Integrated, intelligent and interactive technologies put the innovation in automation

Mike Bacidore: My pleasure. So, Mike, what is batch-size-one production? Why is it important, and how can machine builders and integrators help manufacturers to achieve it?

Mike Chen: Batch-size-one is an ideal state. It's that ideal state that the industry is trending toward where the consumer can get a product tailored specifically to them at a price that they're willing to pay, of course. And, at the same time, it is produced by a manufacturer that can remain profitable while supplying such a tailored product to the masses. So, it's that ideal state that the industry is trending toward, and that trend is accelerating.

We all know as consumers that we want choices, and that one-size mentality no longer fits all of us, and the personalization of product is becoming the normal expectation. We want choices, and we want it quickly. You think of the services out there that you see, like Nike By You, where you can customize your own sneaker or even personalized snack boxes from all these work-from-home days.

From a machine builder and system integrator perspective, the way that we see it is that this trend toward batch-size-one means that their demand for more flexible machines and interconnected IT/OT systems that is on the rise. This trend drives shorter product life cycles. And in order for the manufacturer to stay profitable and stay competitive with the other machine builders and system integrators, they need to leverage the newer technology, as well as skilled workers, to keep those designs fresh, making sure that production systems can still function cost-effectively when they produce multiple variations of different products and of the same quality that customers still expect.

Mike Bacidore: Productivity is certainly the bottom line, regardless of how many units of a particular product are being produced. In that same vein, the Industrial Internet of Things can help to reduce machine downtime and increase productivity, but its potential is so much more than that. How can the equipment leverage data, for example, from the IIoT to respond to shifting consumer demands for that batch-size-one production?

Mike Chen: We get that question a lot in the industry. And a lot of focus is around the technology itself. But, just for a moment, I'd like to make sure that we and your audience really think about the question as how people can leverage the data and the enabling technology around IIoT—not just the technology itself, but how are people using this technology to respond to the shifting markets and demands.

We have an internship program and a trainee program here at Omron for people that are new to the industry. Every year when we run this program, I talk to the new people coming into industrial automation and make sure that we all are on the same page that, over the past half-century or so, automation technology has really always been about automating physical tasks that were done manually or mechanized through machinery and figuring out ways to automate it.

But really the IIoT technology is an enabling technology for AI. And when I think of AI, I don't like calling it artificial intelligence. I think it's more palatable and understandable when we think of it as algorithmic intelligence, which is an acronym the industry has also started using. And so IIoT enables the data for algorithmic-intelligence systems to make decisions. You're not automating physical tasks but you're automating decisions. And each business out there, they need to think about, with their best people, what decisions they are willing to automate and how those could drive business decisions or production decisions, or even machine operation decisions, depending on what resolution some of that data comes in at and what the relevance and what the confidence level is in that data.

At Omron, we encourage companies in the manufacturing space to really consider how can they leverage the algorithmically created insights that gathered through IIoT data to solve societal challenges and improve human productivity, as well as improve product quality or improve flexibility to shift in response to those demands toward batch-size-one, because veteran employees at the machine builders and end users have unmatched knowledge.

We know that they have unmatched knowledge through their experience, designing, building, maintaining the manufacturing equipment. But that experience takes a lot of time to learn, to apply, and grow. And what we're imagining and the industry is imagining with IIoT, is imagine that possibility if some of those decisions, even just a fraction of those, were able to be automated or even semi-automated and enriched with other relevant data through IIoT technologies. That increases either maybe accuracy or consistency, predictability of those decisions and could allow those human subject matter experts to continue their discovery, their development, new knowledge that they could gain, and solutions they could create.

And that's really what manufacturers need. With the trend toward batch-size-one, that agility and that flexibility to respond quickly to customers like we've talked about, and it's easy. I think it's very easy over the past 10 or so years thinking about IIoT as a way to improve productivity and operational excellence. But now, after a lot of iteration experimentation in the industry around IIoT, we also understand it helps the people in manufacturing become more agile and responsive and really remain competitive.

Mike Bacidore: Your excitement about technology is contagious. That is one of the most passionate explanations of AI that I think I have ever heard. So, given those needs of manufacturers and machine builders and integrators, what specifically is Omron doing to support them in adapting to this dynamic market, these changing customer needs?

Mike Chen: To assist manufacturers and our partners and stakeholders, Omron has developed an innovative automation framework. And so innovative automation is a core value concept that we have where our products, our services, our business ventures are all in the direction of providing manufacturers with consistent, reliable ways of ensuring that they can meet both the consumer demands and the needs of the industry.

The needs of not only Omron's industry but their industry, the customer's industry, because this is a complete societal trend toward accelerated customization and batch-size-one are the overall demand and are shifting. The concept around innovative automation is based on three major industrial automation trends that we see over our history, our 80-plus-year history. The expectation of automation is that it must be more integrated. It must be intelligent, and it must be interactive.

So, together, these three pillars of industrial automation enable manufacturers to provide that highest level of quality and sustainability, and operational excellence that will help meet their future demands from innovative automation. Our HR teams and our engineering teams and our product management teams, all of our teams from R&D to operations, we're all coordinated around this idea so that our company culture is to innovate these products' processes and services to enable our customers to do the same.

Mike Bacidore: Fantastic. What about the workers? A lot has been written and talked about with the aging workforce and the shortage of workers, especially now coming out of this global pandemic, especially in skilled positions. How are those workforce issues affecting manufacturers' equipment needs?

Mike Chen: The expertise and experience of designers, builders and maintenance, the veteran employees out there in the manufacturing industry, is a form of capital. This is a form of capital which we certainly need to consider how to properly invest for the future. Highly experienced employees, are they best-utilized doing tasks and making decisions that they already know how to do and they can already essentially do it easily? Or are they best utilized mentoring future talent, driving new innovations?

Every individual company needs to have that decision and blend that on their own. There's no one-size-fits-all answer, even for that one. But really as the experienced workforce pool grows more difficult to pull from, not only because the pool is shrinking, but to pull people who are experienced from that workforce, manufacturers are really incentivized now more than ever to look at how could we possibly think differently and leverage technologies and potentially new business models to address the market demand. Just making sure that we're still utilizing the workforce that is available, not ignoring the entire workforce that is also available to us and not focusing only on the highly experienced and veteran workforce.

Automation equipment and components that are out there in the market that leverage data, leverage data-driven or historical insights, that is something pretty critical for business continuity at this point. So, making sure that that intelligence and insight is built in either at the product level or at the service level for different organizations. So, for example, we have products. We have industrial robots with built-in interactive maintenance alarms and alert users of service intervals. And that's something that perhaps in the past that would've been a seasoned maintenance or other engineer to provide that value and decision making.

Or in other situations like intelligent motor condition monitors that the product itself can detect anomalies in load conditions or bearing wear, that's something that might have needed and was definitely built off of a lot of experienced knowledge and now is able to be embedded in a product. But also on the service level, I think that the business models around complete care service programs where we can protect customers' capital investment and prolong their useful lifespan by leveraging some of those people that are in the industry and having it as a service, not only as a product.

Mike Bacidore: Right. It kind of moves the needle a little further along that path toward equipment as a service, although some of that is already available but certainly not to the extent yet where there is no longer capital investment. But perhaps someday

Mike Chen: The industry is trending toward experimentation into different business models, and we will all see how this evolves.

Mike Bacidore: So, equipment exists. There are production lines, there are brownfield facilities, and yet new technology continues to develop constantly. That integration of the old with the new, the installed base with the new technologies that enable communication and smart manufacturing, how important is it to be able to integrate those new components into existing production environments? And can you give some advice on the best course of action for that?

Mike Chen: The simple answer is it's extremely important because brownfield is really the vast majority. It's very, very rare at this point that you come in with nothing beforehand. Integration of manufacturing technology into brownfield production environments is the norm because most businesses still, whether it's service or capital invest in automation as a way to scale up, they already either have a manual or semi-mechanized production system or line. And I think we're going away from lines but more production systems and production environments where you don't have to do a single line of mass production as we go toward batch-size-one.

But there's almost always going to be a current process or current equipment or current facilities that need to remain running to keep the business going even as automation upgrades are made. I would say that it's critical for people to consider installing technologies which are safe for your work curve in that situation and services like a professional risk assessment, safety risk assessment, become quite critical in upgrading specific brownfield environments to higher automation operations. There are many industry standards to consider, not only on safety, industrial safety, and functional safety, but around things such as network communication protocols and programming interfaces and languages which really help brownfield customers scale their operations while leveraging compliant product, and their current talent. Current talent or new talent that have learned standardized protocols and languages in trade school or professional, or through experience.

So, many times, integrating the products over various protocols, architectures, and programming languages, typically, it's a pretty big challenge for manufacturers. It has been historically for sure. And that coexistence of the various formats in the production environment really increases the complexity, and it can cut into the operational efficiency and performance. But, at Omron, our products are designed with that integration in mind. We have Omron Sysmac Automation Platform. It is designed to be interoperable with the vast multitude of Omron components—not only with Omron components but also using built-in open network interfaces and communication protocols to integrate into existing production environments.

Mike Bacidore: Perfect. I kind of wanted to go back to AI a little bit with you. And I thought it was really interesting with the algorithmic intelligence that you talked about. I really wanted to ask about the advancements in machine learning that are enabling AI. But from your perspective, from that algorithmic intelligence perspective, how can that information be used and shared with, say, enterprise-level reporting and scheduling systems?

Mike Chen: They're all linked eventually. In the ideal state, they'd all be linked. So, there's definitely been many advancements in utilizing machine learning technologies around quality. So, you're using it to verify quality in both the quality and the process. And if we think about it as algorithmic intelligence, that really helps us imagine where it can be applied to solve real-world business problems.

The question that manufacturers must ask is which decisions could be automated and, if automated, could solve a business need? It always starts with a business need first. And many of those answers involve some data-driven decision that leads to an insight that requires further action. And that further action required, that's where it links in and ties in with enterprise-level reporting, as well as scheduling systems like work scheduling systems.

If you are able to more accurately or more confidently see a data-driven decision through machine learning, then you should be able to also more confidently schedule different human operations and human activities around that. So, depending on where the algorithmic decision is being made, and what I mean by that is that it is different levels of deployment or implementation of machine learning you can deploy at the edge. Edge meaning really at the machine level or locally in a facility at the "fog" and then, in the cloud level, which I think is most powerful and most popular. Depending on where you're applying that machine learning, that will determine the additional network communication and IT involvement required to securely connect that data source with other systems. And that will really define the challenges on data connectivity and security. So, our experience tells us that production failure costs grow exponentially as it travels further away from the machine.

So, if you can get some type of insight and corrective action at the machine level, that is going to be less expensive than as that blooms out to further systems downstream. As a technology provider, we are at the machine and robotics level, mostly for Omron. So, our products have access, direct access, or even generate the most relevant data in real-time. Our products are right there. And so helping manufacturers identify anomalies as early and upstream in the production process as possible, that reduces that risk and waste further downstream.

And at Omron, as part of our continuous commitment to intelligent automation, one of the other factors of intelligent automation, we believe it's the combination. It's a combination of local edge-based machine learning with accurate and secure OT data and IT layer insights that can provide the most unrealized value, so far maybe underutilized value to manufacturing customers. So, equipment life is extended, and that risk of defects is reduced wherever possible.

So, both the operational excellence, as well as looking at both operational excellence and data compliance,  you're going to have data and information moving between OT systems and IT systems. It's going to have to be there, and it's going to have to move to business-intelligence (BI) visualization. So, in our controller, as one of the examples of doing that is with a built-in SQL client, as well as OPC UA server capabilities to bridge some of those communication hurdles in order to create an interface, an easy interface that both OT and IT can access and integrate into these data and network architectures for visualization and further BI insights.

Mike Bacidore: Fantastic. Great answer. So, finally, with the introduction of more collaborative applications to the factory floor, it seems like humans and machinery are interacting more than ever, sometimes side by side even. What sort of safety features and programming platforms are enabling this interactive environment in manufacturing plants?

Mike Chen: You've already used our word of interactive. So, interactive automation is that third word in innovative automation: integrated, intelligent and interactive. So, creating a safe interactive environment is really paramount. Like we talked about earlier with risk assessments, whenever there's a plan to bring in new robotics or new production equipment, we, of course, recommend starting with a professional risk assessment.

And through that risk assessment, manufacturers can get help, get help determining how to comply with the standards that are written in order to keep people safe. And that could be potentially coming up with safeguarding measures that make sense for the business environment, as well as the manufacturing environment. The safeguarding measures could include technologies as simple as a door interlock and safety relay. They can also include implementations of safety laser scanners or collaborative robots, or safety-rated autonomous mobile robots (AMRs), so, additionally, industrial robots that are designed specifically to operate in collaborative environments.

What we find with customers that we've worked with for years, is it makes a huge difference in the worker acceptance when they can interact with the new tech at all levels of maintenance and engineering. It helps them kind of overcome their previous image of robots or their fear and really accepting that into the workplace and letting them come up with new use cases for the technology.

So, collaborative robots are designed, we think, to be the next level of like a super power tool where people don't use hand cranks or drills anymore. They very comfortably use power tools for that. So, the collaborative robot becomes that next-generation super power tool where it enhances that worker's capability or capacity to add value to their organization, for both experienced and new employees, really.

And then I've mentioned briefly autonomous mobile robots or AMRs. Such as an example is our LD or light duty series AMRs. They can dynamically guide themselves around the production line and react in real-time to a human environment. They're designed specifically for human environments to avoid collision in a safe way. That's really valuable in enhancing the existing production environments.

We already talked about brownfield. In brownfield, enhancing existing production environments, improving the product quality and yield while simultaneously reducing production downtime. So, manufacturers using AMRs are very much a trend and enable customers to safely manage that production flow even without making huge investments in new facilities and creating a line of traditional production lines. And really when that batch-size-one manufacturing comes back or comes into play, that flexibility is a big deal.

So, in interactive automation, the last thing is how intuitive. How intuitive is it to configure and operate some of this new equipment and technology? And that's where I think you said earlier about the programming platforms and how people will interact with it. The integrated development environment is both a trend and an expectation at this point. Having disparate software systems and disparate ways for people to interact with the technology, it adds that complexity.

At Omron, our Sysmac studio programming software and development, integrated development environment, provides that easy-to-use single environment for programming, configuration, commissioning and monitoring the entire aspect of the machines. And that also plays into how we think of interactive automation as part of the needs of the industry.

Mike Bacidore: Perfect. Can you recap the three Is again for me?

Mike Chen: Sure. So, innovative automation framework, we believe that it's all about integrated, intelligent, and interactive, making sure that your automation technologies are integrated from a business perspective, from an automation perspective, as well as intelligent, able to leverage data and make decisions intelligently and algorithmically, of course. And then interactive, being safe for the human worker really. That harmony between human and machine is what Omron has always stood for.

Mike Bacidore: Yes. That's a great summary. And I like that almost as much as I like the “next-generation super power tool.” That's probably my favorite new expression of the day. Well, thanks so much. Thanks to all of our listeners for joining us on "Control Intelligence," the podcast for Control Design magazine. And thanks, of course, to Omron Automation's, Mike Chen. Thanks, Mike.

Mike Chen: Yep. Thank you, Mike.

Mike Bacidore: If you've enjoyed this episode of "Control Intelligence," don't miss our other older episodes and subscribe to find new podcasts in the future. You can find our podcast library at controldesign.com, or you can download all episodes via Apple Podcasts or Google Play. Thanks again, Mike.

Mike Chen: Thank you.

For more, tune into Control Intelligence: The podcast from Control Design magazine.