Emerging Technologies Roundtable: AR for Engaging With Your PLM Data
00:10 Welcome to the Emerging Technologies Roundtable. I'm joined today by Mike Campbell, EVP and General Manager of Augmented Reality, and by Kathryn Kniker or CK, our EVP and Chief Strategy Officer here at PTC. We're here to discuss how companies like yours can and are leveraging their PLM data across the entire enterprise to improve the speed and quality of their operations. Now, before we dig into how PLM and AR can be used together, Mike, can you help us understand just the basics of AR?
00:40 Sure. I like to compare AR, augmented reality, to virtual reality. In virtual reality we immerse ourselves in a completely different place with a six sided box and see digital content. With augmented reality, we're actually augmenting digital content in the context of the physical world where we often do work. This is especially relevant in the industrial enterprise, and PLM is a great source of that digital content that we would be leveraging in AR across a broad variety of use cases.
01:13 For sure and there are a broad variety of use cases. If you look across the entire product value chain, from engineering design reviews to manufacturing to sales and marketing to customer operations and service, augmented reality is widely applicable across the value chain, which really doesn't happen very often. When you think of a technology that has broad applicability and pretty much equal applicability across the value chain.
01:45 PLM data really enhances the richness of the AR content that you can create. Absolutely. So we always say if your product is at the center of value that you're delivering to your customers, there's lots and lots of data that you create in engineering that gets stored in PLM that can be used in all of these use cases. Think about engineering bills and materials and configured CAD models, PMI data, model based design data, control characteristics, all of this data that we control in PLM
02:19 and we manage, version there, can be used in these use cases. Can you talk a little bit about that? Yeah. If you approach the question from an AR perspective the very first question is with what shall I augment reality? What is the source of content? And in the industrial enterprise, one of those answers, the top answer is absolutely PLM data. And let's just double click into some of the use cases. If we think about in engineering, we want to do a design review.
02:49 We want to make sure we've got exactly the right information so that we can visualize the design at scale relative to some other physical reference point around it. It's even more important further on downstream when we get into things like manufacturing. As you maybe heard in the episode today, there's lots of applicability of AR in inspection use cases, in assembly use cases, lots of activities on the shopfloor where it's absolutely critical that we have the right source of information,
03:20 that it's the right revision, the right configuration. And if we do that we're being more efficient, we're minimizing scrap, we're minimizing rework, and we're driving product quality right up. And then the same is true further on downstream out in the field. If you're out servicing a piece of equipment, we have lots of customers that are challenged because they've got an incredibly broad portfolio and they've recognized that leveraging AR can help
03:50 them familiarize or guide the technician out in the field. But that's only valuable if the information is correct. So having that tie into PLM, that connectivity, being able to pull that digital thread is just hugely valuable. And huge out in the field in service, where you have the least amount of support. So to have that configuration data that's exact to that machine is enormously beneficial to a service tech who is out
04:22 alone trying to service the machine, and it avoids truck rolls. Just the efficiencies that industrial companies, or those that provide service to those devices, is incredible. I would just say that, of course, your point around applicability across the value chain is spot on. But the data would suggest, based on what our customers are actually doing today, that both service and manufacturing is where they're achieving a tremendous amount of value.
04:53 To your point right there. And if you think about it, that's where the physical world and the digital world really collide head on. Right? That's where I need the right relevant digital information in the context of the work that I'm doing right now here in the physical world. So it's a great point. So, I mean, there's lots of opportunities in engineering, but to your point, Mike, in manufacturing and in service. Even in service, there's a shortage of field technicians that even makes it more important to be able to have really trustworthy
05:24 work instructions, kind of in real 3D, versus the way it's done now. So all that being said, there are tons and tons of opportunity. Where do you start? How do you get started? It's a little bit of the curse, right? With this broad applicability, you look at it and say I can't do anything. I think the key activity is to go through an exercise and identify high value use cases that are going to make a meaningful impact on your business that you are technologically ready to address.
05:56 Now, in some cases, I imagine most of the audience here has a good PLM system and has a robust, let's say, collection of digital data to leverage. And then there's the question of technology readiness on the AR side. Right? It's easy to imagine all of the things that AR can do. The good news is that PTC, we have a strong point of view on what AR actually can do, what it's technically ready to do today, and where we can drive meaningful value. So step number one is absolutely, let's work together and get focused on a particular use case.
06:29 The good news is at PTC, we've got a proven method for doing that. Through our value workshops, we go through discovery, we make sure that we're mapping that value to the technology and then go off and set our sites on a target and then fulfill the promise. And I would say, just to completely agree with what Mike just said, COVID has accentuated employee shortage. And so therefore on demand training, really training up and skilling up
06:59 employees isn't just a once a year activity, it's an ongoing activity. And so it has increased one of the use cases where this rich PLM data could be very useful. But I agree with Mike. Look at your particular situation and figure out what's the highest value, and we can help you with what's the highest value and go from there. Those are all really good points, but I'm wondering, are there any just characteristics of use
07:29 cases that you should look at versus specific examples? What characterizes a good use case that people should look for? Yeah, it's a good point. The most valuable scenarios are cases where I would say there's variability. So that variability might be in the products that you're working on, a product with many options or variants, that's somewhere where AR can add a lot of value because it's providing the right information specific to the unique configuration that you're working on.
08:03 Another element of variability is variability in the workforce. If you've got new people that are coming online all the time. We've talked with customers recently that have 40% turnover. So in addition to the challenges around COVID, there's the aging workforce, the retiring folks, all of those kinds of things. So when you have this element of variability in your workforce, they need to be educated, right. They need to be informed about what needs to be done for a particular version. So those are some characteristics that come to mind for me.
08:34 I would say, Kevin, there's probably one other, which is the high cost of failure. So whether that's a really expensive piece of equipment or in a process that is high cost, if the process goes down. So those are two other things to look at to make sure there are really good places to find use cases because you probably have the opportunity to save a lot of time and money and be much more efficient in your overall process.
09:05 And these are not exclusive, right? I mean, we've got an example in our customer experience center in Boston where we have a highly configured product. It's an automotive engine. So there's variability in the design. And the use case that is being pursued is quality inspection, end of line inspection. So you can imagine being a QA Inspector. You're getting engines off the line all day long. Every single one of them is different, which means every single one of them has different things to be inspected.
09:36 And if that's not done correctly, or if you fall into the lull of just checking the seven common things and not the 14 unique things you've got a problem when that product goes out the door. So these characteristics can be used in isolation or they can mix and match and add even more value for sure. Lots of variability and high cost failure. So I mean, that feels like a pretty good place to stop. We talked a little bit about AR, but most importantly, what we wanted to discuss was just the value of PLM data and all these use cases enabled by AR.
10:06 I think we got that done. So, Mike, CK, thanks a lot for joining me for the conversation. Thanks Kevin, great to be here. Our pleasure. And thank all of you for joining us for this conversation today. Greatly appreciate it.