How Manufacturers Are Leveraging Digital Transformation to Improve Operations

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Mike Tidy, General Manager, ATS Digital Solutions – joins Jim Beretta, host of the Robot Industry Podcast, to discuss a variety of topics related to Industry 4.0 and the digital transformation of manufacturing.

The conversation focuses on the increasing use of automation and data within manufacturing operations and several related topics. They tackle questions such as:

What changes or trends are currently taking over the global manufacturing sector [2:20]?

What keeps Information Technology Officers up at night [7:02]?

Where do you store the ever increasing amount of data that is being produced by manufacturing operations [9:37]?

Mike and Jim explore the significant changes happening in manufacturing, touching on topics like; the increasing complexity of Automation equipment, upskilling and re-training operators, the rise of inline testing, and the increasing use of data in decision making on the shop floor.

Be sure to check out the full podcast to hear everything that was discussed or read the full transcript below.


JIM: Hello everyone and I’d like to welcome you to the A3 Robot Industry Podcast. My name is Jim Beretta and I’m your host. We’re broadcasting from Cambridge, Ontario today. I’d like to thank and acknowledge our partner the A3 Association for advancing automation. The A3 is the umbrella Association for the RIA, AIA, MCMA, and A3 Mexico and these four associations combined represent almost 1300 automation manufacturers, component suppliers, systems integrators, end users research groups manufacturers, and consulting firms throughout the world that are driving automation forward. We have a guest today and his name is Mike Tidy. He is a leader of ATS’s Digital Solutions division focusing on industry 4.0 solutions for global manufacturing companies. Mike has decades of experience in IT solutions with the last 10 specifically focused on solutions for industrial companies. He has started and grown two software and services businesses within organizations and is an advocate for digitization and process involvement in manufacturing companies. Mike has been with ATS for nearly two years, working out of their Cambridge head office. So welcome to the podcast Mike.

MIKE: Hey Jim, thanks for having me it’s great to be here.

JIM: I’m glad you could make it. On our discovery call we both heard our dogs in the background and we have two almost like cloned dogs that we both bought, black poodles with a white crest on their chest. So if I hear some yipping in the background, I know that’s your dog.

MIKE: yes although not sure if yours is biting as much as mine is, so that’s why we’re doing some training right now. lots of fun on that.

JIM: excellent, well I wanted to also let everybody know in the audience that I actually used to work at ATS for a very long time, and if you could check out my bio sometime I had almost 16 years in the company, so I know ATS very very well, and they are a very strong controls a very robust group of vision people so I’m glad to have you on the call today, and I wanted to ask you and start the conversation – what’s happening in manufacturing these days? Is it time to market? Is it collaborative technologies? What are some of the things that you’re hearing from?

MIKE: yeah so there’s a lot of sort of higher levels of micro and macro trends going on, and maybe I’ll sort of hit a few points here from my experience anyway which is certainly automation. Automation equipment is getting way more complex, much more independently operated, a lot less requirement for operators to actually be involved in the machines. Much higher level complexity, a lot more products being built from start to finish with full automation without a lot of manual intervention from people except in some cases feeding product in one and one end and taking finished goods out the other. But certainly the level of automation is really staggering, and it’s going on right now, and that comes with a lot of challenges. One it’s challenging to know how many people you need to insert and what your costs of production are, and secondly we’re also seeing a lot of challenges around skill set. So for people working with that equipment, so it’s kind of timely on our conversation on automation and automation technology, because it’s not just the machines it’s how people are working with the machines that is really changing. We’re seeing shortages in skilled maintenance and operators, we’re seeing higher trend into digital technologies to help support some of those people to be able to run the machines they’ve got. Some of the trends, the other trends besides skills and then the advancement of technology within automation, we are seeing a lot of inline testing, so while a product is being manufactured we’re seeing test stations and test data being involved in that to make sure that we don’t get to the end with the fished good that is defective, that we pick those up part way through the line, retool them and then maybe reinsert them back into the line so that we get to high quality output versus more throwaway parts. We’re seeing a lot of focus on data obviously, and we are going to talk about that today, but lots of data, and we are seeing a lot of proliferation of software. A lot of point solutions where people are trying to address scheduling with people or products or machines in operation quality. Just a huge proliferation for people on the floor of what technology is coming to optimize production.

JIM: I’m getting the feeling from you that the word “fast” and “time to market” are all becoming very important parts of automation, but let’s talk a bit more about IoT and Industry 4.0, the big overall trends that you see.

MIKE: for sure, I mentioned earlier that data is continuing to grow in importance, and you see a lot of trends, so if you look at some of the think tanks around like Gartner’s and others talking a lot about data, and obviously data is becoming more and more important in lot more growing areas in that. We still see a lot of sensors, more sensors coming into the market where people used to and continue to get information on PLC’s. We are seeing real growth in independent sensors and data coming off, whether it is vibration or thermography and other things. Cloud and edge particularly cloud just like in every industry is really starting to come along. People talk about cloud and edge and fog computing, and what that means to automation. We’re seeing a lot of interest and change in that, adding to the IoT or Industry 4.0 story. A lot of data analytics, people wanting to know what’s going on now. The days of pulling lots of data and sitting on it for a month and then looking at the end of the month and seeing how we did, rear-view mirror kind of analytics, is not cutting it these days. People want to know now, what happened. They want to know what happened last shift. They want to compare this shift to that shift, operator to operator. The frequency, to your point, the speed of data is becoming even more important. We are also seeing a lot of and hearing a lot of conversation on things like digital twin and artificial intelligence and machine learning. A lot of collaborative technologies as well, augmented reality and virtual reality, I feel like I am throwing lot’s of buzzwords out here, but they all kind of apply to manufacturing. A lot of integration between different machines and different software stacks. We’re also seeing some of the traditional stuff we’ve always focused on is still key. Things like OEE [Overall Equipment Effectiveness], driving down costs, increasing production without having to add more equipment. There is lot’s of that kind of work still going on, where we’re still looking at the fundamentals if I can call it that. And finally services is huge. It’s one thing to have a strategy, and to talk about Industry 4.0, but really things like reliability engineering and leveraging subject matter expertise are growing. So it’s supporting the services around IoT not just the products are some of the trends we are seeing.

JIM: that’s a very broad overview thank you for that. I’m going to make you explain a couple of terms. But you’re probably talking a lot to the chief technology officers out there of manufacturing companies. what’s keeping them up at night?

MIKE: yeah so it’s probably the same thing now of course with automation that’s kept them awake with everything else in their IT lives. Security still continues to be a huge conversation point with all IT professionals. Where is the data being stored? Who has access to it? Is it secure on the plant floor? Is it going to the cloud at our data center? Who gets access to it (data storage)? So all of those security issues around data are still massive and there are large conversations keeping them awake at night. I think remote access is a big one as well. If you look at what’s happened over the last few months with, as much as I hate talking about COVID-19 because it’s our new reality, but it seems to pop up in every conversation. now we won’t be able to fly that expert from Ireland to go to the plant in Iowa to help to troubleshoot. We’re going to have to now do that remotely somehow, so remote access technologies are coming in and people are using tools kind of like the tool we’re using that may not be necessarily set up for secure access but it’s easy. So you’re seeing a lot of technologies being thrust into organizations that the IT folks may not want them using. They might want them using Microsoft Teams or Zoom, they want you using something that’s more secure. There has been big picking on zoom in that one so that’s sort of conversation is continuing to keep them up at night. Networking equipment, how do we network maybe stand alone equipment that used to be on the floor by itself? How do we build that into a larger network infrastructure, is another big trend and I think it’s keeping them awake. Then a lot of them have a digital strategy. So whether it’s coming from a top down from the board of directors or whether it’s something that the IT team has come up with or maybe the operations team, enabling and building digital strategies is another big piece for most of these organizations and they’re being asked to deliver on all the buzzwords we just talked about. All the new trends and technologies, its a little overwhelming for them I think to get dragged into some of these discussions and be the expert where there’s just a lot of information and a lot of different technology.

JIM: Mike that’s great. I was in a cab in NYC a couple years ago, and we are recording this in the middle of the Covid outbreak, and the guy I happen to share the taxi with was talking about race car driving and how it’s not about race car driving anymore. It’s about the data and he was talking about how his team was analyzing gigaflops of information and it is just astounding to me. Where is all this data kept?

MIKE: it’s kind of everywhere and that maybe another CTO challenge to keep them awake at night too. so you’ve got basically everything from Excel spreadsheets. I’ve been in a lot of manufacturing facilities where the main request of automation companies is “can you give me a CSV, can you dump a bunch of data that I can look at later?” you got people using the cloud for analytics and for storage. You’ve got people at data centers either on Prem or global to use them. So it’s kind of everywhere and I think that again depending on what the usage is for the data, you’re seeing a lot more consolidation of that. One of the recent trends that seems to be getting a lot of visibility is MDM or master data management is the title for that. I say its almost like a move on from an old data like concept that was big a few years ago where we’re looking at consolidating operational data, marketing data, production data, and machine data into one place then getting valuable insights out of it. It’s across locations and divisions and continents and maybe even companies so that large exploration of data is of interest because you can pull out some insight out of it, but again security and who’s got access to it while you’re doing it are some key parts. I think you’re right with your race car analogy, it’s the same thing everywhere. Data is King but it’s what we are doing with it is really where I kind of get frustrated sometimes is are we doing the right things with it? are we getting real value added or are we collecting data just for data’s sake?

JIM: Well I’m pretty sure we are in many cases collecting excess data. You almost have to say with each piece you import or whatever what are we going to do? is this going to make a material change to our business? what decisions can we make by collecting all this data? I think lots and lots of manufacturers out there are kind of saying let’s take everything, let’s figure it out later. That might be another podcast, so I hold your feet to the fire and I’m going to get you to explain to me what a digital twin is? I think I understand but I just wanted to hear it from you.

MIKE: yeah so Digital Twins. Earlier we talked about it as an evolving space and it’s a topic that’s got a lot of conversation in the market right now. There’s a lot of focus on it, there’s some companies that have really done some great early adopter work on this and have come up with some good solutions. My own organization has done some work as well on that. What it really is, is it’s a way of representing a physical asset including the ability to test it, emulate behaviors and scenarios, and do other virtual models. It doesn’t necessarily need to look like a picture of the asset that you’re working on but it digitally needs to match it and it’s characteristics. Certainly the aerospace industry’s been doing this for quite awhile with engines in particular. What it does is it allows things like driving maintenance, stress testing, Accessibility, and future proofing design changes over the life of the asset. It’s typically integrated with a bunch of other systems, so your PLM or CAD. Maybe your ERP systems apply or push additional information in. It’s really a way of looking at the reliability of the asset and being able to help to model that into the future. I think the places we found it most effective are in the mass production environment. I said aerospace is a big one. There’s a lot more challenges with Digital Twin, I think pulling it into the space of individual robots and machines that maybe aren’t mass that are more customized but that’s also where the demand is going in the economy right now. People want to see those unique assets that they built up whether it’s an assembly line or a testing line being modeled so that they can actually come in and see how efficient it’s working and make tweaks to it before we spend months and months building the machine and actually having a solution. It’s a precursor typically putting screws together and welding metal to build the line and customer demand is definitely increasing in that space. We’ve done some of it in the energy space where we built some digital Twins for some machines using nuclear which has been interesting. Typically at the end of the day it’s not just the technology like we said the data, it is what business outcomes you’re driving, so how’s it helping us with the design of the machine, the maintenance, the product support? What does the customer user interface look like or the experience you have with it? How do we optimize it? There’s a lot of elements around the design piece of it. Hopefully that helps. It was a long answer to a short question.

JIM: OK well I have a couple other short questions. I want to also have you explain to the audience, because they’re out there driving or exercising or whatever they’re doing, what’s the difference between a SCADA system and an MES system?

MIKE: sure so SCADA is the traditional methodology that we’ve been using for decades and decades and predominantly focuses on data acquisition and a visual representation and storage of data. SCADA providers, and there’s lots of them around, for decades and decades as a set of counters, some of them since I expect the 80s and 70s, did provide additional functionality and are continuing to work their way up the food chain. They’ve gone from the data management piece to more of a higher stack including analytics and trending and forecasting. MES on the other hand is sort of a higher level system that typically is responsible for control and driving the machine control to match the demand from the systems which are typically like ERP like our SAP systems. So what we’re typically finding is the MES is sort of that high level of sitting between the machine and the ERP system and providing for full control and data acquisition for the machines on the shop floor. So what we’re doing is if you consider an automotive supplier who has an order for a vehicle, the order would come into SAP or whatever systems they are using. It would, based on the model number, push features and requirements of what that car looks like into ERP. ERP would then push into the MES and the MES would then filter that down through a number of systems including the automation systems to build the car. So MES is typically viewed as the higher level that sort of sits on top of SCADA and it can contain SCADA like features in a SCADA system so the system that we actually provide we do have a full stack MES in it, suite which is part of our solution we’ll talk about that in a little bit longer but basically think about where MES plays it can play sort of in the Green field space where there’s clients who have nothing, who are basically manually loading recipes into the PLC’s to drive machines or it can operate as a broker, some middleware system between ERP and maybe that recipe management in the machine control. So MES is not monolithic, it’s a number of different systems and modules that work together to allow us to automate the equipment room and remove some of the manual interventions that used to go on.

JIM: Thank you for that. So what are some of the major things that are happening in automation systems deployment? I mentioned speed you mentioned that automation is getting more complex, what else is going on?

MIKE: I think complexity is an interesting word and you touched on this a little bit earlier, but things are getting much more complex and intricate. Predicting automation space. I think that what we are looking at is really services are now the new frontier that companies are really forced to look at and that is because we’re seeing that growth in complexity with automation. There’s really a huge growth in system services that have to be done. I know we’re seeing demand for augmented reality and virtual reality and training requirements to try and push some of that knowledge into the organizations that may not have that deep skill. We’re also seeing a real focus to augment customer staff to backfill for skills gaps. It’s interesting how many companies now are having to hire controls engineers where they never did before just because the machinery is so complex that they have to have people on site. I think a lot of companies, and ATS is one of them, are seeing that as a gap that they’re filling. Another thing I think we have to do is provide directive and timely insight to machine operators, maintenance, and production staff. Companies are needing more tools help to manage those procedures and some of them have to manage certain remotely with Covid. If you think about in the past there may be one person in a company who is the expert on controls and they would fly all over the world solving problems for the manufacturer that happened in their equipment. That can’t happen in a Covid world so we’re now in a place where having those remote technologies and having that skill set shared across multiple people is going to be more and more important. Again it just reinforces that AR-VR shift that we’re seeing right now in the industry.

JIM: I think we’re going to look back at this Covid time and also pull out some of the things that have pushed industries into acting differently. So you have a product in the automation industry called illuminate. Can you tell the audience what is unique about this software?

MIKE: Sure, so the product we have is called Illuminate Manufacturing Intelligence and like one of the earlier questions around industry 4.0, were an industry 4.0 solution. It was developed by ATS and our high-level tagline is “machine builders building software for machine operators”. ATS has got over 40 years of experience building and servicing automation equipment. What we’ve done is we’ve taken all of that knowledge and skill that we built up over decades of building really great machines and put that into a software that allows people to operate the machines and provide lots of benefits which I’ll hit in a second. Our system works across a number of machines not just ATS’s. It works on virtually all controllers and PLC’s that respond to third party equipment not just ATS. It’s really focused on discrete manufacturing. We’ve got examples using medical devices and consumer package goods like tube filling and things like that. We work in the nuclear and energy industry including solar panels. Lots of consumer products. Electric vehicles is a big focus, particularly battery manufacturing and control. A lot of work in automotive and OEM’s. Some work in aerospace, radiopharma, and pharma dosaging machines. Sort of a broad base of the discrete spaces were Illuminate plays. What’s really unique about it and said is that the system was built by machine builders and operators so we have a really powerful manufacturing platform that’s based on tens of thousands of machines being designed and rolled out and supported globally by ATS, and we’ve taken that and wrapped it into a software package. All we do is automation and manufacturing so we have a deep understanding of that space and we reflect that as best we can in our solution. A little bit of the pitch in that last piece. What is it? We’re an end to end manufacturing control solution. We include some functionality that they see most in the PLC all the way to the ERP system. So we’ve got a full MES, we have solutions in vision and vision integration for operations. So faults for example. We support testing. We have manual stations for those who are still there manually which include autonomous guided vehicles and control of those in management. We have predicted maintenance, preventive maintenance, data analytics in a data analytics package, as well as simple reporting. If you look at it just I described a lot of things there, but it’s highly graphical and it’s highly intuitive. Very easy to use, it doesn’t require a lot to figure it out and get going quickly so even though it’s got a lot of complexity in it we try to make it really simple to use and a deploy.

JIM: So Mike who, what, and where? Let’s say I have a 10-station automation system, it wasn’t built by ATS, what kind of system can it fit on then?

MIKE: Basically we go top to bottom. It works just to sit on all types of machines and all types of controllers. We’re less concerned about what it is. I don’t think we’ve been stumped yet which is kind of interesting. It can be installed and configured remotely so that works well right now in our Covid world that we don’t need to necessarily be on site to do it, we can remotely install and get it going. It runs on the customers premises, which at this point is quite often the preferred method for systems that are integrated with machines and controllers in their port of production. We’re an “on-Prem” solution for that and we have single cell machines, so we’ve got clients who have a great idea the entrepreneurs of the world who have a great idea for a product. They maybe get a couple of manual stations and have people building their product by hand and working out the kinks. We use illuminate for that as they progress into automating that process we can grow with them and when they go to full automated production lines and multi-site global locations we can also go with that. It starts with baby steps and can go right all the way through to full production or we can just jump right into full production. We’ll say most are full production cause that’s where people tend to get most excited but it’s certainly a solution that scales from small to extra-large and everything in between

JIM: so it’s aimed then at medium to large manufacturers and high value and high-volume manufacturers?

MIKE: We’ve got people that are starting their digitization journey so it’s interesting some companies start with the real vision that we want to be immediately digitized and we want to be using all the newest technologies and others start a little more manual. We tried to pick that up with some multi location around the globe using illuminate on everything they have from packaging and cartoning machines to filling and assembly. We have a global footprint of multinationals and also a lot of small to mid-size boutique manufacturers and testing operations as well. We have testing cells as well. We support them all, we have a Global Services team that gets the customers up and running and provides training and ongoing management. Then it will continue as we have a reliability engineering team and some technical SME’s who can keep the systems running once they’ve installed them since we know not everyone has that great IT organization or those great deep technical skills. I think one of the differentiators for Illuminate is that we’ve really focused on the question “how do we enable people with our services and deep SME skills to get them up and running and keep them going?”

JIM: Thanks Mike. A big challenge in automation is that it’s really hard to connect machine vision, say a fault that happens, to an event. I still remember this from my days as an applications engineer and in sales where something happened and we had to get the high-speed camera and check it out, but you seem to have cracked the code on this from our earlier conversation?

MIKE: Yeah we’ve integrated a number of vision solutions. We’ve got about four or five in the portfolio now, but the one that people really resonate with has been around almost since we started working with illuminate. It’s something we call the DeBug camera, very sexy marketing name for it, but basically what we do is it ties fault, defects, and others sort of trigger events on the machine or through the operation to a video image in real time. You basically get a really focused short video clip of the issue as it occurs. Basically if you’ve got a fault, we use the camera station on that machine. It captures when the fault occurs and triggers an then captures an image where we get a snip before the fault happens and a snippet after the fault is happening so you’re really getting this little parsed out video clip that is tied directly to the fault, so when you go back either in real time or at the end of the shift to see what faults we had, you can go back and say OK we had five of this type of fault and we’ve got five video clips of that fault occurring and they’re all time stamped, they are in the line of the actual production information and it’s just way more efficient than putting a guy or a girl to sit beside a machine and watch it all day and look for faults or look for defects or parts that aren’t being produced or operational issues. You get that little snippet and you can analyze it, watch it over and over again. The snippet is then stored with the machine data and is available in the future. One of the other things we’ve done around vision, the base one is DeBug, we’ve also done some really interesting work around machine learning with quality control defects. So basically what we can do is we take images of product, make an assessment of what good looks like using operator information and input, and then we can automate the process and actually have the operator not required. We’ve done some really exciting work with a number of clients around machine learning which is now part of our portfolio, again another way of using vision. One of the things we didn’t talk about earlier but has just become a huge area as well and a unique thing you mentioned about Illuminate is we’ve actually tied vision into machine data so they’re not standalone systems and are part of the same report itself, part of the same process.

JIM: so, we can retire the high-speed camera right?

MIKE: Well some of those are part of the scalability thing. Some of those high speed cameras are $150,000 – $200,000. They’re very big, very expensive piece of equipment, that when you’re building a machine is very critical. But when you’re actually in operations mode we often find that doesn’t require you role in the big guns for it and certainly there are some instances in super high speed machines where they still use them but you know we found that a lot of our machine builders are using the DeBug camera as part of illuminate to replace your $150,000 high speed big gun camera. So yes I think we’re maybe soon to retire them. Everything has a place!

JIM: Absolutely. One of the big challenges if you’re integrating IoT and you’re buying products like the Illuminate program, do I need to also hire a data manager or data decision person? Can you kind of go into that a little bit?

MIKE: Yeah so we tried to be really directive about that and we try to build Illuminate in a way that it really drives outcomes versus just data. So what we’ve tried to do is say you don’t need a data scientist or analytics people we’ve built things like analytics to review performance data and make recommendations right into the system. As an example of that we have a predictive maintenance module, which instead of just presenting a whole bunch of data and probabilities, it actually looks at the machine at the components and identifies the most at risk elements of the machine and it reports it in dashboards and sends alarms and alerts and basically says if you’ve got 1000 grippers on your machine or 1000 servos or 5000 servos like that one in one operation, we actually look at that and identify the most highly impacted ones and say you don’t need to look at the 1000 just look at these six cause these six are really a problem and may cause issues in the next little while. So what it does is it looks at outliers and then focuses your maintenance plans on actually taking action on the things that need to be done versus a whole bunch of different data points. So again it’s focusing on outcomes and results and removes that need for deep analysis and I think most companies do not want to hire data analysts data scientists they’d rather just be given outcomes and things to do. It’s funny, it’s kind of the fascination with technology that I think a lot of us had was one point was just how cool is it to get all this data. I think now people are like you know I don’t want any more data just tell what I need to do. They wants us to help make their jobs easier and that’s really what we’ve tried to do with Illuminate is focus on the outcomes and not on the Gee whiz exciting stuff that went into it.

JIM: One of the things that we talked about prior to the call was about remote learning and I think this is a huge thing because of course we’ve got this massive skills deficit in advanced manufacturing and we have a lot of unemployed people right now. Have you cracked the code on remote learning as well with this product?

MIKE: Yeah actually it’s funny and timing is always interesting. Literally a couple months before maybe three or four months before Covid came in we launched a product called smart coach. Basically what smart coach is, is its system is built for remote learning and it’s part of our digital solutions portfolio. So what it does is it’s bundling a bunch of existing technologies together, so we’re doing a little re-purposing which I think is good we don’t have to create everything from scratch, and uses simple tools and voice prompts and what it allows you to do is have subject matter experts and also customer experts build up sort of a sizable library of video and data augmented trainings with kind of minimal investment from our ATS staff and then very little ongoing support so using you know things like HoloLens, and other virtual devices for recording, we can then take imagery and record people performing tasks, best practices, bring in other data sources and kind of capture some of that tribal knowledge that some of the people have on the floor as well as taking some of the knowledge maybe from an ATS person who built the machine and pull that all together and make it in it really easily digestible format. What that does is you pull together a 5 minute video on how to replace the part or how to do a piece of maintenance. We do it fast it’s done almost in real time and stored a tone in things like illuminate and then whenever there’s that machine event that video can be easily popped up and pulled up and you can have basically any operator go out and do the work on it and do the maintenance tasks. I think it’s already easy again we’ve been doing video and recording for a long time but I think it’s changed now I’m not sure that we practically have a solution for it is. Just making it super easy that basically an operator with sort of five minutes of training can make his own operator video on maintenance tasks and that’s a huge change from where we’ve been in the past.

JIM: It sounds very exciting Mike! you know you can take something like a changing out a robot end effector or something, put it in a video, and you could use that thousands of times right? Because changing out a robot end effector is probably very similar across many different types of robots. so that’s very exciting so I’d like to ask you a question about maybe getting your crystal ball out and saying what is the future for this type of software? It almost sounds like we’re here now but I’m already asking you what the future is.

MIKE: I think we’re definitely in it’s not like this this is this type of software is been around for a while and ATS has been in this business for 17 years of building great software like this Illuminates history is this is our 18th year of Illuminate. so I think there’s still a huge future for it. The one thing I would say is there’s a lot of players in the market. Manufacturers have a lot of choices, a lot of different companies to choose from. There’s really no definitive market leaders or massively dominant players that own this space and I think that’s good because it gives people a lot of choice. You’ve got specific use cases you want to address or specific needs. That means there’s probably a software for that or an app for that. What it also does is it really forces those of us in the industry to continue to innovate and differentiate. There’s no room for complacency in this industry because one it’s growing so fast, and two there’s other technologies that are on the sidelines like we talked about remote learning and augmented reality and virtual reality and digital twins. There’s lots of exciting parts coming into the industry that is going to force those of us that are playing in this space to continue to really innovate and move forward and stay relevant. I think that’s great for the industry and also for us. I’d say for Illuminate specifically we have a really significant road map that we’ve built up over the last few years of new developments that are driven by industry trends. We’ve talked about some of them. That’s also been driven by consolidation in the market of players who have come and gone and just a lot of customer feedback so based on that and there’s a ton of white space in the future for this type of software and all that’s going to do is continue to serve customers to have way better choices and produce better product in the future. I think we’re still in our sort of junior stages. If I think of that to our dogs we started our talk with, We’re not puppies anymore we are young adult dogs and I think there’s still a lot of growth and excitement to happen in the industry and I think Illuminate will be a great part of it going forward.

JIM: That’s great thanks Mike. I’d like to thank you for taking time in your day to chat with our audience. If some of the people out here have some questions how can they get in touch with you?

MIKE: Sure, so two things. We called the product Illuminate that’s actually Illuminate Manufacturing Intelligence so if you go to you can find more information on this there and if you want to reach out to me directly it’s or you can reach me on my cell at (519) 694-8666 or of course via LinkedIn. Any of those will work but yeah, it’s been a pleasure and thanks for having me on!

JIM: you’re very welcome. if you like this podcast please rate us wherever you pick up your podcast, five stars means a lot to us but more importantly tell your friends about it, send them an email. You can tweet us at the hashtag robot nation podcast and if you’d like to get in touch with us our email address is If you have an idea and an interesting company or technology and you’d like to be a guest or nominate someone to be a guest please get in touch with me by sending me an email and we’ll see you next time. Thanks for listening be safe out there! Today’s podcast was produced by customer traffic Russian industrial marketing and I’d like to thank my nephew Chris Gray for the music Chris Colvin for the audio production my partner Janet and our partner a 3D Association for advancing automation and painted robot who hosts our site and integrates zoho into

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