In this episode of Manufacturing Matters, Jason Baechler and Steve Pereira from Moritex Corporation join Winn Hardin and John Lewis to discuss lidar and its different implementations, including MEMS scanning, flash lidar, FMCW, OPA, and polygon mirror technologies. They discuss the unique challenges of designing and manufacturing optics for lidar vs machine vision, and go on to discuss the role of lidar in autonomous vehicles and industrial applications, as well as challenges like interference from other lidar systems and the need for sensor redundancy in certain systems.

Winn Hardin: [00:00:07] Hello everybody and welcome to a new episode of Manufacturing Matters, where we discuss the technologies and the trends that are affecting the automation market, general manufacturing, and everything that makes sure that manufacturing still matters here in the U.S. and around the world. Now today we’re here lucky enough to be with Jason and Steve from Moritex Corporation. How are you doing, guys?

Steven Pereira: [00:00:25] Doing well.

Winn Hardin: [00:00:27] Fantastic. Jason, Steve, Steve, why don’t you kick us off. Tell us a little bit about you and then kick it over to Jason and he can tell us a little bit about himself and Moritex.

Steven Pereira: [00:00:34] Sure. My name is Steven Pereira, sales manager for Moritex North America. I’ve been with the company for 17 years, handled the eastern U.S. and Canada, provide sales support as well as technical and engineering services. I have a degree in computer engineering from the University of Rhode Island, and I’m fascinated with optics and lighting design and implementation.

Winn Hardin: [00:00:57] That makes you a super-geek, Steve, excited about optics. Jason, tell us about yourself.

Jason Baechler: [00:01:04] So I also have a background in engineering. It’s electrical engineering, but I’m the president of Moritex North America, responsible for our business strategy and development here in North America and actually really the Americas. I manage also our sales, application, engineering, customer service, and support team in the region. I’ve been with Moritex almost 20 years now.

Winn Hardin: [00:01:28] Outstanding. Outstanding. Want to tell us a little bit more about Moritex and the market you serve and the products and services?

Jason Baechler: [00:01:35] Moritex actually was established in the ’70s, and we started out as an illumination supplier for machine vision applications and really moved into optics in the late ’80s, early ’90s. So today we’re one of the leading suppliers of lens and lighting components and integrated optomechanical solutions for machine vision and other imaging market verticals. And one of these applications is lidar, which is a little bit more recent due to the developments that have enabled that market. And overall we operate across the world and supplying our products that are mainly designed in Japan and then manufactured either in Vietnam or Shenzhen, China.

John Lewis: [00:02:22] That’s great, Steve. I haven’t met you before, but it’s really good to meet you. And Jason, I know you from my days as editor in chief at Vision Systems Design. And when we worked together there, I thought of Moritex as sort of a machine vision optics company. And can you talk a little bit about the work Moritex is doing in the field of lidar?

Jason Baechler: [00:02:47] Yes, yes, for sure. So actually, we joked internally that we used to be a semiconductor optics company because the majority of our products were telecentric lenses that were used for semiconductor applications, whether it’s coarse and fine alignment or metrology. But that market’s relatively volatile, as we all know. And so Moritex looked to diversify its product portfolio in the early 2000s. And we’ve really taken some organizational, let’s say, and also market opportunities to expand into certain areas, one of which is, as I mentioned, lidar optics. So Moritex today we design and manufacture lenses or other optical components and assemblies mostly for flash lidar. There’s a variety of different types of lidar that we can get into. So today we work with the different companies that are in the space in developing their systems from early on, looking at applications and help them to set their different requirements and then provide them different solutions and walk with them through the path to mass production.

John Lewis: [00:04:09] That’s interesting. I know when I was editor in chief of Laser Focus World, we covered a lot of topics on lidar. There are a lot of new and interesting technologies coming out, like FMCW. Can you talk a little bit about some of the different types of lidar and how Moritex is involved in those?

Jason Baechler: [00:04:29] Yeah. And actually I have a nice reference that I can use here if you give me one moment to share my screen.

Winn Hardin: [00:04:42] Before we jump into the technology types, let’s establish a little bit in terms of the importance of this assembly. First of all, Moritex’s background in optical assemblies, doing optical assemblies seems to well position yourself as a lidar supplier. And I think we’re going to delve into it as we talk about the different components and the design considerations depending on the application or the lidar solution that the specific customer needs, which is super sweet. But at the same time, for those who don’t know, lidar is one of the key sensing elements for autonomous vehicles, right? Whether it’s from Level 1 through 5. For example, Allied Vision shows autonomous vehicles growing from $76.13 billion in 2020 to $2.1 trillion by 2031, for a CAGR of 40%. Probably in every market in the automated imaging space, nothing has a CAGR like that. Not even close, right? So the autonomous vehicle market is exploding, and you say, okay, well lidar is just a small component, right? It’s just a small piece of that.

Winn Hardin: [00:05:44] But if we look at the lidar market, its growth just by it’s lonesome it’s going to go from $1.1 billion in 2021 to $7.8 billion by 2031, a CAGR of 21%, which is still awesome. Completely off the charts when we talk about that capabilities. And then, of course, lidar has been in the news a lot lately because of Elon Musk’s decision to try to get away from lidar, which I find incredibly ironic. I mean, well, he’s trying to depend on imaging systems for autonomous navigation of his cars. To me, the irony is that it’s my understanding that Tesla is still using lidar in all of their prototyping systems, so it’s safe enough for prototyping but not necessarily, you know, he’s trying to make the argument, which most of the market I believe is rejecting right now that somehow you can go completely autonomous without lidar. So I think it’s important for us to think about. Do you have just a general thought on that, Steve, Jason, in terms of does autonomy work without lidar in a safe operation?

Jason Baechler: [00:06:43] There’s a number of jokes that I’ll hold back about that.

Winn Hardin: [00:06:49] We do jokes here, man. We do jokes.

Jason Baechler: [00:06:50] We do jokes. Okay. Okay. I mean sometimes people just want to say things that seem to be breaking a mold or want to be controversial. But I think anybody with a practical . . . I mean look at the problem here. So we’re trying to create an environment with vehicles but actually, this relates to the bigger picture of our cities, our streets, where we have vehicles that are extremely safe. So some of the requirements for autonomous vehicles are just total pie in the sky compared to any other technology that was developed in the past, like airplanes. You know, we’re not concerned about 10% failure. We’re talking about 0.00001% failure and beyond. So, I mean, if you look at the practicality of that, you need sensor redundancy. So no matter what, you’re going to need different types of sensors, whether it’s lidar, radar, vision, FLIR. The answer is yes, right? As many sensors as you can pack into a vehicle to ensure the safety and security when you get to these fully autonomous vehicles or whatever they are, systems, we can look at forklifts, anything else. So, yeah, first off my high-level view is that there’s going to be sensor redundancy no matter what. And lidar has a lot of advantages versus some of the other sensor types. So I believe that definitely it’ll be used. Which applications and where, the market will work that out. But overall, definitely, lidar will be used in autonomous vehicles and in other systems.

Winn Hardin: [00:08:38] I wonder if at some point the National Highway Transportation Safety Administration, I think that’s the long name there, I wonder if at any point they’re going to try to tackle standards and say, all right, y’all, if you’re going to be driving on U.S. roads, you need this level of redundancy. You need something from Group A, B, C, D. It’ll be interesting to see whether . . . have you guys heard from your work whether there’s any efforts at the government level or federal level?

Jason Baechler: [00:09:04] From what I understand, there are efforts. We’re not as focused on that. We let our customers kind of worry about that a little more. We just look at it for market trends and directions. But yeah, there are some efforts, and remember, this is a two-way conversation, right? Not only does whatever’s moving need to have sensors, but also there’ll be fixed sensors on highways. And when you have everything that’s connected, then you have the ability to really control the environment. So yeah, I know that there’s efforts on the federal level and also certain states, especially Michigan, California, Arizona, that they have some efforts to regulate this. That might affect the CAGR and other details of the market more than anything else. But yes, I know it’s in progress, but I don’t know so much about it. I’m not an expert.

Winn Hardin: [00:10:00] But you know what? If we have to shave off two percentage points off 40.1%, I guess we’ll all survive. All right, back to the technology, man. You were about to start talking about the different flavors of lidar.

John Lewis: [00:10:13] I have a question that just popped up before we get into that. A lot of the conversation has been on autonomous vehicles on the road for moving people around. But in manufacturing, warehousing, and logistics, we’re seeing a lot more autonomous mobile robots, tugs, and forklifts and stuff like that. Are you looking into those markets as well as autonomous vehicles?

Steven Pereira: [00:10:39] Yeah, well, Moritex is focused on those markets as well. So similar to the same discussion between Elon Musk and vision versus lidar. The same is being done for autonomous forklifts as well. So there’s some companies that do vision for guidance and some that do lidar as well. Now in the mobile forklifts and AMR space, the advantage for vision is a little bit better because they’re able to get out of spaces that they’re not supposed to be in, whereas some of the other units, they get lost somewhere and then they have to completely shut down. Whereas vision guided robotics for forklifts, in specific where things are not supposed to be where they are, can help them get around and move around different objects that are there. But both spaces do use both vision as well as lidar and other type of sensors.

Winn Hardin: [00:11:40] John, you opened that door. I get to do a follow-up then. So, Steve, on the warehouse side, do you see that kind of as a shorter-term market where lidar sales or Moritex can expect to get greater traction and volume, even though the volume is nowhere close to getting Volvos. But is that a shorter term or do you see these developing apace, autonomous vehicles and warehouse forklifts?

Steven Pereira: [00:12:05] So it’s both the short term and long term. So it’s a big investment now in order to make it more safe in the factories. And so that’s where a lot more AMR and safety protocols are going to be in place, but it’s also long term as well. So whereas the roads are going to be safer and that’s kind of longer term, a safe and smart factory is something that’s here and now that can be achieved and rolled out in a quick way through the next five to 10 years.

Jason Baechler: [00:12:41] Yep. And the analog comparison you can give is, okay, autonomous vehicles, I know there’s the levels of autonomous driving and whatnot, but I think that the move from each one has been limited by different obstacles. So I think kind of we throw that out the window a little bit, let’s say, and just focus on getting sensors out in the market, right? So in vehicles, you’re talking about robo taxis, to move to trucking, to fleets and then to consumer-facing. So the safety regulations kind of get more difficult, and I should say the cost barriers for entry, like cost especially, but the similar thing is happening also. You’ll see them in warehouses, robots with lidar systems mounted to the top or back or front for seeing the general environment in warehouses, and then that’ll move along to grocery stores and other environments. So to the point where all this technology will be ubiquitous, but it’s the same kind of progress. And volume does increase as you go through each step. But also there are new challenges, especially when interacting with humans, right? More and more humans, when more safety is at risk.

Winn Hardin: [00:13:53] So you mean when I go grocery shopping, soon the dude who is parked right in the middle of the aisle and is completely oblivious, his cart is going to automatically move out of the way. Just made my day a little bit better.

Jason Baechler: [00:14:05] We’d hope so. More for the short term just it’ll help keep things on the shelves, so we don’t have to ask somebody for help.

Winn Hardin: [00:14:11] Damn it. I thought I was gonna have easier access to my ramen noodles or something. It’s the little things.

Steven Pereira: [00:14:18] Your Oreo cookies actually will be moving towards you in a mobile robot, so make sure that you don’t forget them.

Jason Baechler: [00:14:25] Product suggestions. Yeah, I like that.

Winn Hardin: [00:14:28] All right. I’m sorry, John. I’ll shut up now.

John Lewis: [00:14:32] Now maybe we should get into the different types of light technology and how Moritex is involved in those.

Jason Baechler: [00:14:39] So first I should say, just to remind everyone, we talked about some of the different details of the autonomous systems and markets. So we’re an optics company, right? So we’re dealing with the developers of these lidar assemblies. And let me share my screen here. I should have had this queued.

Winn Hardin: [00:15:06] So you mean everyone wants to do it slightly different? You got to be kidding. Seriously?

Jason Baechler: [00:15:09] Let me give you a quick overview of the different lidar technologies. Now, I should say, caveat, I borrowed pretty heavily from the internet and from presentations that I’ve seen on this. So this is not such an original slide, and also it’s put in order on purpose so that we start with MEMS scanning. So this is sort of the original technology that was implemented for lidar. In case you aren’t aware, this is coming from Velodyne, and their headquarters is about two miles from our office here where I sit in San Jose at this moment. But just a coincidence. So the MEMS scanning actually, these are the first products that you see in the market that are mounted to the tops of vehicles typically. And you have this scanning mirror system, let’s say, that’s imaging. And this is again the most common that you see now from Velodyne and other makers, but being replaced by other technologies that are a little bit later to the market but I think have a little bit better chance to be produced at an affordable cost and implemented in small-form-factor solutions. So what I should say is that first is all of these different technologies have some sort of emitter or a light being emitted that might be steered and then also a receiver. So this receiver is taking in the light that’s reflecting off the object. And then there’s computation that’s done in order to make decisions for a vehicle or just collect data. But so MEMS scanning is microelectronic mechanical systems is what MEMS stands for. But these are some of the original lidars.

Jason Baechler: [00:17:05] But flash lidar really has taken a forefront, a place in the forefront, because it’s based on different technologies that are used in different markets, right? So they can use a CMOS sensor that is not too different from a traditional camera. And then they have different light emission technologies, whether it’s lasers or pixels that also are used for other applications, including there’s flash-based lidar components that are in an iPad. So the volume that you get from these other applications will bring down the cost and make it more affordable for flash to be used in the market. But also there’s FMCW you mentioned, which is frequency modulated continuous wave, OPA, polygon mirror, which is also pretty common. These are in alphabetical order after flash, not in order of importance, but what we’ll probably talk the most about today is flash lidar, because we believe that it’s one of the best as far as technology and affordability and size for the markets. One key thing to highlight, though, is that the wavelengths for all of these different lidar systems or technologies are nonvisible, which is very important. So for vision-based imaging in a vehicle, you have a lot of challenges with the wide spectrum of lighting. You need these somewhat specialized HDR sensors, in some cases, high dynamic range sensors. And so in this case, we don’t care about any of the visible range light, and we can focus on narrow wavelengths and really improve, reduce the amount of noise and other obstacles that we might detect that we’re not concerned with here.

Winn Hardin: [00:18:56] How does that align with sun spikes? I’m just curious in terms of spikes on solar radiation, is that a consideration there in terms of the noise and interference you mentioned earlier?

Jason Baechler: [00:19:07] Sorry. Can you repeat the question?

Winn Hardin: [00:19:08] Yes. I was just wondering, how did those wavelengths relate to the solar spectrum and its effect on noise and uncertainty? Measurement uncertainty?

Jason Baechler: [00:19:18] So a lot of the flash, especially for flash lidar, we’re more familiar with. But in general, lidar systems will have typically a solar filter. So they’re actually filtering out a large part of the spectrum except for the wavelengths that are of interest. So in a traditional flash lidar setup, you’ll have, like I had mentioned, you have the transmitter and the receiver. The transmitter will actually emit a pretty already narrow wavelength. So you don’t need a filter. But on the receiver side, you’re taking in everything, right? So, yes, typically they’ll be mounted there or whether it’s the cover of the lidar assembly, there will be a filter to filter out those unneeded wavelengths.

Winn Hardin: [00:20:10] Cool. Okay.

John Lewis: [00:20:12] Are there concerns with lidar about interference from other lidar systems that may be either on the warehouse floor or out on the road?

Jason Baechler: [00:20:23] Yes. Yes. So very much so. And this is something that’s a bit of a challenge, right? Because if you think about it, it’s not just other lidar systems on the road, but they’re actually in a vehicle. Most likely there’s going to be different lidar systems assembled in that vehicle, right? So, for example, if you’re looking at a truck, where you need to stop from a really long range, because the size, weight of the vehicle and the velocity that you’re traveling. So you need to see way out in front. Well also, you’re concerned about someone walking around the vehicle or other vehicles that are next to you. So you have short range and long range lidar that might be actually in the same assembly. And they’re both emitting light, the same wavelengths. So not just of other wavelengths. So yeah, this is a major problem. A lot of it you can control this with certain optics or special optics that might eliminate light or cut light from different angles. Also, there’s computational algorithms for the lidar systems that can be used to identify, to try to make sure that the light that’s being collected and then the image that’s being processed is coming from, can be actually mapped out to the transmitter. So there’s different optical techniques that you can use to eliminate some of this, but a lot of it’s based on the computation.

Winn Hardin: [00:21:56] I would think as much as you could do in optics, you’d like to, right? Just to lower the computational requirements, power requirements. It’s a passive filtering mechanism.

Jason Baechler: [00:22:02] Yeah, exactly. You want to limit the load, and also it’s real time, right? For the most part, right?

Winn Hardin: [00:22:11] Latency is not an issue when it comes to light.

John Lewis: [00:22:14] Can you tell us a little bit about the difference from an optical design standpoint of designing optics for lidar versus for traditional machine vision and imaging type applications?

Jason Baechler: [00:22:26] Go ahead, Steve.

Steven Pereira: [00:22:30] Sure. Traditional machine vision optics are for general applications. So you’re going to want to have a flexibility in the amount of light that’s received or the F number, as well as the working distances and the fields of view that you’re going to have. Whereas in lidar, you’re going to have it specialized. So you’re going to have to specialize it for the different types of F numbers. Specialize it for the wavelength and also for chromatic aberration and other things. One thing that Moritex is very good at is mapping the different light waves and eliminating distortion or crosstalk, which is very, very important in lidar systems. And it’s similar but not exactly the same as distortion in traditional machine vision fields.

Jason Baechler: [00:23:21] And then you have the other challenges, right? Size is one thing. So we already talked about some of the challenges with MEMS scanning, where you have some large mirror or other polygon mirror applications. But in flash lidar, the assemblies, the target is to have the assembly be smaller than in a 2D, the business card. So think about, the lens has to be quite small. You know, actually the lens typically is the largest component of the entire system, other than the housing. But then cost, right? Because you know, the end production repeatability over high volumes. Machine vision volumes were, high volume  is 5,000, 10,000, maybe 100,000. In automotive, some of the high volume is millions, and so repeatability over high volume is really important as well. And some of that we designed into the optics.

Winn Hardin: [00:24:24] So Steve, back to what you were saying a minute ago. Steve, are you saying that when it comes to lidar systems, you actually have higher optical requirements, performance requirements than you do for general imaging applications?

Steven Pereira: [00:24:35] Yes, higher optical requirements as well as specialty requirements, reduction of stray light, and all of that. And they want it to be $20 or $10 and less. So, yeah, it’s a challenge, but there are different types of manufacturing techniques that we can use in order to reach those goals.

Winn Hardin: [00:24:58] Based on Jason’s point about how we need small package sizes, does that mean we have a smaller sweet spot? So kind of even though we’re having to manufacture these to tighter tolerances and specifications, the aberration-free section of the lens is actually much smaller. Is that a consideration at all when we’re talking about volume units?

Steven Pereira: [00:25:18] No. They want the best of everything, at the lowest cost.

Winn Hardin: [00:25:22] No?! Customers don’t want everything?! Free. Don’t forget free.

Jason Baechler: [00:25:34] We have another visual that we can show here. Kind of giving the quick summary. Steve you’ve already touched on a few of these, but sort of to Winn’s question, we talk about F number, so F1 is a very bright lens. Most machine vision, traditional lenses they’re going to be darker than that and they’re going to be used at a higher F number setting, which is actually a darker setting. I know it’s a little bit confusing. So anyway, so these lenses because we’re filtering out other wavelengths, we have a near infrared, typically near infrared or infrared wavelength that we’re transmitting. We need to collect as much light as possible. So that’s why think of F number and these things, it’s the angle of light or the amount of light that you’re collecting. So we want to collect as much light as possible, but at the same time, we don’t want stray light, right? So we don’t want light from other . . . this is what we mentioned. We don’t want light from other systems, from angles that are unwanted. And so we use different optical techniques and optomechanical techniques to minimize the stray light, because stray light then becomes either unwanted signal or noise, right? It can be looked at in the same way. And then for optics, we talked about already minimization or, sorry, reduction in size and cost. But then also there’s the environmental aspects. So anti-fog. You don’t want these things to fog up. You know, if you’re traveling at 70 miles an hour on a highway and you need to stop, you don’t want to not be able to see a car in front of you because there’s condensation in the optics, vibration, resistance. You know, these have to be stable over wide temperature ranges. And then of course we have to meet the different quality and repeatability, reliability, etc. requirements for IATF and other certifications.

Winn Hardin: [00:27:52] Thanks. Thanks, Jason.

John Lewis: [00:27:55] Yeah, I had a question about, you talked about MEMS and galvos and different methods of beam steering that are kind of used in some of these different types of lidar technology. Is flash lidar a solid state technology or does that have beam steering as well? Mechanical components.

Jason Baechler: [00:28:14] So John, you hit the nail on the head. Maybe what I should have said coming into all this. So that’s one of the biggest benefits, actually, from flash lidar and FMCW and these other technologies where you don’t have any moving components, like a mirror. So yes, solid state is the aim for all lidar systems, and flash lidar right now is the leader in being able to deliver an actual solid state product. I am aware there are different systems where they actually spin. They spin a flash lidar. But once the technology and volumes increase and cost goes down, you can stack a bunch of these in different systems. Then you don’t have to spin it any longer. Yeah, definitely solid state lidar is required. What I understand is that some of these spinning lidar systems need to be calibrated every year, two years. Whereas a flash system in theory without any accidents or other any other issues, you wouldn’t have to calibrate possibly ever, or it might be quite a bit longer, five, 10 years.

Winn Hardin: [00:29:36] That seems like a Pandora’s box. I know people who don’t change their oil for three years. You know, cars only last three and a half years. But that’s a side point. I’d like to follow up question if I could. You were talking about how right now in some cases flash is going to spinning to keep our component and our cost structure down, right? Even though it brings calibration issues and other things. Can you talk about how far are we from, based on with Moritex optics working with your downstream providers to develop a working assembly, working module, right? Where are we in terms of cost today to where we need to be for widespread adoption? And is there a path to get there, because squeezing manufacturing costs out of optics is not the easiest thing to do. I mean, physics is physics, right? So tell us the bad news.

Jason Baechler: [00:30:26] Yeah, you said we do jokes here, right? So as an optics company, we’re usually the ceiling when it comes to physics. You know, electronics can be developed quite a bit faster. And we have to always come back with the bad news in any system development because we live in the real world, fortunately or unfortunately, so I mean there is a path if you go to like CS and walk around, you can see different products that are being marketed for applications, like mounted drones. So these are drones that are only a couple thousand dollars. So the lidar assembly can’t be more than, I don’t know, $20, $50 maybe in such a product. So already for the low-end applications, it’s relatively affordable lidar. I think for vehicles, the path is a little bit longer because, again, we’re talking about long-range, most complex systems. So I’d say that there is a path, a lot of it comes with volume, and for optics using the different technologies we have and materials we have today, it’s a bit more of a challenge.

Jason Baechler: [00:31:51] But really what it comes down to is being able to design a product that you can then manufacture repeatedly, with repeated performance and quality, in a certain way so that you can keep costs down to a minimum. So there’s different techniques. I mean, some lidar lenses will be all plastic. They could be plastic and glass optical components with aluminum barrels. Could be plastic barrels with different hybrid optics. So yeah, there’s different techniques. I’d say again, for us it’s a bigger challenge. It’s not such a clear path. But on the electronics and other components, the path is very clear. If you look at CMOS sensors before and CMOS and the scalability and the cost reduction. So the other components, that’s why flash I believe will be the winner in all this or the leading let’s say of the lidar technologies because of the volume and scale of mass production that you’ll see in this space. But then also outside in adjacent markets.

John Lewis: [00:33:04] Yeah. I was wondering, maybe dovetailing off of that, if you could maybe talk a little bit about how Moritex prioritizes innovation and technology advancement within its business strategy. And what steps does Moritex take to stay at the forefront of this industry?

Jason Baechler: [00:33:24] So you want to know our biggest secrets? That’s all you’re asking for.

Winn Hardin: [00:33:27] That was actually going to be my next question, actually. If you could give us the financial reporting. I’m sorry. Just kidding. It’s a total joke.

Jason Baechler: [00:33:38] Well, in Japan we have to be quite open with our financials, so that part’s easy, right? I mean, it’s a difficult question. I mean, we could talk, have another podcast episode about this. But yeah for Moritex, one of the main things, and we really believe in this, is developing our people. When I joined Moritex 20 years ago, we had limited resources for optical design. Today we have 50 out of 450, 500 employees depending on cycles. We have 50 opto and optomechanical engineers. So we have a high number of engineers at the company. We really invest in these engineers and the different tools that they have and the education that they have. Speaking of tools, we also invest in different software technologies that allow us to design and simulate the performance of optics. So really, really focused on that side of things. But of course, then you have to research materials because that’s one of the key paths to mass production and affordability or for lidar sensors. So it’s cast a wide net when it comes to development and improvements. But we do invest quite a bit in the education and also software resources at Moritex. And in addition we have different manufacturing sites and manufacturing capabilities. So we have invested quite a bit to expand, build our own equipment for assembling lenses and optical systems. So yeah, it’s a multi-pronged approach here. It’s not such a simple answer. I hope I addressed the question adequately.

John Lewis: [00:35:41] Sounds good to me.

Winn Hardin: [00:35:42] Definitely. Yeah, I was going to go a little bit more. My question was going to be slightly easier, so you wouldn’t have to give the full spectrum of response. But I was simply going to say at a Moritex lidar division, can you tell us something that’s coming? Can you tell us something that we should look for over the next six to 12 months or areas of improvement that we should all get excited about?

Jason Baechler: [00:36:05] Yeah, the answer’s no. I can’t tell you. I would love to, but this is the beauty on some level and also one of the other challenges for us as a lens manufacturer is that, like I mentioned, and I joke with Steve quite a bit is, we’re not integrating the sensors and the optics in a lidar system, and we’re also not integrating that system into a headlamp for an autonomous forklift. And we’re not making the forklift. So we’re stages down in the supply chain, right? And so you probably won’t see anything from us necessarily. But for us, for Moritex, the approach is we’re enabling the success of our customers, who then can enable the success of their customers and then enable safety and improvement of quality of life, all those other things. So that’s the funny thing about the division. We have no standard products, but someday your life might be saved by a product that does include our lens. So, yeah, going back to actual standard products, we do have, as Steve mentioned, we do have lenses that are off the shelf that are used for autonomous systems, and I think the idea is that we’ll feed back some of the technologies that we’re developing for the lidar products into these custom lidar products, into other lenses and components that we sell as standard. Like we have traffic-designated lenses that are color-corrected over the visible and near infrared ranges. You know, they have our logo on it, and you might see them in a camera system that’s mounted in a traffic environment, maybe checking speeds or looking at license plates. So it’s kind of passing that technology that we develop on the high end down to the low end is really where you see the output from the lidar division.

Winn Hardin: [00:38:27] In many ways, the same way, Steve, that your past work in electronics, one of the most challenging machine vision end user industries in the planet, has helped to improve your general machine vision optics line. I mean some of that transfers even though, like you say, those of us in the peanut gallery may not be completely aware of what the small little parts are, whether it’s for DFM or whether it’s a design innovation or material enhancement or whatever it might be.

Steven Pereira: [00:38:54] Uh, yeah, for sure. So we’ve been designing optics for semiconductors and optomechanical components for a while, and we haven’t even integrated some of our optics into wire bonders and different things that you wouldn’t know until you open up the machine. But we do have that as well. And vibration resistance is very important. So we’ve had that capability for a long time, and now we’ve passed that on to our standard products, where you can get a CCTV lens that matches up with one of a low-cost sensor, has good image quality and vibration resistance, and is at a very good marketable price, and matches the industry standard. So you’ll see that as well.

Winn Hardin: [00:39:40] I think the next time we have you guys on, we need to get someone from Luminar or someone else at the assembly level so that they can give us insights from that. And then you can just look over and say, can we talk about that? That’d be cool. But there’s a lot more to talk about, especially in the nuance in terms of the material choices. I have a feeling, as John alluded to, there’s a ton of innovation that’s going on. Hybrid lenses, whether it’s plastic material, barrel, glass, all the different IR, AR coatings. But as to your point in terms of the engineering growth you’ve got there, that also speaks to how much I think innovation you guys are putting in and how much you believe in that marketplace. Since I suspect lidar you’re expecting to be a good growth market for you in the future without getting into specifics. Fair statement?

Jason Baechler: [00:40:29] Yes, very fair statement. That’s why we would create a division specifically for autonomous systems.

Winn Hardin: [00:40:37] I like to make observations about the obvious as much as possible. I’m in marketing. Steve, Jason, it has been a super pleasure for you to join me and my associate John Lewis today on Manufacturing Matters. Really want to thank you for your time. Thanks for sharing your info.

Jason Baechler: [00:41:00] Thank you for having us. You know, it’s great to have known you guys in the industry and also to work with you here and try to contribute to get the word out on the technology. So I appreciate what you do and thanks for having us.

Winn Hardin: [00:41:15] Our pleasure, everyone. And to our viewers out there, thanks for joining us on this episode of Manufacturing Matters. Be sure to check out our past episodes. You can find us on manufacturing-matters.com or any of your favorite podcast platforms and social media. And until our next episode, remember that manufacturing still matters here in the U.S. and around the world, and we can’t wait to meet you again. Thank you.