As manufacturers accelerate their use of artificial intelligence to optimize production, improve quality, and predict maintenance, the cybersecurity stakes have never been higher. This episode explores how AI is reshaping the industrial control system (ICS) landscape — creating both powerful new defense tools and complex new vulnerabilities.
Our panel of experts dives into how standards like ISA/IEC 62443, NIST CSF 2.0, and MESA’s Smart Manufacturing Model are evolving to address AI-driven risk. We’ll discuss practical steps for securing connected plants, protecting data integrity, and maintaining trust in AI-assisted automation.
Listeners will learn:
How AI is expanding the ICS attack surface — and how it can also strengthen defenses
The role of governance, standards, and data integrity in an AI-enabled OT environment
Real-world insights on zero trust, digital twins for cybersecurity, and the convergence of IT/OT security
Join MESA’s host and subject-matter experts as they examine what it takes to build secure, intelligent, and resilient manufacturing systems in the age of AI.
As we gear up for the upcoming Smart Manufacturing Now 2025 event, I have had the privilege of moderating a special podcast with MESA members who have been at the forefront of applying AI in manufacturing.
This isn’t just about the hype — it’s about real stories from the plant floor:
This podcast is your sneak peek into the kinds of insights, stories, and forward-looking discussions you can expect at Smart Manufacturing Now.
Give us a listen and don’t miss the event — join the conversation shaping the future of manufacturing.
#SmartManufacturingNow #MESA #SmartManufacturing #AI
A special MESA Knows podcast episode previewing what’s coming at Smart Manufacturing Now! Our third year conducting this important virtual event, Hear what to expect from the event, who’s speaking, and why this is the gathering for manufacturing leaders driving digital transformation. Don’t miss the insights, energy, and opportunities coming your way. https://mesa.org/smart-manufacturing-now/
In this episode, we dive into the critical role of data integrity by design in enabling the future of smart manufacturing in the life sciences industry. As Pharma 4.0 initiatives gain traction, leading organizations are shifting from reactive compliance to proactive data governance strategies that embed quality, traceability, and trust directly into their digital systems.
Our expert guests will explore how companies are operationalizing ALCOA+ principles—ensuring data is Attributable, Legible, Contemporaneous, Original, Accurate, and more—and aligning with the FAIR principles (Findable, Accessible, Interoperable, Reusable) to future-proof their digital infrastructure. We'll discuss real-world strategiesfor building data integrity into system design, enabling seamless regulatory readiness and supporting the ethical, effective deployment of AI in regulated environments.
Whether you're a digital transformation leader, a quality professional, or an AI innovator in life sciences, this episode will offer insights into how your organization can design for trust—right from the start.
In this episode, we sit down with manufacturers and supply chain experts to explore how today’svolatile trade environment is forcing a strategic rethink across the industry. From shifting sourcing decisions and rising costs to accelerating reshoring and digital investments, we unpack how tariffs and uncertainty are no longer just a policy issue — they’re an operational reality. I am joined by several members of our Knowledge Committee as well as special guest Robert Cohen, Senior Fellow at the Economic Strategy Institute. Our guests share real-world stories of how they’re adapting:
We also dig into the role of predictive analytics, supply chain visibility, and policy advocacy —and what forward-looking manufacturers are doing now to prepare for what’s next. Whether you're navigating sourcing headaches, retooling your production strategy, or trying to future-proof your business model, this episode delivers insight you won’t want to miss.
What’s really driving success with analytics and AI in manufacturing? In this episode, we dive into the latest industry survey results with Julie Fraser of Tech-Clarity to uncover what’s working, what’s not, and what leading manufacturers are doing differently. Don’t miss this data-driven conversation that puts real-world insight behind the buzz. This full survey report is available from MESA. It represents the next installment in the biennial survey that MESA has been creating for 2 decades now. There is a wealth to learn from our history of these surveys, from both current state as well as the trends that we can observe through the 21st century.
Following on the heels of a great community discussion, I have Joanne Friedmann and Khris Kammer discuss the elevation of data to the forefront of IT/OT architecture. Embedded in that is a thinking about the value of data and how it be measured, your Return on Data. Smart manufacturing and the MESA model place data at the foundation of any effective architecture. There is a significant shift in IT/OT where data is becoming the core driver of architecture decisions, rather than just an afterthought. Traditional IT/OT architectures were built around applications, with data being managed as a byproduct. Now, data-first architectures ensure that storage, processing, and movement of data are optimized for real-time decision-making, analytics, and AI-driven automation. AI and machine learning models thrive on high-quality, well-structured data. Data must be easily accessible across different systems (ERP, MES, SCADA, etc.). Organizations are implementing unified data governance frameworks to ensure consistency, security, and compliance. Modern architectures use event-driven models to react in real-time, which is critical for smart manufacturing and predictive maintenance. Manufacturing execution system (MES) platforms will evolve to be data-first, prioritizing real-time analytics. AI-driven decision-making will require IT systems to be built around data streams, not just applications. Data interoperability between legacy and modern systems will be crucial.
The pace of technology change in manufacturing can be dizzying. Some of our listeners to this podcast have asked us to take a step back from some of our deeper investigative topics and simply review the current state of technologies applied to analytics in smart manufacturing. We call this episode "Back to the Basics". I am joined by an all-star group of MESA experts to define what is artificial intelligence and machine learning and how they are being applied across all facets of manufacturing.
How is Artificial Intelligence Changing Industrial Analytics?
From the Smart Manufacturing Now event and a tumultuous year of technology change, it's clear that AI will have a significant impact on industrial operations. But how will we measure performance, quality and safety going forward? Is there continuity between operational analytics before AI and today, so that we can understand the impact. The Knowledge committee extends this discussion in this PodCast.
The practice of MRO (Maintenance, Repair, and Operations) has been with us as long as the first industrial revolution and today is as critical as ever. But Smart Manufacturing has had major impacts on MRO. Our group has assembled to discuss the impact of Smart Manufacturing on MRO. Smart Manufacturing technologies and operations enable more accurate predictive maintenance, better tracking of equipment conditions, and more efficient planning of maintenance activities, leading to further improvements in operational efficiency and cost savings.
The large language model (think Chat GPT) made quite a splash at the end of 2023. This class of technologies can be applied to many real-world challenges that face industrial enterprises. But what problems are practical to be solved today by the application of LLM technology? The MESA Analytics Working Group discusses the challenges and opportunities that LLM bring to manufacturing. Join us, its a great discussion filled with possibilities for a promising new technology.
The digital twin may be the ultimate expression of digital transformation. The concept of a Digital Twin has evolved and expanded over the years, but at its core, it generally refers to a virtual representation of a physical asset or process that can accurately represent and simulate its equivalent physical asset or process. Digital twins in manufacturing have been gaining momentum and are increasingly considered valuable tools. However, whether they are "ready for prime time" depends on the specific industry, use case, and the maturity of the digital twin implementation. The MESA analytics working group has assembled an all-star group with the experience to discuss this from several dimensions. Come have a listen and join the conversation!
Knowing where you are on your digital transformation journey is the key to setting goals and identifying and celebrating the wins. But is it healthy to obsess about this score? And whats behind this single number that is expected to define your level of readiness? And compared to whom? In this episode the analytics working group from MESA International will try to unpack all this and get to the root of the value of a digital maturity assessment.
Why do 87% of data science projects fail?
Non-Availability of Quality Data ....
The data is usually raw and may contain many missing or absurd values. In such cases, it sometimes becomes impossible to make the given dataset into a model-friendly dataset. Thus, if the data quality is not good enough, the data science project will likely fail.
What is the anecdote? ... Data Governance.
But the truth is that data governance is a big challenge for each enterprise. According to a Gartner survey, over 90% of data governance projects fail to perform well.
The MESA Analytics Working Group explores what good data governance could be and how it can reasonably be achieved.
The concept of a "manufacturing metaverse" is still in its early stages; however, its potential impact to uncover real-world business value can be observed and measured today.
The MESA Analytics WG Podcast team debates and cuts back to the core of what we can expect today and what we can speculate for the future of a more immersive, integrated cyber-physical manufacturing world.
Chris Monchinski is joined by John Jackiw, Dennis Brandl, Larry White and Steve Hewitt to discuss.
How will industry jobs be affected by the increasing application and integration of analytics. With all the buzz around new technologies in AI/ML, ChatGPT, etc. this topic is “ever” relevant.
Everyone is speculating and considering what this impact will be (some interesting links below)
https://www.whitehouse.gov/wp-content/uploads/2022/12/TTC-EC-CEA-AI-Report-12052022-1.pdf
https://www.wsj.com/articles/how-ai-change-workplace-af2162ee?mod=Searchresults_pos4&page=1
https://www2.deloitte.com/us/en/insights/focus/technology-and-the-future-of-work.html
In fact, what does Chat GPT think....
The increasing application and integration of analytics in manufacturing will have a significant impact on manufacturing jobs. Here are some ways in which manufacturing jobs may be affected:
It is important to note that while some manufacturing jobs may be affected or replaced by automation and analytics, new job opportunities will also emerge as companies adapt to these technologies. Workers with the ability to embrace and leverage analytics, as well as those involved in designing, implementing, and maintaining the analytics systems themselves, will likely find new avenues for employment in the evolving manufacturing landscape.
Zero-trust security is an approach to cybersecurity that assumes no user or device should be trusted by default, even if they are within the network perimeter. Instead, access to resources and data is strictly controlled and continuously verified, regardless of location or device. This has several implications for data analytics in zero-trust security environments. The members of the MESA Analytics Matter Working Group will discuss the implications of the need for more data in the face of greater security and constraints on data access. Stephen Jackiw joins us with his perspective from the cyber-security world.
ChatGPT, the Chat Generative Pre-trained Transformer, is all the rage. Speculation abounds on the technologies applications and who might be de-careered because of it. The analytics working group at MESA has an informative discussion on what ChatGPT is today and how technology like ChatGPT may be applied across manufacturing, especially when challenged with synthesizing massive amounts of industrial data. As a natural language user interface, tools like ChatGPT may help enable collaborative knowledge management systems and interactive, prescriptive analytics.
In the Smart Manufacturing arena, the concept of Cyber-Physical is not new. We have many examples of the interaction between the digital and physical space including connected works and co-bots. Now we have the "Metaverse"... but what does this mean for industrial digital transformation and how is this different from the concept of digital twin.
Gartner, the Tech world, and various bloggers define the Metaverse as something, at best, not ready for prime time, and at worst, a dystopian, evil concept that will do more harm than good. We beg to differ. One interpretation or adoption of the concept –the Industrial Metaverse—is being implemented today, and can add tremendous value to businesses struggling to make sense of a siloed, complex world. It brings together the various models we have today, and can help unify them in a way that improves safety, efficiency, regulatory compliance and environmental sustainability.
The analytics working group is joined by Cheryl Wiebe of Visionaize.ai to discuss the Industrial Metaverse and why it matters to MESA.
Original Air Date [June 22, 2022]
In data analytics better than half the time in the project effort may be spent on data acquisition and preparation. Capturing meaningful and accurate manufacturing metrics for driving data analytics can be very difficult. But when there is a high level of uncertainty about a measurement, we need to consider how much accuracy we truly need to obtain meaningful insights from our analytics. The true goal of any measurement is not perfection but to reduce uncertainty.
The podcast crew of the MESA Analytics Working Group is joined by guest Kip R. Krumwiede to discuss how to approach measurements that provide what we need to satisfy our analytic end goals.