068. Idea – Benefits of Manufacturing Digitalization Transcript

Chris: 00:42

Welcome to EECO Asks Why. Today we haven’t idea episode. We’re going to be talking about the benefits of manufacturing digitalization, and to help us walk through this conversation we have Bill Migirditch, who is the Manufacturing Solutions Manager at RoviSys. So welcome, Bill. 

Bill: 00:55

Hey, Chris, how are you? 

Chris: 00:57

I’m good. How are you doing today? 

Bill: 00:59

I’m doing very well. Thank you. 

Chris: 01:00

I’m excited to have this conversation with you, bill. Thank you. First of all, for taking the time with us to walk us through this. So maybe get us started. So explaining to that listener out there, who’s not familiar with manufacturing digitalization. What is that? How would you explain that topic? 

Bill: 01:17

So great question. And there’s a lot of answers to that question. So at its core to me that statement generally means a utilization of digital information to optimize your operation and performance.

And I know that sounds fairly generic. So like I got a couple of examples to run past you. So , obviously for the recording here we focus in manufacturing and that’s where most of my answers are coming from that background. So if you consider a manufacturing operation that produces something, whether it’s a discreet, a batch operation or something that’s hybrid, in most all of those operations, you’re going to find common operational systems for management of orders, production, quality, process. And even the automation is, we all kind of on this call are very familiar with. And in many cases, the information from those often disparate systems are used in a collective manner to run an operation.

When you talk about manufacturing digitalization, my experience and my team’s experience, it’s the task of putting those sources together to be more effective. So for example, let’s say you have a production scheduler who’s managing a week’s time for orders and they might look at a lot of things in order to plan when they make things through the plant. They might look at literally the schedule. What do we have to make? When is it due out the door? They may also talk to their peer groups like maintenance and quality in case there’s things that they need to do to make sure that production plan goes through as planned. And so to give you a detailed point, they may do something like look at the maintenance system to make sure that the line that he or she is planning to use isn’t scheduled for a major tear down. 

And so with that example in mind, in a digital world the way you can approach that would be to do something like when you sit down to do the schedule and scheduling alone can be digitized. You’d be surprised the number of places that don’t do that. But when that scheduler sits down, that person could then have their scheduling system look at the maintenance solution to say if their maintenance system, something like a Maximo or SAP, and look at the assets that are intended for that order, and simply check to see, Hey, is this line free to be used? Or is it on scheduled take down kind of thing? That that’s one very basic example. 

So here’s another one. Let’s say you’re operating a plant that’s processing like natural materials to a variety of assets and it requires frequent offline checks to make sure that when we make the product or we run the process, it’s having the intended effect on the product’s condition or its attribute. An attribute would be the things you’re trying to put into the product. So whether it’s color or size or whatever it is.

And in many cases today that often involves a lot of disparate, separate pieces of work going on, where somebody might, I’ll give you a worst case so you run the line. Line runs. Quality might come out and grab some of it, take it back, check it, look at it and go, well, that’s not quite great. And in the meantime that line back there just cranking away, making the same thing over and over and over. And your keep repeating the same mistakes. And so in a digitalized world, you might take that situation and tie that information together so the lines running. The quality person goes out and grabs a sample.

And notates electronically when that sample is taken. Quality does their work. Their data, literally the data they get in the lab, gets recorded to their Lim system against data from their process historian. And it says, okay, when you produce the sample in this cop, and it has these attributes and these attributes are due to the process conditions that I’m pulling right out of the historian.

Very very basic example. And I’m going to tell you an actual story about that later on in the discussion here, but that’s a very basic example of digitalization. Just using what you know. Now of course digitalization, people also talk about IIOT as well. And I’ll talk about more of that a little bit later, but there’s examples I’m giving really kind of were framed in the on-premise situation, there’s no reason why that information and those solutions and tying all that stuff together can not go outside the operation and leverage some web-based utility or tool or thing of that nature. 

Chris: 05:29

Right. So I mean, the things like scheduling and that quality piece are they traditionally done now via other means just more human direct interaction?

Bill: 05:39

Yeah. And in my experience, it depends on where you go. If you go to the bigger companies, more of the fortune 100, the five hundreds, those are the people that probably have, if you take, for example, scheduling. Those are the people that probably have made the investment gone out on the curve and said, Hey, we’re going to go through and implement more of an automated scheduling planning solution that can look at the orders and to tell you literally, Hey, based on a number of factors, whether it’s the line, the size of the order requirements. How we make that. 

And so as you get in, start to turn the focus back towards mid tier and smaller companies who may not have the means to implement a big formal tool like that. They often end up using, we could all guess, it’s a spreadsheet. It’s a spreadsheet exercise. Somebody sits down, they got a spreadsheet that gets handed to him. It gets spit out of the ERP system and they hand it to you and then go, Chris, here you go. Here’s everything we’ve got to get made by Friday. Have at it. That’s pretty common. And that’s pretty common for a lot of things to be on scheduling. Can be quality, a number of things. Yep. 

Chris: 06:39

Gotcha. Okay. That definitely painted a much better picture for me. So if I’m in that environment, how are you seeing that technology evolve that’s directly impacting things like that? 

Bill: 06:51

Yeah. So, and not to dwell on scheduling but there’s tools that do that kind of thing automatically. So smart AI type tools that can look both at your schedule and the demands of your schedule, the things you got to make. And it looks at your assets. And key variables about your assets and your operation. Could be basic things like is the asset available? Does it have the capacity to produce what you’re asking it to make? Do you have to go out to other departments to produce that such as quality and are they ready? And these are literally attributes that our automated scheduling system can just say, yeah, you got it. Or you don’t have it. And it’ll sit there and that AI engine will crank away and determine that. 

Now, in terms of how the technology is evolving, more down toward the manufacturing floor. Usually the way I like to start with that as you start talking about IIOT and go up from there and, in terms of what the technology is doing, as it relates to the equipment and down sort of like the level zero level one, especially with IIOT, I think the biggest thing that has changed and has evolved with those sciences and offerings is that the host of low cost smart devices that make it a lot more effective and easier to go and gather information about your operation or a line or a piece of equipment and get that information back. There’s such a plethora of hardware on the market today that’s cost-effective. Smart. Anywhere ranging from simple to smart.

So inexpensive, like in your world, it’s just inexpensive IO or smart sensors that can go out and do the work, crunch the numbers and hand a result back to a cloud-based tool that can say, here’s your information. Here’s what’s going on with the equipment. I think right now, the thing that those are a couple of the things that I feel like are really helping evolve and impact that whole approach of smart manufacturing. 

Chris: 08:50

Right. And how about, you’re in a lot of these environments talking with the end users, what are you seeing people get most excited or amped up about as they’re evolving towards digitalization?

Bill: 09:02

I think what gets people the most excited is the possibility of what they could do. So when you sit down with somebody, when often we do this, we talk to folks and they say we want to explore this manufacturing digitalization opportunity.

That’s more on the early stage curve that somebody’s coming to you and say, Hey, I’ve heard the term. I want to know what I can do with this. Now at the same time, we talked to people who were at any number of locations along that journey, starting from I’ve heard the term. I don’t know what it is. What can I do with it? All the way up to people who have said, Hey, we’ve got a committee, we’re looking at digital manufacturing and we’ve got some ideas in mind. 

So when I talk about the possibility of what they could do, oftentimes I think the thing that gets people the most excited is we will go to them and say, well, what are you forget the technology. Just forget, what are you trying to fix? As you sit down with your planning teams on a monthly or whatever basis, what comes out of those meetings that you’re being asked to drive improvement with? And when we sit and we talk to those people about those objectives, what they do today to hit those goals and the tools they use. And oftentimes it’s, like I said earlier, spreadsheets, Word of mouth, emails, data that has to be stuck together to make a decision. 

When you start to put a vision in their head about, well, here’s what you could do. Given what you have today and just simply getting a digital initiative together to get the information to the right people at the right time. Something we’ve all heard that theme. All the way to let’s take what you have today. When I say what you have, I mean like your systems, your automation, your quality system, your production system, your historians, the things that deliver valuable information.

And we augment them with other technologies to help you achieve what you want to do. Here’s how we think it’ll help you drive change. And so I think the thing that gets people the most excited is, when we come in, because we, as an integration partner, we talk and deal with a lot of people.

And as a result of doing that, it helps us be a more valuable resource to be able to say, well, let me tell you about what these guys did. Had very similar situation and that kind of thing. So it’s the possibility what they could do. 

Chris: 11:15

Right. The note I wrote down to stand out to me is you’re painting the vision of possibilities, whatever that may be for wherever they may currently be, you know? Cause everybody’s at a different starting point, as you mentioned, but looking for, I guess that that’s where the magic happens. Right. Being able to paint that vision and really connect the dots. And I know sometimes when you start connecting dots, headwinds come up and people see hurdles and sometimes they get overwhelmed. Like, Oh man, I can’t do this. Speak to that person who may be out there listening right now to some realities out there around those headwinds and hurdles. 

Bill: 11:54

Sure. Yeah. When I think about the hurdle topic, I think the thing that comes to mind often is the cost related to a digital project and the rationalization of what it’s going to do for the operation. What we sometimes see in a market, especially because all the stuff is technology-based, is people get excited about the technology. And don’t give enough thought to what is that going to deliver for you? I mean, it’s great to say. And I think we all know when people don’t put in technology these days, like they did 20 years ago for the sake of putting in technology.

So one of the hurdles is, is really about how do you justify what you’re trying to do. And I, I call it define before you design, in other words, find out what objectives you’re trying to improve. And throw the properly sized solution at the objective to make sure that you get a win so it’s the cost versus the benefit and the impact.

The other hurdle is we have a term we use within our IBS and digital supply chain group. We call it customer maturity. And we don’t mean that negatively. We mean it by. To give you an example, if you hand a solution that’s too technically complex to an organization or an operation, a geographic location that doesn’t have the training in place, the training methodologies, that knowledge base in place to support it.

You’re sort of heading for a train wreck so because people are gonna, they’re not gonna use it, they’re gonna stumble with it and it will soon atrophy.. They won’t use the tool. So that’s a hurdle. It’s it’s right sizing the solution for the people. So there’s ways of assessing and adjusting for that.

Chris: 13:33

Right. And that’s for a smaller operation that’s out there. If they’re wanting to right-size that project, and maybe look at more incremental areas of impact. What guidance or advice would you give them? 

Bill: 13:47

For a company of any size, the project, big and large, and especially more toward a small operation cause I think this has a bigger impact is, you have to have clear improvement goals with a project of this type. Technology related projects. So whether it’s reduced waste, resource quality, increased performance, meet the needs of a regulatory requirement.

So identifying what it’s going to do, what is this thing going to change? And then secondly a really big thing that’s important is leadership engagement. Leadership has to be committed to the solution. The concept whatever it is they’re going to put in place and be willing to give people the time to put it to work. Put it to practice on a daily basis. So, as they meet daily, they’re going to look at that solution and the information that comes from it and say, Hey, this thing is showing us something about how we did, how are we going to adjust? And take that data or that information or those metrics, how are we going to do things differently?

Because what it will do, what these technology solutions will do is they will show you what you’re doing wrong. And that’s kind of a general statement, but there are solutions out there that you put it into place. You turn it on. It’s going to gave me information you didn’t have, or you may have been measuring manually.

For example, we see this all the time. You put in a tool to measure something they’ve been doing it in the past, maybe with a spreadsheet or manually. And now the information is coming back and it’s different. And one of the biggest challenges we have with peoples to say, okay, first of all, we want you to know that you trust what you’re reading.

And they go, okay. Well we might not like the answer, but yes, it’s something different. And so typically what we do, especially with smaller operations is we say, okay, let’s watch that for a while a month, two months, and watch that baseline. And you might even compare it to your manual method to the point where you say, okay, we believe the information. Now start using it.

Chris: 15:43

I love it. Well, I mean, there were some great points there. Understanding where that customer sits from a maturity standpoint, but I really liked what you said, being clear on the goals on what those improvement goals are, but the leadership engagement. They have to have that buy-in.

So I go back to earlier in the discussion you were talking about define before you design. I think you’re all over that’s coffee cup worthy right there, man. Bill that’s. That’s awesome. 

Bill: 16:11

Soon as I get off this call, I’m going to have those made. so.

Chris: 16:13

There you go. You get one, send it to us. We’ll through EECO Asks Why on the other side, we’ll be good to go. So when you’re talking about these smaller projects and where you’re trying to get that buy-in people to embrace it and really shift the culture to where, okay, we like this, this is working really great. We just need more of it. And sometimes those smaller projects, they can be the beachheads. So how could someone out there who’s thinking about these projects really begin to put a plan together to, Hey, This could be something bigger, but I need to start small. 

Bill: 16:46

So I’ll give you a two part answer. And the two part answer sort of mirrors what I just said in the previous question. So number one, if you identify beachhead, obviously you’ve got some idea where you want to go, but find one that has an achievable set of success metrics for what it’s going to do so that the project can produce real results and that you get a win essentially.

And it’s a quick win upfront and that the people who own the issue, quickly and clearly identify, okay. If we put this in, what is it going to expose and what is it going to help us change? And that might be two or three things, you know?

So if let’s take unplanned downtime on a line that’s got a lot of sections to it and you want to put something in to help capture when you stop, why it stop, and how often you stop. One goal for that might be to take that information meet periodically through the week, identify and chase and resolve issues.

And that works should help you do something such as decreased the unplanned downtime on the line. So that’s part of your success metric and then the next part of it, is engagement and commitment. And so again, using that same example, I would say, okay, you go to this particular line and you’re going to get with the operators, the supervisors, the managers, and the people above the managers to say, for the next bit of time, we’re going to be taking this information and reacting and making changes based on what we learn and what that means folks, is that, it might mean that we run Monday, Tuesday, and Wednesday and at the end of Wednesday, we’re going to come up with this list of stuff we saw happen as a result of the new solution. We might come to maintenance and engineering and say, we need two people to go out here and fix this laundry list and do it right away because we’re trying to new process.

So identify with what’s causing you to stop and you take some different actions to change that issue. And that’s the engagement part because all too often what happens is that technology goes in, it exposes what’s going on. But the people who are typically required to go out and make the changes, whether it’s manufacturing, engineering, or maintenance, they haven’t been engaged.

And now you’re coming up and, Hey, I need you to do this and they’re going, well, I can’t do that. And that’s where the leadership part comes in. I have this term I use, but we’re all pulling the rope in the same direction. So you get the team. And we’ll get on board.

Chris: 19:05

That makes perfect sense. Absolutely. I mean, and so far as the team kind of perfect segue into where I was hoping to ask you about next, who do you see is typically involved in these types of projects? 

Bill: 19:19

From the start, usually what we see is when these types of projects have reached, let’s just say it’s reached a level where the operation or the site, or the team said, yeah, we want to do this. We’ve done our little bit of homework on digital manufacturing. So typically what we see, oftentimes is it’s, it can be a mix. Oftentimes it’s somebody with an IT and manufacturing background who has now earned the title of digital manufacturing director.

We see senior engineering leadership picking up these responsibilities because oftentimes engineering is expected to drive that kind of change and improvement. So I think those are two of the most prominent groups. IT and engineering that pick these up. 

Chris: 20:02

That makes perfect sense. So thanks for sharing that. How about any examples? I know you’ve been out there working with this technology and these concepts for quite a while, do any stand out as, Hey, this is a really cool project. This customer, this end-user actually adopted this and saw some really great impact or benefit or improvement, things like that?

Bill: 20:25

Yeah. Yeah, I picked out three and the first one I’m going to give you, it goes way back. Probably 15 years back for me when it, before I was actually at Rovisys, but in this particular case we had a client that was a tobacco producer and what they were trying to do was reduce the variability in their processing operation, where they process the tobacco and what they would do is, they’re making the product and doing things to it. They’re throwing things into it and quality would come out and literally grab up a scoop, like a bucket of material, bring it back to the quality lab and do their testing to it.

And test it for its its attributes. So whether it’s moisture content of, different ingredients, whatever it was. And then that information manually was used to go back to the process people say, well, we took the sample and tested it and here’s what we got.. And so they expect the process engineering to go well, okay. We will try fixing this and adjusting that. So what we did in that case, and this is very simple, but it was very, very effective is we went out to the line where the QC tech goes out to take the sample and we installed a digital button that we said, look, when you take the sample, we want you to just take the sample, hit this button.

And what that button did is it told their process historian they just took a sample. And at that time we set it up so that the historian would then go, okay, I’m going to grab a snapshot of certain process parameters upstream of this location that says. Here’s what it was. Okay. Whether it’s, I, and I can’t tell you the details, but there’s moisture and all these other things that the process would would have, and then they would take that data.

And after they did the QC test, they would compare it to the process condition. So at the end of the day, what it allowed them to do was make a very quick correlation between the products condition and the process that made it. And by going through that and work in that process, it allowed them really tightened their process variance and greatly reduce the variances that caused the product to be different.

Another one that’ll give you a relates to OEE solutions. So we had a customer they made a discreet consumer product and I, and I have to be general cause I can’t mention their name, but they had an operation where they started using an OEE tool and we had multiple lines that could make pretty much all of their products. They had a fixed set of products that they produced and they could aim them down any one of 10 lines. And as I started to use the OEE tool, obviously they started getting information about the lines, but they also had a configured, so they knew which products they were making.

So the OEE data and also included job number and product. Over time, what they were able to do is they could take that product information and compare it. So if you took a specific single product, they could say, okay, how does that product run on line 1 through 10. And does any one line make this better than another one?

And they also happen to look at shifts too, but let’s just stick with the OEE metric. And at the end of the day, what they were able to do by better leveraging that OEE data was to say, when we make this product, it certainly runs better on line 5. That’s the place to make it. And it also runs horribly on line say seven.

Now the way they use that. Is they said, okay, well let’s go to seven.. And figure out why we don’t make it well at seven and fix that. And so the cool thing about that application was inherently OEE. If you use it the right way, it’s going to help you just get more uptime and availability and just get more stuff through. It also helped them take the lines that couldn’t do it and make those capable. So it was almost like they doubled their capacity effect. They took the lines that made it fine and cranked it up a few digits, percentages, but they also took those lines that didn’t always do such a great job and made them more effective. 

The last one I’ll give you that. It’s more toward, I think it’s an interesting example of manufacturing digitalization, cause it’s involves an operation that really was a yard that process and produced natural materials, it’s primary materials.

And so the way the place was set up was they produce a product where carriers like truck drivers. They would come in. They would go to pick up a specific order and be sent to any number of locations on the site. They’re expected to get their trucks filled, get through against some specific order, get their trucks filled, get through the operation and get out and get down the road to the customer who uses the product basically.

And so the problem they had is that during busy times, they’d struggled to get haulers in and efficiently through the operation because everything was done manually on paperwork, like with the orders. So the hauler would be expected to come in, let them know what they’re there to pick up. Who is it for? The operation, the customer site would then have to go, okay, well, that’s this particular order right here. And so the solution we put fourth these folks is we said, okay, what we’ll do now is when haulers come in. We’ll give the truck and RFID tag that gets magnetically stuck on the truck.

So we know it’s here. That comes through this gate. Thing picks it up. We also happen to use license plate readers to identify the truck. So once that gets picked up, then they can assign it. They would electronically assign it right to the order. So now that they know this particular truck is here to pick up this order, the driver would get on a smartphone, they’d get instructions on where to go. On their phone. They drive there. They get their vehicle filled. And the, in this particular case, it was by weight. So they get weighed out now. Where the transformation started to happen is once that happens, of course, they had adequate automation that when the truck rolled onto the scale, they weighed the truck empty.

They filled it. They know how much they put in it. The truck drives off the scale, but now they also keep in mind. Now they digitally know what order was that for. So now instead of manually processing that order, that filled truck was rolling away and the site order goes, okay, you’re done. You filled that order. 

The other thing they did is now they knew the truck was done and it could leave the site. And one of the problems they were having previously was trucks tended to kind of meander around on site, waste time, find a time to catch a nap. And the place was busy. I mean, they were very, their business was good. And the faster they can get trucks in out and down the road, the better off they’d be. And their customers would be better off, especially if their end customer was actually busy. So that information was able to give them visibility to one, help the trucker come in, know what they’re there for. Know where to go.

Once their vehicles filled, that order could get processed in real time. Now there’s no more paperwork you just take and say, Hey, that order got filled. The ERP system looks at it. And by the way, that interaction was cloud-based, we’d take that information about the truck got filled, here’s the weight it’s against this order. And here’s the carrier. And electronically, we go up to the cloud and exchange that information with their ERP system. Well, now the ERP system has got the information and the person doing the invoicing can now invoice against it. 

Now, the other thing they did towards the efficiency end of this thing is, they would then watch which carriers had a tendency to come in and get slow or not be fast. And on site, they could work on that and it allowed them to assess and monitor and measure where they had trouble and fix those things. So at the end of the day, they can just get people through there faster.

Chris: 27:52

Right. Well, no, they were three great examples. The tobacco processing one really stood out to me mainly because I used to call on some of those processors and I used to see the people go out with the buckets and take the samples. And that was just a really good it painted a very good picture for me.

And then the OEE for sure. But this last one. Just the many benefits of that RFID solution just ties it back to quality as well as just production in general, all the different points. So thank you for bringing those three out. And Bill, this has been a wonderful discussion and we call it EECO Asks Why. We always wrap up with the why. So maybe for our listeners out there, can you wrap us up with a good why. Why should manufacturers embrace this digitalization as they look to grow in the future? 

Bill: 28:39

Yeah, sure. No, that a great question because look at the end of the day, our customers have to answer that question and if they can’t answer that question then, right. It’s going nowhere. So, I think when done right, the digital initiative empowers your people to make more accurate and effective decisions by bridging the gap between disparate systems. And, and I say that the desparate systems, because oftentimes if I had to generalize where some of those hurdles are it’s because you’re asking an operation or a site to accomplish a task using separate systems that require a lot of human manual labor and interaction.

Now, I’m not saying you don’t need that. You definitely need that. There will always be a spot where there’s that manual bridge of getting stuff, information from, in system A to B,. But those digital initiatives, that’s really one of the first areas of low-hanging fruit.

And then the other area is digitalization has the power to bridge the information gaps that exist between people through manual tasks, with systems like quality checks, process checks, like the example I gave you. And also, one of those areas being like automated workflow where you’re taking manual human tasks, whether it’s rounds and inspections, something where somebody’s walking around with a clipboard and having to go around and assess and measure. Where it’s not connected to automation. It’s some unconnected thing. So that’s an area where it’s kind of like the next frontier for some automation. You’re taking what the human does and you’re not taking the human out you’re just making what they do more effective and more real time. So instead of a piece of paper, it’s electronic, they take the data. The data goes somewhere for usage right away and the form they’re using can also tell them, Hey, you took a measurement that’s so far outside of spec there’s gotta be something wrong.

Chris: 30:35

Exactly. Well, I mean, this has been very helpful, painted a really good picture about some many benefits that do exist out there for the manufacturers that are listening. Check out Bill, you can go to the show notes. You can see his link. Connect with him directly if you want to learn more. Bill, thank you so much for taking the time for sharing your wisdom, everything that you’ve shared with our guests today.

Thank you. Yeah, it’s an exciting space. There’s lots of opportunity and appreciate the chance to chat with you about it.

Absolutely, we can definitely hear your passion. So no doubt, you’ve done wonderful things to just thank you for everything that you’re doing for this industry.