The Manufacturing Executive
The Manufacturing Executive

Episode 101 · 6 months ago

The Future Is Here: AI Based MES Solutions


The manufacturing industry has been slow to adopt new technology. But with the continued improvements in technology, updating your systems has become more cost effective, faster to implement, and more flexible for your manufacturing needs. 

Today’s guest, Barry Johnson, President of Digital Manufacturing at Symphony Industrial AI, talks about how to take advantage of digitization, AI, and emerging technologies to increase productivity.  

Join us as we discuss:

  • What MES is and the purpose it serves in manufacturing
  • How digitization drives continuous improvement
  • How AI is changing the future of manufacturing

I just want to do say away in the spense application, I don't have to buy this big modelific I means implementation on deploy. I can buy just the functionality I want and I can deploy that in agile fashion theever value across my line and my facility or multiple sites, and come back and do that in a in a repeatable way. Welcome to the manufacturing executive podcast, where we explore the strategies and experiences that are driving midsize manufacturers forward. Here you'll discover new insights from passionate manufacturing leaders who have compelling stories to share about their successes and struggles, and you'll learn from B tob sales and marketing experts about how to apply actionable business development strategies inside your business. Let's get into the show. Welcome to another episode of the Manufacturing Executive podcast. I'm Joe Sullivan, your host and a CO founder of the Industrial Marketing Agency guerrilla seventy six. This episode is brought to you by Workstep, a software provider that helps companies higher and retain their frontline workforce across the supply chain. Visit Workstepcom to learn more. Very few manufacturers can afford to deploy an army of data scientists and their production environments to analyze historical data in search of creating that golden batch. But in today's AI rich environment, manufacturing leaders can turn their process engineers and manufacturing engineers into what my guests today refers to as the citizens data scientist. With the right tools in hand, the right data insights and knowledge can be harvested, processed and put into the hands of the right people inside of their organizations to effect change. Let me introduce our guest so he can tell you all about it. Barry Johnson is president of the digital manufacturing division of Symphony Ai Industrial, where he leads a global business focused on helping manufacturing companies drive digital transformation via their low COODE AI enabled manufacturing operations management solutions. With six hundred plus deployed plants and more than fortyzero users, the digital manufacturing division helps manufacturing companies reduce variability in their processes while increasing through put and yield. Barry is an experienced senior executive with more than twenty five years of demonstrated success in the industrial software sector, driving revenue growth and improving a business performance internationally. Very previously served in multiple executive roles at Rockwell automation, including global vice president of software sales. Before Rockwell very held numerous software rolls at GE driving growth organically and inorganically. Very welcome to the show. Thanks Joe Christy here. That's good to have you, Barry. We're going to talk about ems software today and for anyone listening who's not super familiar with the topic, wondering if you could just kick things off by simply telling us what MS is all about and the purpose it serves inside of a manufacturing organization. Sure so. The concept of MES certainly is a new it's been around probably since the S, starting, I think you know, the semiconductor industry. Companies Manufacturing really complex products needed systems and tools to help them do that. So manufacturing execution systems, or sometimes referred to as manufacturing operations management systems, which is technically a super set, is really a specialized class of software from manufacturers that really it manages the execution of real time physical manufacturing processes. And at the fundamental levels that's really all about transforming raw material into finished goods, and so every manufacturing company, no matter what you're making, does that. Transfers raw material...

...into intermediate or finish goods, and companies do that in a wide variety of ways today. Some companies do it with paper and a spreadsheets to manage that process. Other companies have developed home grown or customized solutions to help manage that process. Over time, other companies of purchase package software and MES software from automation vendors or software companies and deployed solutions along the those lines and they delivered a lot of great business value for companies that have, I'll say, had the fortitude to embark upon that journey, because it requires the traditional approach, requires some significant investments, but companies are being able to do it. You end up having a business system in place that enables you to, you know, really reduce your inventory, drive higher yields, reduce your cost of quality. There's a lot of great business benefits that come from having a system that really now is digitized your manufacturing operations and provided you with insights and how to drive continuous improvement. So that's really what it's all about. We started to hint at you know that traditionally, mes solutions have required significant investments. Previous conversation you told me they're ten tend to be kind of slow, maybe kind of rigid. How's this changing at this moment in time, or maybe in recent years, and from your perspective, what's the future of MEES solutions look like? Yeah, so, like I said, Joe, meys is been around for a long time and one of the challenges that sort of, I'll say, played the industry for for, you know, the time that's been around. You're right. If, tradition you can think of these systems as significant costs, long time to implement, fairly rigid and they've also been very sort of industry specific, for manufacturing process specific. It's what I mean by that is, if you're a batch manufacturer, that's very different than if you're manufacturing discrete parts or if you're a process manufactured doing continuous processing, and so traditionally there be a different MES solution from maybe a different vendor. So if I'M A multimolde manufacturing company, Sam a pharmaceutical manufacturer, and I make an active pharmaceutical ingredient, which is a batch process, I might have one set of technology and then downstream, as I'm doing packaging and filling, a completely different syte of technology, and so it's just it's just one of the things that's really sort of slowed the industry's growth and really made it this reality where even the most sophisticated companies that have deployed ms have only got it deployed in a portion of your enterprise. Because of some of the reasons I just mentioned, it's been really difficult to adapt a solution to the individual needs of a smaller site that might be a little bit different than sort of the other sites that the system was designed around. So that's been a bit of the challenge with the traditional approach. So every manufacturing company that I talked to is looking, you know, towards you know, next gen M es, I could use that word, and there's a lot of really exciting things that, like I said, traditional on he ask those vendors and those solutions of that technology is developed in the in the early s mid S. now, with the emergence of Sass, with the proliferation of mobile devices, lowcode, no code approaches, now we're starting to see companies that are providing solutions that are much more modularized and composible. I mentioned a lowcode approach to being able to develop applications, whereas in the past, where you develop and applications. It's a large sort of it project. You're writing a lot of code. Now companies...

...are providing sort of object based, visualized dragon dropways to develop applications and the ploy those in really agile way and really the goal of empowering manufacturing engineers and operations people, as opposed to it projects, to be able to deliver value. And then I again come back to mobile piece. Every manufacturing company is dealing with with this, with this situation where the vision is being able to handle an IPAD or a mobile device. To a new manufacturing associate and their productive day one because they had got to work instructions, they've got everything they need to do to go about their jobs. So all these technologies are kind of emerging in a way that really changes the landscape and changes the game in terms of if I'm a manufacturing company, is especially one of the challenge is also if I'm a medium sized manufacturer, he's you know, it's been really cost prohibits really take advantage of on this technology. And so now, you know, companies like ours and others now offer a much more agile potuer. If I just want to do say a way in dispense application. I don't have to buy this big monolithic I means implementation and deploy I can buy just the functionality I want and I can deploy that in an agile fashion, deliver value across my line or my facility or multiple sites and come back and do that in a repeatable way. So there's just so much of a different approach that companies are starting to look at. Well, let's talk about Ai for a minute here. What are some ways that AI base I mes solutions can create value that may not have been the case with traditional I mes software. Yeah, so really traditional on yes, hasn't really done anything with AI at all in the manufacturing sense. And even AI and manufacturing, when you look at it, most companies have looked at using a I in the context of really predict a maintenance type of use cases. But this is a really interesting topic because companies have started to see the potential benefits of using AI to assist in some of the areas where mes has been really strong. Looking at process analysis and improvements in your manufacturing operations over time. That can only be gleaned by looking at historical data and looking for patterns and anomalies, and so one of the things. That is really exciting. You know, we're going to projects like I could talk about a little bit, but it's all about kind of how do I adhere to the golden back or the golden run? So again going back to my earlier comment and he has it all about transforming raw material and to finish goods and if there's a perfect way to do that or a golden way to do that. And what you're trying to do is eliminate deviations and eliminate a lot of variabiliar process. How do I take ai and how do I look at the ability to correlate input variables into that process to my output quality and using multivariate analysis and some data science algorithms to really generate optimal set points and speared manufacturing process towards that sort of golden batch level and looking for ways to identify deviations as early as you can the manufacturing process. It just makes a much more efficient water on your operations. So kind of where the market is today, companies have had to deploy data scientists to look at you taking a bunch of historical data and trying to build models, and no manufacturing company can really afford to have an army of data scientists, something the manufacturing environments. So again here, with some of the emergence of some technology from companies like howls and others, you know, we're providing tools to enable sort of, you know, the citizens, data scientists, if you will, which in our world is really process engineers and manufacturing engineers. They're... them tools to be able to integrate process data, train and noladate models and be able to deploy those in a way that again puts knowledge and insights from the hands of the people that are running manufacturing processes and being able to use AI and really do that. So I'll just give you one example, Joe, where a lot of times you'll see in manufacturing processes the only way to do a final inspection that might be a visual inspection, might be looking for a cosmetic defect or something that's difficult to catch some kind of testing promise. There's still a lot of a lot of manufacturing companies still have a lot of people doing inspections at certain critical checkpoints throughout the nlne or order, the manufacturing company that makes electronic components, and one of their challenges is it's really not until they get the end of the process, really do a final quality check, they find defects and they're small little devices, so they've got a lot of people looking at them. And whenever you do that it's fraught with human error, right it's number one. Is Expensive and you end up with a lot of just human error. So we're working with them and we're using a combination of image recognition image capture, which again is not a new technology. That around a long, long time, with vision systems capturing high speed data, but now looking at and building ai models and looking for patterns that continuously learn and continuous to train. And so this example, this company, we're able to dramatically reduced the number of first past defects. Over time we're going to be able to help them really with quality and yield and ultimately much less of a need on that human interaction and people looking at products coming out the end aligne. Turn into good or bad. Such is one of maybe, but it's really exciting topic in manufacturing again, getting beyond sort of predictive maintenance, which are great use cases, but really into I can improve quality, if I can improve through put, I can improve yield using using models. That's there's really a lot point that's a great example. Let's take a quick break for a word from our sponsor. Hiring and retaining frontline supply chain workers continues to be a major struggle in today's market. WORKSTEP is a leading software provider that is partnered with manufacturing companies to help them better understand the true reasons behind their workforce turnover and take actions to improve it. WORKSTEP has successfully helped many manufacturing companies reduce their frontline worker turnover by up to thirty six percent. Visit Workstepcom to learn how you could do the same and protect your bottom line. Are there any other you know, success stories? You know, whether or not you use an actual company's name is not important to me, but that you can talk about to kind of show what sort of transformations you've seen come to life after deploying a modernized MEES system like you've been talking about today. Yeah, others, they were in company names, but all totally you know, maybe a couple in a couple dither context. So yeah, we work with a large, large multinational conglomerates and sort of the industrial and consumer good space. And again the big levers are productivity throughput yield, and so with that, with that client they've been able to save averaging over a million dollars annually per plant, just by eliminating, as I said at the beginning, manufacturing companies, most of them you'll see, all kinds of systems that were built over time to manage the transformation of raw material and to finish dreads. So just by being able to reduce the number of homegrown systems, redundant applications, standardize your operations. That's another big benefit. Where you're talking about being able to deploy and yes, solutions across the number of number of sites, you can start to do benchmarking. So if I'm making the same product, you know, in Chicago's and Singapore that I am in Germany now, if I've got a solution to play across all those sites, I can...

...start to do benchmarking and quality improvement, of continuous improvement over over time. So that's just one example. You know maybe another one smaller scale, but a company that's in sort of the agriculture and chemical business. They were looking for a better way just to get a handle on again sort of yield and overall equipment efficiency, and so we deployed a susher for them across fifteen sites. Going back to the agile notion. was talking earlier of the capbuilds to some newer technology across fifteen sites in a matter of about three months, and so that's kind of unheard of and compared to the sort of a traditional model of the approach to m MES. So that's a couple of examples. You know. The other thing that I touched on this earlier. One of the challenges has been MS hasn't really fit into smaller manufacturers. But I might just have one manufacturing site. So when we work with the company that's sort of in the business space and the plumbing and common control solutions and again just looking at sort of real time operations management of their their high mixed type of operations and we were able to reduce a lot of their scrap improve their yield, just giving them visibility in their operations to drive continue some improvement and that saved them a bunch of money. About fourteen percent improvement and throughput and overall coutment efficiency. Again, just the one other example, I'll pause. Another building manufacturer with really know one site and just what they're looking to do is just get a better a better handle on the variability across their products, so they make something that they're they want to have a very consistent process and they were. We were able to work with them to drive at twenty five percent improvement in productivity just by reducing scrap and reducing stuff that they had to throw away. So just a couple of examples, and there's many, but it's all about really reducing the cost of good sould and and really driving improved quality and through book so you've suggested a couple times here in this conversation that you know a number of manufacturers will probably only have software deployed in some areas of the company and what's holding the back is at the the investment costs up front. Traditionally is like, well, how do you scale that and figure out when the right time is to scale that across the organization? Yeah, I think it's a number of factors. Cost is certainly been one. The rigidity has been another. Right, because I'll sort of go back to the example I pushed on earlier companies that deployed and es solutions that have had success and had to there's some tradeoffs, right. So if I want to drive standardization, that's that. There's a lot of benefits that as I just mentioned, you kind of you can do benchmarking from site to site, but in order to kind of fit into the way it do that, you've got to you gotta mold your manufacturing processes sort of fit the software, fit the application you're developed. Now, as soon as you do that, you've had to give up some of the some of the specific site capabilities you might need if you're making different products. So there's always been that balance of how do I drive standardization versus how way, how do I meet the needs of localization and the local sites? So that's been one of the things that's really, I think, inhibited the growth across multiple sites. So now again the companies like ours offering a way to deploy solutions in a much more agile way. Again, going back to that can bind off just the function out of that I need and deployed across multiple sites and come back and do it again, and it's almost as though the benefit of the Rlif from the first implementation funds the next. Is Sort of a continuous improvement type of approach. But the other thing I would just caution you know, people to be aware of. You've got to have some governors in place when you start to deploy solutions across your enterprise, because it's very easy to take a solution. That might be really easy to spin up a solution, but but if you have a different solution for this...

...cell versus this style or this line is this line, this plan versus the other, pretty soon you end up in a untenable situation where you got a lot of different, albeit on the same platform, applications deployed. So what works was really trying to help companies do is look at what are ways where you can still have governance as well as drive the ability to rapidly deploy value across the enterprise. So there's ways that we can do that and it's really an exciting, exciting time because that really hasn't been an option for most manufacturing companies in the past. Will tell us a little bit about symphony and what you guys do and what makes you unique? Yeah, so at the sympathy level, we're a collection of companies are all focused on really bringing ai to bear help digital transformations in the businesses that we're focused on. So we've got a large business focus to the retail business and media. I'm absolute part of the industrial business and so we're all about driving again digital transformation, leveraging a as I spoke about, as as a means to do that. So there's a tremendous ai something has talked about a great deal, because there's just so much untapped potential, and so that's really what we're all about, is still bring real, tangible business bact to our clients. It's got to be a fun space to be in right now. It's just so much interesting technology emerging and everything's happening so fast. It is, as you said when you introduced me out, have been other than the space for a long time and, quite honestly, the progress of the market has made compared to some of the industries other industries is pretty stagnant. The manufacturing industry has been pretty slow to be able to adopt new technology. Things is like the cloud is an example. A lot of manufacturing companies still they've kind of wanted their data on prem or worried about because these systems are mission credible. You know, once you got a system like MES deployed, if it goes down, I'm not making product and depending upon the sector that you're in, that can be really expensive or really dangerous in some cases. So companies have kind of tended to take an approach of I'm going to get something in place, I'm going to lock it down, I'm going to not touch it and I'm going to bring that asset for as long as you can. But, as I said, now, with saft becoming more and more prolific again, especially for companies and sort of medium size space, now I can you can consume and MES solution some companies like ours that we can host. You don't really have to stand up any infrastructure. It's really just kind of, you know, be able to take advantage of the out of the box function owity that companies like ours can provide and start to deliver immediate value. So mobile is another, you know, key thing. People aren't tethered to their work cells as much anymore and the whole proliferation of mobile devices just is making all of this a lot easier as well. Barry, is there anything I did not ask you about that you'd like to add to the conversation? No, I think this has been has been really good. I think if what it maybe what I would say is, you know, this is a very much an inflection point at a different time in the market. I said earlier, every manufacturing company I talked to whether they've got a traditional on yes, in the past really didn't. We're all looking for how do I take advantage and how do I drive more productivity in manufacturing companies. Executives that I talk to. They don't have time to imagine, you know, solution as they want real life applications to build our business value, and so I would just encourage companies to, you know, to take a look at some of the new vendors out there. There's a lot of new approaches to solving some of these problems where if you're if you get involved with somebody, you're going to start to good lunar business value. So I would just encurage people to take a look at the market. That's changing more now than I've ever seen a change, you know, in my twenty five years of being and it's really interestiting. That very great conversation today. Can you tell our audience how they can get in touch with you and where they can learn more about symphony ai? Yeah, I mean the easiest places just to check out our website and will make sure the link is...

...sent to everybody. But it's symphony industriallycom beautiful will very once again, thanks for doing this today. Thank you, Jos as for the rest of you, I hope to catch you on the next episode of the Manufacturing Executive. Before we go, I want to say a quick thank you to our sponsor work stuff. Worksteps software helps companies higher and retain their frontline workforce across the supply chain. Visit Workstepcom to learn more. You've been listening to the manufacturing executive podcast. To ensure that you never miss an episode, subscribe to the show in your favorite podcast player. If you'd like to learn more about industrial marketing and sales strategy, you'll find an ever expanding collection of articles, videos, guides and tools specifically for B Tob Manufacturers at grilla seventy sixcom learn thank you so much for listening. Until next time.

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