoRaWAN simplifies protocol conversion and enhances data recovery.
To lear
Ep 04: A Practical Guide to IIoT Connectivity - Stan Schneider ( CEO, Real-Time Innovations )
While the connectivity of industrial systems is the most important aspect of IIoT, there is currently a confusing mix of connectivity technologies and standards.
To understand IIoT Connectivity I had a conversation with Stan Schneider, who specialises in innovation where pervasive networking meets functional AI
Stan is CEO of Real-Time Innovations (RTI), the world’s largest software framework pr
Industrial AI Co-Pilot for Frontline Operations: Mason Glidden - Chief Product Officer, Tulip
Frontline workers are the backbone of manufacturing, but they’re often held back by manual data entry, process inefficiencies, and knowledge gaps.
AI-powered Industrial Copilots offer a solution that elevates their capabilities:
𝐍𝐨 𝐌𝐨𝐫𝐞 𝐌𝐚𝐧𝐮𝐚𝐥 𝐃𝐚𝐭𝐚 𝐄𝐧𝐭𝐫𝐲
AI Copilots automate data capture and seamlessly integrate with existing systems—eliminating wasted time and inaccuracies.
𝐒𝐦𝐚𝐫𝐭𝐞𝐫, 𝐅𝐚𝐬𝐭𝐞𝐫 𝐖𝐨
Ep 25 : Containerisation for Industrial IoT - Neil Cresswell (CEO, Co-Founder - Portainer) )
Here's the thing. Containerisation is not only an IT technology, it is an advanced IT technology. And yet, it already looms on the horizon for Operations Technology.
And, while the technology opens up massive opportunities for optimisation and efficiency in the OT network, it demands a fundamental rethink of industrial software distribution and management.
To find out what this actually means
Maximize OEE & Production Line Safety with Video AI Agents : Karim Saleh - Co-founder & CEO, Cerrion
Manufacturers are constantly battling two critical challenges:
Inefficiencies in Equipment Usage: Downtime, slow cycle times, and unidentified bottlenecks reduce Overall Equipment Effectiveness (OEE), leading to wasted resources and missed production targets.
Safety Risks: Ensuring worker safety while maintaining productivity is difficult, especially in environments with heavy machinery and fast-m
Ep 43 Infrastructure as Code for Industrial IoT - [ Peter Sorowka, CEO Cybus GmbH]
Peter Sorowka is a recognized expert in Industrial IoT and the technical architecture of data-driven industrial production. In 2015, he founded Cybus - a software company specializing in secure and governance-strong IIoT Edge and Smart Factory solutions.
As CEO of Cybus, he has been advising and guiding global enterprises towards decentralized, secure Smart Factory and data-driven Smart Services a
Ep 02 : Principles of IIoT Architecture - Rick Bullota (Co-Founder, Thingworx)
Having a solid understanding of the key components of an IIoT architecture and how to integrate them is the most important aspect of building an IIoT application, both as an in-house solution and as a service offering
So, to help shed light on the principles of IIoT architecture design, I had a discussion with one person who is best positioned to speak on the subject, Rick Bullotta
Rick Co-Found
CDOT AI Code - A New Language for Parts: Serra Tuzcuoglu CEO and Co Founder, Cosmodot - CDOT AI Code
Part traceability in manufacturing has long relied on traditional barcodes that fail where it matters most: under heat, blasting, and coating, e.t.c.
As a result, manufacturers normally place barcodes after key part transformations.
That means, for 70%+ of the production process, you're flying blind. You're guessing which parts went through which treatments.
And when something fails? You're
Ep 03: Fundamentals of Edge Computing - Rob Tiffany ( VP & Head of IoT STrategy - Ericsson )
The success of IIoT in mission-critical applications depends on its ability to support local storage, compute, and connectivity for real-time responses, while sending selected data to the cloud for additional analytics. In short, Edge Computing
To gain a comprehensive understanding of Edge Computing, I sat down with somebody whose day job is strategising and executing at the intersection of 5G, E
Ep 05: Advanced Plant-Floor Data Analytics - Marcos Taccolini ( Founder and CTO, Tatsoft )
Cliché as it may sound, data IS the new Oil. But, to fully reap the benefits, data needs to be properly collected and advanced analytics correctly applied to it.
To better understand the process, I had a conversation with one person who has close to 3 decades of building industrial data aggregation and advanced visualisation tools, Marcos Taccolini.
Marc is currently the Founder and CTO of Tatso
Ep 34 Node-Red for IIoT in the Enterprise - [ Nick O’Leary, CTO Flowforge Inc ]
The Node-Red project turns ten this year.🎉
And yet, its remarkable potential remains largely untapped in the industrial software domain.
Having been a Node-Red user and promoter since its early days, I've observed that its preparedness for enterprise deployments is a key challenge limiting its broader adoption.
To discover the most effective strategies for deploying and managing enterprise-grade N
Ep 01 : The Ultimate Guide to Digital Twins - Pieter van Schalkwyk (CEO, XMPRO)
Digital Twins will, undoubtedly, transform how manufacturers build and maintain products. From consumer goods to complex structures such as buildings and aircraft.
But as of now, confusion and lack of its grasp are limiting adoption.
To understand the technology better, I had a conversation with Pieter van Schalkwyk, whose company has helped Fortune 10 companies build Digital Twins.
Here's what
Ep 06: Foundations of Industrial IoT Data Architecture - John Harrington ( Co-Founder, HighByte )
So here's the thing, data from industrial sources is inherently messy. For example, a typical PLC system manages thousands of tags from both physical instruments and internal calculations, but this data is often unstructured, not linked to a unifying data model, and uses naming conventions that are vague to the outside world.
This makes data from such sources not readily usable in analytics appli
AI Copilots for Manufacturing Assembly Optimization: Zeeshan Zia - Co-Founder & CEO, Retrocausal
In our latest episode of the AI in Manufacturing Podcast, I sat down with Zeeshan Zia, co-founder and CEO of Retrocausal, to dive deep into how AI co-pilots are transforming the manufacturing sector. Here are three key takeaways:
1️⃣ Labor Challenges Meet Smart Solutions
Manufacturers face critical labor shortages, resulting in significant costs. Zeeshan shared how AI-powered Assembly Co-Pilots a
Data-Driven Manufacturing Optimization with AI: Zhitao Gao - CEO and Co-Founder of eXlens.ai
Many factories today grapple with recurring production issues and inefficiencies; whether it’s inconsistent quality, unpredictable downtime, or process bottlenecks.
The cost of inefficiencies keeps mounting, and while human intuition and manual checks have been valuable tools, they’re no longer enough to drive significant breakthroughs.
AI offers an opportunity to uncover hidden patterns that hu
Ep 41 Applied AI in Manufacturing - [ Roey Mechrez, Head of AI, and EMEA MD @Tulip]
By now, we're all aware of the profound impact Generative AI promises for manufacturing. Beyond just assisting engineers in application development, it equips managers with cutting-edge analytics and delivers invaluable error resolution insights to technicians, etc. - all through intuitive interactions.
That's why I'm excited about Tulip Interfaces' new "Frontline Copilot" which uses LLMs for natu
Ep 11: Global Industry Standards for Industrial IoT - Claude Baudoin ( cébé, OMG, IIC, Cutter )
As Industrial IoT matures, most of the components in the IIoT stack have become commoditised. Things like hardware, OSes, drivers, protocols, databases e.t.c
But yet, many organisations still develop custom interfaces for these components, instead of adopting standards. And in cases where there is adoption, there lacks an industry-wide consistent approach to standardisation.
To understand the im
AI Agents for Advanced Time Series Data Analytics : Jeff Tao - CEO and Founder, TDengine
In manufacturing, time-series data is everywhere, but most plants are still relying on static dashboards, lagging insights, and manual root-cause analysis.
The result?
- Downtime that’s explained, not prevented
- Insights that arrive, after the line slows down
- Human effort wasted on repeat investigations
AI agents transform the way manufacturers harness time-series data.
They process live se
Ep 08: Technical Foundations of IoT - Dominik Obermaier ( Co-Founder & CTO, HiveMQ )
While it may be convenient to follow simple steps to get connectivity working for your IIoT solution, sometimes you are better off having an understanding of the elements that make up the broad spectrum of connectivity technologies.
To understand the foundations upon which IoT protocols are built, I had a conversation with Dominik Obermaier. Dominik is the Co-Founder & CTO of HiveMQ, a compan
Ep 35 Human-Machine Collaboration for Smart Manufacturing - [ Rafael Amaral - Tillit ]
In smart manufacturing, effective data collection and analysis are crucial. But to truly succeed, it's essential to integrate the coordination of personnel, equipment, and materials into the process.
For the factory worker, this would typically be through a series of digital nudges that guide their decision-making throughout the day, enabling them to work in harmony with smart machines for optim
AI Powered Smart-Guidance for Smart Manufacturing: Nikunj Mehta - Founder & CEO, Falkonry
In this episode, we dive deep into the world of smart manufacturing with industry expert Nikunj Mehta from Falkonry. If you're curious about how data is transforming industrial operations and the future of maintenance and reliability, this episode is for you!
Here are some key takeaways:
82% of Failures Are Random
Nikunj explains that a staggering 82% of failures in industrial systems appear rand
AutomationML, OPC UA & Asset Administration Shell for - Dr. Miriam Schleipen , EKS InTec GmbH
The biggest challenge in the transition to Industry4.0 lies in the horizontal and vertical integration of information flow within and across manufacturing organisations, and the digitalisation of the engineering processes involved. Among the technologies and standards developed to enable this flow of information, is the compelling combination of AutomationML, OPC UA, and the Asset Administration
Open Source Software for Industrial IoT - Frédéric Desbiens Program Manager , Eclipse
At the present moment, it is quite clear that the future of industrial automation will be driven by software. More so, that of IIoT. And, due to the merits that have allowed it to dominate in the IT space, Open Source software is likely to lead the industrial software revolution. Regardless of the conservative nature of the industry. To discuss the use of Open Source in building IIoT solutions, I
Designing Multi-Agent Systems for Industrial Operations: Kence Anderson - Founder & CEO, AMESA
# AI in Manufacturing Podcast ## Episode: Designing Autonomous AI Agents for Industrial Operations **Podcast Name:** AI in Manufacturing Podcast (Industry 40.tv)**Episode Title:** Designing Autonomous AI Agents for Industrial Operations**Guest:** Kence Anderson, CEO & Founder, AMESA**Host:** Kudzai Manditereza --- ## Episode Summary This episode explores how autonomous AI agents can transform
Optimizing AI Inferencing for Agentic Operations in Manufacturing: Calvin Cooper - Neurometric AI
# AI in Manufacturing Podcast: Episode Show Notes ## Episode: Optimizing AI Inference for Agentic Operations in Manufacturing **Podcast Name:** AI in Manufacturing Podcast (Industry40.tv)**Episode Title:** Optimizing AI Inference for Agentic Operations in Manufacturing**Guest:** Kelvin Cooper, Co-Founder & CEO, Neurometric.ai**Host:** Kudzai Manditereza--- ## 1. Episode Summary This episode ex
How to Build AI Solutions That Actually Work on the Factory Floor: Renan Devillieres - OSS Ventures
**Podcast Name:** AI in Manufacturing Podcast **Episode Title:** How to Build AI Solutions That Actually Work on the Factory Floor**Guest:** Renan De Villiers, Founder & CEO, OSS Ventures**Host:** Kudzai Manditereza --- ## 1. Episode Summary This episode explores why only 5% of factories currently operate like tech companies — and what it will take to reach 50% within a decade. Renan De Villi
A Guide to Implementing AI Agents in Factories: James Zhang - Co-Founder & CPO , OpsMate AI
Episode Title:** Practical Guidance for Implementing Industrial AI Agents in Manufacturing Guest:** James Zheng, Co-Founder & Chief Product Officer, Optimate AI Host:** Kudzai Manditereza---## 1. Episode SummaryThis episode explores how agentic AI is creating a new category of digital skilled workers for manufacturing, addressing the industry's deepening productivity plateau and skilled labor
Scaling Agentic AI Workflows in Manufacturing with Causal AI: Bernhard Kratzwald - EthonAI
## Episode: Building and Scaling Agentic AI Workflows in Manufacturing **Podcast Name:** AI in Manufacturing Podcast **Episode Title:** How to Build and Scale Agentic AI Workflows in Manufacturing**Guest:** Bernard Kraswald, Co-Founder & CTO at Ethon AI**Host:** Kudzai Manditereza--- ## Episode Summary This episode explores how manufacturers can build and scale agentic AI workflows to achieve
Unified Namespace is The Essential Foundation for Industrial AI: Walker Reynolds - 4.0 Solutions
## Episode: The State of Industrial AI, Unified Namespace, and Knowledge Graphs After PROVE IT 2025 **Podcast Name:** AI in Manufacturing Podcast **Guest:** Walker Reynolds, President & Solutions Architect at 4.0 Solutions, Founder of the PROVE IT Conference**Host:** Kudzai Manditereza**Target Audience:** Manufacturing data leaders, IT/OT solution architects, and digital transformation profess
Building a Data Foundation for AI-Native Industrial Intelligence: Craig Scott - Founder & CEO , Fuuz
1. EPISODE SUMMARYThis episode explores why most manufacturing AI initiatives fail and what companies must do to build a foundation for AI-native industrial intelligence. Craig Scott, Founder and CEO of Fuuz, an industrial intelligence platform, shares insights from nearly a decade of bridging the gap between shop floor data and enterprise systems. The conversation reveals why the missing "shim" b
Ep 09: Industrial Internet of Things (IoT) 101 - Benson Hougland VP of Product Strategy, Opto22
Nowadays, with so many IIoT concepts in the air, you can't help but breathe it in. But sometimes it's helpful to take a step back and put all of this in context to understand how we got here, as that might help shed light on what IIoT is and isn't about. To gain a fundamental understanding of OT-IT integration, I had a conversation with Benson Hougland. Benson is VP of Product Strategy at Opto 22,
Building Effective Data and AI Innovation Teams in Manufacturing: Van Tucker - Harbor Lockers.
What really makes data and AI innovation teams succeed in manufacturing? In this episode of the AI in Manufacturing Podcast, I speak with Van Tucker, VP of Harbor Lockers by Luxer One, a company that develops and manufactures smart public lockers. We discuss the challenges and strategies for building effective innovation teams in manufacturing. Here are some of the insights that Van shared: 𝐂𝐮𝐥𝐭𝐮
Edge AI in the Digitalization of Industrial Process: Rainer Maidel -BE.Services
Instead of sending data to the cloud for processing, Edge AI analyzes data right where it’s generated, on the machine, in the plant, in real time. It’s the difference between reacting later and responding now. What Happens When You Keep Intelligence at the Source? 𝐑𝐞𝐚𝐥-𝐭𝐢𝐦𝐞 𝐃𝐞𝐜𝐢𝐬𝐢𝐨𝐧𝐬 A conveyor motor vibrates abnormally. Edge AI detects the anomaly instantly and slows the line before damage occurs
Edge AI Architecture For Integrating Into Control Systems: Ander Garcia Gangoiti - Vicomtech
Many small and mid-sized manufacturers want to explore AI to improve efficiency, reduce waste, or make their processes smarter. However, this process requires OT and IT knowledge not present in manyindustrial companies, mainly SMEs. Ander Garcia Gangoiti and his team built a micro-service edge architecture based on MQTT, TimescaleDB, Node-Red and Grafana stack to ease the integration of soft AI mo
Scaling AI-Driven Transformation in Manufacturing: Jonathan Alexander - Albemarle Corporation
Learn how Jonathan and his team at Albemarle Corp went from pilots to $150M in annual improvements through a business-first, scalable AI strategy. In the latest episode of the AI in Manufacturing podcast, I spoke with Jonathan Alexander, Global Manufacturing AI and Advanced Analytics Manager at Albemarle Corporation, about building, scaling and sustaining AI-driven Transformation in Manufacturing.
