Podcast Masterminds in Maintenance

S2:E7 An Introduction to Smart Manufacturing with Mark Miozzi

Ryan Chan

Mark Miozzi is the Smart Manufacturing Specialist at Rexel Automation Solutions, a leading distributor worldwide of electrical supplies.


In this week’s episode of Masterminds in Maintenance, we are excited to have Mark Miozzi, Smart Manufacturing Specialist at Rexel Automation Solutions, on the show! Ryan and Mark discuss the smart manufacturing – the benefits, the process of implementation, the technologies involved, and so much more! Listen today!

Episode Show Notes

  • Benefits of Smart Manufacturing
  • Implementation process of Smart Manufacturing
  • Technologies involved in Smart Manufacturing

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00:02 Ryan Chan: Welcome to Masterminds in Maintenance a podcast for those with new ideas in maintenance. I’m your host, Ryan, I’m the CEO and founder of UpKeep. Each week, I’ll be meeting with a guest who’s had an idea for how to shake things up in the maintenance and reliability industry. Sometimes the idea failed, sometimes it made their business more successful, and other times their idea revolutionized an entire industry. Today, I’m super excited, we’ve got Mark Miozzi here on the show with us. Mark is the Smart Manufacturing specialist at Rexel Automation Solutions, a leading distributor of worldwide electronical supplies and Rockwell Automation Solutions. Welcome to the show, I’m really, really, excited Mark to have you here and get the opportunity to learn from you.

00:42 Mark Miozzi: Me too, Ryan. Thanks, I really appreciate the opportunity to speak with you.

00:45 RC: Well, what we always do with all of our guests, I would love to start us off by having you share a little bit more about your background and how you were introduced to this field of maintenance and reliability.

00:57 MM: I’ve been supporting manufacturing companies for over 20 years, my career actually started as a value-added reseller for computer mainframe systems. So back when disc drives were the size of coffee tables and memory boards were the size of pizza boxes, and then it was interesting through Y2K as the world didn’t end, but servers did end up taking over and companies shifted from mainframe technology to server-based technology. And then I found myself on the other side of the wall supporting more on the shop floor of the smart machines, and manufacturing systems that actually produce goods, and now working with customers as they migrate their legacy control systems and obsolete control systems to current IIoT ready smart machines to help with efficiencies and the gains that an ethernet network could bring compared to obsolete discontinued communication networks that a lot of machines are still running today.

01:55 RC: So it sounds like you’ve really spent the majority of your more recent career in the Smart Manufacturing revolution. Just so we’re on the same wavelength, could you help explain what Smart Manufacturing is, and ultimately what the benefits are to all the businesses that might adopt Smart Manufacturing?

02:17 MM: Machines that are on plant floors in industrial facilities of manufacturing facilities have controllers inside of them, they have computers inside of them that have data available, and companies are going to be able to be more efficient if they can tap into that raw data that is already being produced by their machines and then allow current technology to serve it up to them in ways that they can use that data in real time to make decisions based on what the machine is doing and how it’s performing, and start to implement predictive type maintenance, start to be able to change recipes quickly and adapt to changing technology and trends and have information ready at their fingertips. So using smart sensors, using analytics, using the raw data that’s already available to them in real time, and being able to be more efficient based on how the machine is running at that point in time.

03:16 RC: We talk a lot about the whole IIoT revolution, what’s the difference between this whole Smart Manufacturing revolution going on right now, and the previous technologies that have been in place for decades? SCADA systems, PLCs.

03:34 MM: Technology is becoming more cost-effective with the way that it’s communicating based on an ethernet and open protocol type technology, so that the information is now readily available to users using open platforms. And numerous things can be tied to that data. From the sensors on the machine to the actual controller itself, to the pumps, to the motors, to the next machine, connecting those machines together with the software that’s able to put everything in front of people. So the technology is really improving to be able to give real data in an efficient way for machines that don’t have to be high-end SCADA systems, waste water systems. It can be packaging, palletizing, production, all under one roof and in a pretty easy way to connect using current communication networks.

04:29 RC: Yeah, absolutely. So what I’m hearing, and I totally agree with this too Mark, is that what the whole Internet of Things, and this whole revolution going on right now, it’s really about lowering the cost, the barrier to entry to start monitoring different pieces of equipment that would have been too costly before. So instead of only running a control unit on the most expensive asset that you’ve got, now it’s lowered the cost and barrier to entry so that you can start placing sensors in different parts of the business, different parts of the production line. I’m curious, what have been the most common applications of IIoT in more recent manufacturing businesses?

05:10 MM: Implementation of robotic cells with traditional manufacturing cells and being able to share the data between the two, implementing more technology on to the line in almost a way of being able to modernize through cost-efficient ways and get the data at the same time in that same migration because the computing power of current technology far surpasses what was started in the SCADA machines years ago, as you mentioned that barrier of entry and the cost of the equipment is now so much more effective to be able to realize those benefits that IIoT and analytics could give customers.

05:51 RC: Something else that’s very top of mind for a lot of people in the industry right now is obviously what’s going on with COVID. And what I see happening in in lot of production floors is they’re kind of reducing the number of people that are allowed to step foot onto a manufacturing floor because of social distancing measurement rules. Are you seeing that be a driver towards IIoT, or I guess maybe a broader question is like, what is gonna make IIoT really prevalent in the industrial space?

06:27 MM: We’re definitely starting to see a lot of customers that have their innovation plans and want to use technology. It’s becoming a little bit more top of the list now in ways that they have to be flexible, they have to re-purpose some people because even these systems need people to maintain them, they need people to review the data and be able to create the work orders to keep everything efficiently moving. So we are gonna see a shift in what people are doing on the shop floor.

06:56 MM: It’s quite interesting to see how companies are adapting now and technologies that are being used and how additive manufacturing and 3D printers are being used to create products that we never thought would be in manufacturing spaces before. So the innovations are gonna keep coming out. I think we’re gonna see a lot more projects start and in the way that we would promote projects, to start with a small project, start with a line or a cell and prove out your concept of how you can be more efficient, how you could be more adaptive to a change that needs to happen and then prove that out to other models. So you’re gonna see companies start to realize the benefits of that data, of the efficiency that the technology brings to them and they’re just gonna want more.

07:40 RC: Where I think all of us are already starting to see some of the big pushes towards robotics, IIoT and I’m really, really excited by this, Mark. From your perspective, what are some of the most interesting, what are you most excited by amongst the newest technological shifts and changes that are coming up?

07:58 MM: I’m really excited about how easy it is to get analytics onto people’s devices now. With the proper infrastructure, customers could be monitoring nodes on their network, on their smartphone in real time, and be able to make decisions within their team structures, send that out to other people, create work orders, use technology that we’re all carrying around in our pockets now to, be more efficient. The 2:00 AM phone calls that you might have used to get at the waste water treatment facility, right? They’re going to continue to be reduced, people are going to be more flexible and be able to be more predictive and with machine learning and the amount of information that is there for customers to absorb, it’s gonna really change the way that we’re manufacturing and being efficient in our manufacturing facilities.

08:47 RC: I too am extremely excited by the amount of data that can be collected once you put a smart device on part of your production floor and part of your production line. The one challenge that we’ve seen a lot of our customers face when you do that is you’ve got all of this data now stored in the cloud, but we don’t have the proper resources to be able to analyze that and drive action. And so, maybe to you, Mark, what’s one of the solutions to that problem? Because I know that it’s common. We’ve gone through a project to stick smart devices all along our production line and we’ve got piles and piles of data, but we don’t know just quite yet how to best interpret, analyze, and ultimately take action off of that data.

09:38 MM: Yeah, there is a ton of data, even if you think about cameras and how much information comes and is being stored from images, of just somebody working on the line and what that causes, but data scientists and those type of fields are really gonna be beneficial to customers as they start to mine their data, starting with the small projects to gather all the data, to learn what is valuable for them. So all the other data that is just running and being produced does not get stored. It flags the anomalies, it flags the information that you’ve programmed it to look for and you start to build your decision trees off of what you really need to capture for the data and the rest of it is only stored for a minimal amount of time, or whatever is needed from that. But trying to start small with projects, to not be overwhelmed by the data, is a fine line the customers have to learn through their first, second projects, so then as they continue to rinse and repeat, they know what they’re looking for and how much data they need to store and then it’s being creative and figuring out ways to store your data and keep it accessible for you.

10:45 RC: Who do you think should be the person that’s responsible for, again, ingesting all of this data, analyzing it, and then coming up with action plans? Is it that data scientist? Is it a reliability engineer? Is it someone in operations? Is it a technician? Wo should own that?

11:05 MM: Honestly, it’s a team in my opinion. The companies that have innovation teams or factory of the future teams, connected enterprise groups. Information to the reliability engineer that’s valuable might not be the same information that’s valuable to the operations manager or to the engineering department. So, you need champions that are looking for information and data to make their decisions and have a collaborative effort. One person can’t be responsible for all that data and all of the decisions that come from that data, because it affects different parts of the company in so many different ways. So truly having a team that’s focused on innovation and efficiency is gonna be, I think, where companies are gonna see the success.

11:53 RC: Yeah, absolutely. I’m sure you’ve implemented so many of these Smart Manufacturing projects at different companies, where have you seen the biggest success for some of your guys’ customers? What kind of positive impact did it have?

12:08 MM: Positive impacts come from reliability and implementation of the predictive maintenance. That’s really where we’re trying to start with customers is knowing what they have, what they can support, what needs to be migrated for support, and then what they could get after all of that is complete? All projects start with wanting information and wanting to be more efficient, but you have to start somewhere. So we’re focused on starting at that roadmap, to help customers be successful, but then some of our projects in food and bev, semi-conductors, waste water is a real successful one for us too, the projects just keep growing as we build on that start small and expand type of model and it’s all across industries. There are bumps in the road in every project, hiccups come up all the time, but it’s just having the right team in place to be able to work through them with that end goal of delivering a smart machine or a smart silo.

13:07 RC: Where do the most successful companies start with with regards to IIoT? Is it like a specific sensor or are you talking about like is it temperature, is it line speed? Where are you seeing the most successful companies really start adopting IIoT?

13:23 MM: It’s in the communication and it’s in the network. It’s in the sharing of data, getting information out of the cell and into people’s hands that’ll benefit from making things faster, more efficient, quality control, etcetera. The biggest benefit is maintenance most of the time. One really good story was there was a line that had thousands of vacuum hoses on it, and if a vacuum hose went down, it would take maintenance 45 minutes to troubleshoot to determine where that problem was. So with the investment of ethernet with an analytics device, using machine learning, the company was able to minimize that by 30 minutes. So now, if a vacuum line fails, they can pinpoint that, have it replaced in 15 minutes.

14:10 RC: And I’m guessing they were what, pressure sensors along the different points of the vacuum, so that they could basically get a notification immediately when it happened, and know exactly where to go, versus have to shuffle through 1000 different points within the vacuum. I’m sure a big part of every single implementation has to also do with integration too. I’m a manufacturing facility, I’ve been using the same system for the past 20 years, 30 years. How do you guys integrate in with the MESs, the CMMSs of the world, the ERPs or do you typically recommend companies and say, “Hey, look, we wanna crawl, walk, run, let’s not try to boil the ocean and integrate your 20 year old system in with the newest technology”, or do you commonly find that it’s really important at the get go to start integrating the different solutions?

15:07 MM: I like to follow more of a crawl, walk, run. I like that analogy. Try, look, small successes and we promote and utilize ethernet IP, which is open protocol, so devices can talk across manufacturer. A lot of the technology we use is manufacturer agnostic, if there’s an ERP already implemented, we can talk to it, there’s numerous software to make that happen all the way around. It’s all about the assessments and the base lines prior to kicking off the project and then the pre-work and the testing that goes into making sure those handshakes work seamlessly as they’re designed to. There’s numerous software packages, numerous ERPs and platforms, as you’re aware, and there are numerous programs that make everything talk together, so it’s just being able to have the openness and the platform to start from, to be able to increase the ability for systems to talk seamlessly.

16:01 RC: Kind of wrapping this up, what’s one thing you wish more people knew about within the maintenance reliability industry?

16:08 MM: There’s so much data there already at your fingertips and it’s very cost effective to harness that data, to make real-time decisions, and it’s always more cost-effective to maintain active and current assets and products than it is trying to maintain those 20 or 30-year-old systems. Sometimes, we live in the curse of manufacturers that just run. “The thing, the machine’s been running for 25 years.” Well, one day, it’s not going to. That is when you really start to get into trouble, spending a lot of money to maintain discontinued and obsolete machines. So taking that, using the programs that are out there to migrate through your spares, it’ll give you more value and it’ll save you money over the long run.

16:52 RC: Awesome, totally agree with you. There’s so much cool technology out there. Sometimes I even myself get overwhelmed with the amount of new technologies coming out. So definitely, do your due diligence, test the right ones for your facility and you’ll find something that I think a lot of our customers have realized that way outperforms that 20-30 year old piece of equipment, that manufacturing line. I’ve learned so much in just this short period of time. Where can I go, where can all of our listeners go to continue following you on your journey and connect with you?

17:31 MM: LinkedIn, Twitter, great platform to make business connections and have conversations.

17:37 RC: Alright. Well, thank you so much again, Mark, for joining us. Thank you to all of our listeners for tuning in to today’s Masterminds in Maintenance. My name is Ryan Chan, I’m the CEO and founder of UpKeep. You can also connect with me on LinkedIn, or shoot me an email directly at [email protected] Until next time, thanks again, Mark.

17:54 MM: Thank you.

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