Industry accelerates its journey to Industrial Autonomy

Tom Fiske: Thank you. It's pleasure to be here.

Larson: I alluded to the business environment late, which is been anything but business as usual, in addition to the COVID pandemic. How are manufacturing companies being impacted by some of these these big trends the last couple of years?

Fiske: Yeah, well, as you mentioned, the business environment is one of the most challenging we've seen in recent years. The economy has been contracting and inflation is rising, global tensions increasing, and it's affecting everyone in all regions of the world, from producers to consumers. For the producers, though, it's not just affecting their production sites, but it's also having an adverse effect on a company's supply chain. So, we see the long lead times for getting raw materials, difficulties in keeping production and operations running, disruptions to shipping of finished goods, and companies are dealing with soaring energy costs, and they're also dealing with retaining workers and attracting new qualified workers. And then, you know, on top of all of that, they must deal with the new reality of the pandemic, the distributed and remote workforce. So, you know, in the face of that global geopolitical risks, economic shocks, and supply chain disruptions, and all of those other uncertainties, companies got to really begin to focus on their operations and making them more resilient through these challenging times, and to position themselves for long-term growth. And, you know, that's going to be difficult, requires better management, people, processes, assets, information.

Now, the one good thing is, fortunately, over the last couple of years, there's been a plethora of innovations that have occurred, that companies begin to exploit and accelerate their digital transformation. And so, we're starting to see this journey, and it's evolving into that what we call the IA2IA, the Industrial Automation to Industrial Autonomy, where companies are beginning to incorporate more autonomous functionality into their operations. But you know, it's, it's funny, because at the beginning of this year, we did a study, a survey on industrial automation, and the survey had about 500 C-level executives, from all different industries, across all different regions. And the intent there was to study the impact of IA2IA and the levels of deployment, the readiness of technology's impact on the workforce, and also look at the one of the biggest challenges in digital transformation and moving to Industrial Autonomy. The results showed that the adoption of Industrial Autonomy is increasing, especially from the last survey that we did.

And we found that about 50% of the respondents indicated that they're already deploying some form of Industrial Autonomy. Now, granted, it might be, you know, focused on a single application or single purpose, but that they're already implementing Industrial Autonomy, and they're looking to expand that application across their organization.

Larson: Interesting.

Fiske: And, yeah, it's very interesting. Yokogawa has done a project, a first of its kind, that supports companies on their journey towards autonomous operations, which were used AI to autonomously control a chemical plant for 35 consecutive days. That's never been done before.

Larson: Yeah, that's impressive if it takes even model based controllers, in the old sense, didn't didn't last that long, totally, totally autonomously, that's for sure.

Fiske: Sure, you'd have people shutting them off and they didn't they were properly functioning.

Larson: Then you had to maintain those models, and constantly tweak them to align with reality again, so yeah, that was the situation until not long ago. So, congratulations on that.

Do you see that sort of those those algorithms being more widely implemented? I mean, where do you see this this going? I mean that's a huge jump forward, that could pretty rapidly transform a lot of things.

Fiske: Absolutely, yeah. So, we see the need for Industrial Autonomy in all industry sectors. Some industry sectors, like the oil and gas, for instance, they're looking to operate with minimally manned staff, in some instances are trying to achieve unattended operations for extended periods. And other industries are looking to make their workers more productive, and supplement in an augmented decision making and replace some of their routine tasks. So, you know, we think applications like that AI control and other autonomous functionality will become the norm as we progress in these challenging times.

Larson: You mentioned, really the next step for a lot of companies is scale, going beyond individual pieces of equipment to more enterprise level and fleets of assets. What particular challenges does that represent, from your perspective, when you start rolling this out across, you know, companies with hundreds of manufacturing sites?

Fiske: Yeah, they're basically a couple of fundamental challenges that companies must overcome to expand the scope of Industrial Autonomy, and one is the data and application integration. And that's because data and AI are fundamental building blocks for Industrial Autonomy. And, you know, it's a challenge, because typically, operation technology and information technology are operated and owned by different groups within a company, but we are seeing this convergence of IT and OT, and so OT data can be analyzed with IT techniques and and then pass back to OT, and they can use the results to improve efficiency and optimize operations. Now, you know, this typically requires analyzing, and interpreting enormous amounts of data. And to achieve those results to optimize facilities requires a lot of specialized skills in data science, operational technology, IT, domain expertise, as well as a lot of experience in that area. And, you know, there were other host of challenges as well. Some of them are related to processes and workflows, many companies are still operating in silos, and their departments, or they create borders around the departments, and so workflow between them and exchange of information is still challenging. So, that goes again to the integration and the integration of workflows to optimize operations across different departments and extended into the supply chain. And then there's the people aspect to it as well. You know, I mentioned earlier that some companies are focused more on worker productivity and worker enablement. And so, they're looking at this as a way to capture their knowledge and upskill their abilities, and to to help them make better decisions by providing them with some real-time information. And then to move it to into the autonomous stage where it can relieve the staff of some of the more challenging or mundane type of operations.

Larson: Yeah, we kind of use the seems that term integrated operations has emerged to be almost a twin sister to Industrial Autonomy. Can you explain a little bit more what integrated operations are relative to Industrial Autonomy? And how those complement each other?

Fiske: Sure, so integrated operations is more about bringing together the data and the applications as well as multidisciplinary teams. And so you can co-locate those teams, and that enhances collaboration, analyzing problems, and so they can function and work together. It breaks down silos, it provides greater situational awareness. They can collaborate to monitor equipment and resolve and troubleshoot issues and the facilities.

Larson: So it's not just a technology thing. It's a team team building exercise as well.

Fiske: Absolutely. And you know, so Industrial Autonomy supports that through the autonomous functionality of possibly analyzing a lot of data, monitoring the process monitoring equipment, and in some instances, it can take mitigating actions if something goes wrong. So, if there's an equipment failure, like a pump, then it can identify what needs to be done. If there's an exhilarate pump, it may shut down that pump and divert the flow to the auxilary pump. Or if it's an impending fault, it detects a fault in a few weeks or so, then it can trigger autonomous workflows to have a workaround for operations, as well as schedule of maintenance and even set up meetings for companies to collaborate with subject matter experts either internally or externally.

Larson: So, if we truly achieve this vision of end-to-end integration, what kind of benefits are we looking at? And is autonomy one step beyond that? Or how do you view that?

Fiske: Well, it's a tough a tough question. I think the benefits are going to be significant, because integrated operations provides a consistent view of operations from the plant floor to the boardroom. So, you know, one person's role or responsibility was to find that view. But it needs to be consistent with everybody else's. And, you know, integrated operations, you know, let's say, typically, will take a multidisciplinary approach. But now they're, they're armed with all of this real-time data and information that not only is telling them what's happening, but it's predicting what's going to happen. And if you already can anticipate and know the outcome, then you can make better decisions to optimize operations. So, and this goes across the entire operations of an organization. It's not just based on production, but it truly is a multidisciplinary aspect. So, it brings in elements of operations engineering and maintenance and supply chain. So, the benefits are going to be significant. It's going to be a step change in performance.

Larson: All those traditional silos we're used to protecting and maintaining across the organization are gonna get flattened or put sideways in a lot of cases, it seems.

Fiske: Yeah, it will. And so, you know, I know some companies are struggling as to how do they get going? Where do they start? And, you know, I consult with a lot of customers, and each customer is unique, and they have different capabilities, they have different resources available to them. They have different strengths, weaknesses, different objectives. And so, the path for each one needs to be tailored to their unique situation. But once they determine that path, then they really should establish a standard that they're going to use across their enterprise. And so, this integrated operations approach, utilizing Industrial Autonomy is built on a foundation of strong automation, AI, a common information model. And the solution really encompasses people, processes and technology, leveraging that data and information, and begins to help them transform their digital journey from automated to semi autonomous, and eventually autonomous operations.

Larson: So, that makes sense. Is there anything that the management should be particularly aware of or concerned about in these organizations as they set out on this journey?

Fiske: Yeah, there's several things. They really need to begin to look at when they are in their journey and how they can move forward. They need to take a few steps. The first step is to really integrate operations and the data, so that they can accelerate that transformation. They need to break down those silos and centralize some of their operations. They really need high-performance, collaborative, multidisciplinary teams then can use Industrial Autonomy to provide greater situational awareness of the process the equipment, and also to augment some of those processes and make them autonomous. They can leverage autonomous workflows. They need to look at how they can then begin to innovate through discovery, design, and development process. And that innovation step can include redesigning business models and redefining workflow processes. Because that's the benefit of a lot of these things is not just digitizing your existing processes and doing them the same way, but taking advantage of the new capability that these applications are for, like, creating autonomous workflows, or making a process autonomous. And autonomous is different than automation in that it has the ability to adapt and learn to different states and modes and circumstances.

Larson: Yeah, that reminds me of a saying I once somebody talking about. With digital transformation, last thing you want to do is pave over the cow path, you know. Look at new ways of doing things digitally versus just digitizing the old way, and your going to come out way far ahead of where you might have been.

One of the things that we've really touched on in terms of a complimentary concept to Industrial Autonomy is talking about the system of systems concept. Can you talk a little bit about what that is, and how that how that fits with some of the technologies we've been talking about, some of the strategies?

Fiske: Sure. So earlier, we talked about the benefits of Industrial Autonomy and integrated operations. But integrated operations go beyond production to include the extended supply chain, which are becoming more globalized. They've changed so rapidly that it's very difficult and not possible to make optimal business decisions based on experience and intuition. And achieving resilient operations is contingent upon highly reliable supply chains, enabled by improved collaboration and sharing of that information. And we see this trend continuing beyond supply chains as more and more systems are increasingly connected in complex ways. The connected systems are referred to as a system of systems. And the individual systems are managed independently, they function and operate independently. But when you bring them together, they've worked together to provide additional functionality that can't be achieved by any single system. And that's the whole point of a system of systems is that additional functionality. And adopting a system of systems approach will allow companies to leverage a much wider range of data, and so that they'll be able to quickly adapt to those changing business environments. Operating strategies, together with various agile actions will result in additional value creation. And those actions could be done by people or they could be initiated autonomously.

Larson: That makes a lot of sense.

Well, certainly Industrial Autonomy is one of the biggest technology opportunities out there right now. Sustainability has to be one of the biggest things or benefits that we're driving toward or why we would apply autonomy. How do the two of those fit together?

Fiske: Yeah, so they fit together very well. Integrated operations and Industrial Autonomy is expected to help companies achieve their sustainability goals. What's really needed when you look at sustainability across an entire enterprise, is how does one area impact the other? And so, companies are looking at the integrated operations at a much wider perspective to create that view. And then they can better manage those scarce resources of energy, water, raw materials, while achieving their emissions and decarbonization goals.

Larson: Yeah, that makes a lot of sense really does. So, you know, you've gone out and done this exhaustive study, which is really interesting on adoption rates on Industrial Autonomy. But where do we stand in terms of developing the technology needed to really take us further down the road to lead the ultimate goal of IA2IA? Where do we stand in that in that journey?

Fiske: Yeah, so the the technology to achieve both enterprise wide integrated operations and Industrial Autonomy is readily available. We did that global survey, and the respondents ranked the cloud as the most ready to support large-scale Industrial Autonomy. A cloud platform enables data collection and aggregation, analytics to analyze that enormous amount of data, as well as AI and other applications to apply that data to monitor assets and orchestrate cross-domain workflows. And it also facilitates AI model building deployment and model maintenance. And when I talk to customers, I find that they want to democratize AI, avoid those one-off solutions, and be able to scale results across their enterprise and do that very quickly. And so, a platform approach is highly advantageous to achieve that objective. Now, some companies are also looking to adopt IA2IA in stages by first making the information available to connected workers, and then using AI as sort of a digital twin for the predictive and prescriptive applications. And then finally, just putting the system online to fully deploy the autonomous functionality.

Larson: Okay, yeah, that makes a lot of sense. As often happens to technology is head of the people who have to implement it, but it's good good to hear that we've got our work cut out for us and the tools are available.

Fiske: That's correct. And it'll take some work because it's a change in the way companies operate today. And that's always a challenge for companies to implement new technologies to generate benefits, because they have to change the way they operate their workflow, and in some instances upskill their workforce to be able to work with the systems.

Larson: Alright, well, thanks so much, Tom, for sharing your perspective with us today. It's been thought provoking as always. And once more, my name is Keith Larson and you've been listening to a Control Amplified podcast with my guest today Tom Fiske, Principal Technology Strategist with Yokogawa. Tom, if any of our listeners want to learn more about Yokogawa's offering in the Industrial Autonomy area, where can they go for more information?

Fiske: They can just type in the URL to our website Yokogawa.com/IA2IA.

Larson: Okay. And that's the number 2, right? IA 2 IA?

Fiske: That's correct. Yes, that's right.

Larson: Thanks, Tom. And for all you who are listening, thanks for tuning in. Thanks once again to Yokogawa for sponsoring this episode. If you've enjoyed it, you can subscribe it the iTunes Store and Google Podcasts, or wherever you find your podcasts. Plus, you can find the full archive of past episodes at ControlGlobal.com

Thanks again, Tom. Signing off and take care everybody

For more, tune into Control Amplified: The Process Automation Podcast.