Techniques for Enhancing Battery Quality Control by Eric Moch from Glimpse

Episode Overview

Episode Topic: In this episode of Skeleton Crew – The Rad Tech Show, we joined with Eric Moch, CEO and co-founder of Glimpse. The focus is on the innovative use of X-ray and CT scanning technology in battery production, specifically for quality monitoring. Unlike traditional medical applications, Glimpse leverages this technology to inspect and ensure the quality of battery cells, a crucial component in numerous industries, from electric vehicles to power tools. Eric explains how Glimpse is transforming the high-volume battery production industry by making CT scanning a scalable, factory-floor solution, addressing the challenges and opportunities within this rapidly growing field.

Lessons You’ll Learn: Listeners will gain a deep understanding of how advanced imaging technologies like X-ray and CT scans are applied in non-medical fields, particularly in Battery Production for X-ray Tech. Eric Moch discusses the importance of quality control in battery manufacturing and how Glimpse’s technology helps identify latent defects before they cause significant problems. You’ll learn about the different types of battery cells, the challenges of high-volume production, and how integrating advanced scanning technologies can significantly enhance product reliability and performance. This episode provides valuable insights for professionals in the battery industry and those interested in technological innovations in manufacturing.

About Our Guests: Eric Moch is the CEO and co-founder of Glimpse, a pioneering company that utilizes X-ray and CT scanning technology for battery production quality monitoring. With a background in engineering and experience at Tesla, Eric brings a wealth of knowledge and expertise to the conversation. His passion for improving battery technology and his innovative approach to using CT scanning in high-volume production settings have positioned Glimpse as a leader in the industry. Eric’s insights are not only informative but also inspirational for those looking to understand the future of battery technology and quality assurance.

Topics Covered: The episode covers a wide range of topics centered around Battery Production for X-ray Tech. They discuss the distinction between different types of battery cells, the scale of production, and the specific challenges faced in maintaining quality at such high volumes. Eric explains how Glimpse’s technology addresses these challenges by providing detailed insights into the internal structure of batteries, identifying defects early, and ensuring long-term reliability. The conversation also touches on the potential future developments in battery technology, including new chemistries and applications, and how these advancements can benefit from improved quality monitoring techniques.

Our Guest: Eric Moch- Leading the Way of Battery Production for X-ray Tech at Glimpse

Episode Transcript

Jennifer Callahan: Hey, everybody. Welcome back to an episode of The Skeleton Crew. I’m your host, Jen Callahan. And tonight, my guest, Eric Mok. He is the CEO and co-founder of a company called Glimpse and his company is using X-ray and CATL scans to not deal with anything medical related or body related, but they’re actually doing it for quality monitoring of, batteries. So he’s going to share with us what his company does and kind of how he got into this field. So, Eric, thanks for taking the time to be with me tonight.

Eric Moch: Thanks for having me.

Jennifer Callahan: My pleasure. I’m excited to get into this conversation with you, because right before we started recording, Eric had shared with me that he actually knows one of my previous guests, Leonard, who he was from, doing something similar to what they were, how they’re using X-ray to, make sure that the quality of, of different, case models were doing well, so. It was interesting to know that we shared a common thread there and I didn’t even know it. But Eric, why don’t you start with us about Glimpse and, give us a surface of what you guys are doing right now?

Eric Moch: Yeah, absolutely. maybe before I dive in, I thought it might be helpful to, explain the audience. I’m guessing not everyone is familiar with the battery industry, so let me take it from the top. I think when we talk about batteries, there’s there’s sort of two types of batteries. There’s the battery cells. It’s also called primary batteries and then the battery packs, also called secondary batteries. So battery cells are sort of the smallest unit of energy storage that you can buy and cells come in typically 3 or 4 factors. So you have the cylindrical cells. Those think of it as triple-A batteries on steroids. Still beefier and bigger. Then you have the pouch cells. So pouch, think of it as like a thin sheets. and then prismatic, prismatic look like, big metal bricks essentially. And so you have those three form factors and those are cells. A battery pack is made out of multiple cells. In a car, you typically have a few hundred up to a few thousand of those cells. and so I just wanted to have the distinction here Glimpse, our company focused on the cell level, not at the pack level. There are folks that scale entire packs, but you need much bigger equipment. And I think it’s sort of a different use case. Okay. With that being said, yes, we use X-ray CT scanning, for essentially harnessing insights from, those batteries gather insights for our customers.

Eric Moch: I would say that this is a fairly well-known technique in the industry. but it’s been a luxury instrument. It’s been a very slow, low-volume, inspection techniques that typically live in a lab and is operated by scientists. typically folks would scan a few cells a day, and then sort of really deep dive into those, into these data sets to then generate some conclusions at the lab level, maybe for new designs, failure analysis, etc. But when you look at the battery industry, it’s a very high-volume industry. So a typical factory that produces those battery cells, will produce, 200,000 per day, up to a few million per day of these battery cells. So you kind of have a discrepancy here where CT scanning is a very valuable technique, very insightful. But on the other end of it, you’re trying to apply these techniques to a very high-volume industry. So we created Glimpse, sort of resulted that discrepancy and take CT scanning from the lab into the factory floor. In order to do so, obviously you have to scale it by several orders of magnitude. And so that’s kind of the mission of Glimpse, is to democratize CT scanning so that you can make it a high throughput tool for the battery inspection industry.

Jennifer Callahan: Okay. What types of companies would you be working with that would be scanning their cells?

Eric Moch: Yeah. Any company out there that, deals with batteries, battery producers and battery buyers typically are the two sorts of large groups of customers we deal with. So battery producers, the biggest in the world, are Panasonic, LG, Samsung, in China, you have a lot of those. the largest in China is CATL. So those produce the battery cells. And then the buyers are, honestly, so many different industries. Obviously you have the electric vehicle manufacturers. So think of, I don’t know, BMW, Ford, GM, etc.. But you have the power tool industry obviously uses a lot of batteries. In a cordless drill, you have many batteries. And so think of Black and Decker Milwaukee tool and then satellite company, small domestic appliances, etc. So these are two types of customers, the people who produce batteries and the people who buy those batteries.

Jennifer Callahan: So you were talking about the automotive industry, I thought it was interesting that you and one of your co-founders both used to work for a large, name. I don’t know, is it okay for me to say it?

Eric Moch: Of course. Yeah. Of course.

Jennifer Callahan: You used to work for Tesla. and that’s where you met your other co-founder. so how did you guys get to talking and, figure that you kind of wanted to leave that business and, start into your own direction with the batteries?

Eric Moch: Yeah. Peter Attia, is our CTO, and Peter and I met while we were at Tesla. We had somewhat different roles there, but we were obviously working very closely on the engineering side of battery cells.

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Eric Moch: I think it’s just a realization that CT scanning is really a super insightful technology. It’s used across the sort of, the development cycle of a battery cell. So all the way from R&D to prototyping to mass production to failure analysis, if and when the battery fails. and and because we realized that it was so, useful, we wanted to make it ubiquitous in the industry. and so that’s kind of where the idea came up and we started thinking about, okay, are there any like, physical limitations to scaling it, and what are the reasons why it hasn’t been scaled so far? And so we decided to start Glimpse to sort of, open up that capabilities for the entire industry.

Jennifer Callahan: Okay. do you work with Tesla currently?

Eric Moch: We’re not at liberty to share, sort of which customer we work with. Unfortunately, I’m not able to comment on that.

Jennifer Callahan: That’s all right. No problem. so I was looking at your site and reading, to see, how you’re starting and finishing. and the different, businesses that you guys are doing. It was interesting that you said, that a battery might be working fine when you first get it, especially in a car, because you had the site mentioned, that it could be working for several thousand miles, 100,000 miles, and then all of a sudden it it dies because there is a defect within it. so the CATL scanning of it could detect something like that before it’s even put into, say, a car.

Eric Moch: Yeah. Great question. and I think that’s a very that’s somewhat of a subtle point, but a very important one. Essentially, if you think of a battery, as a system, it’s a very, technically nuanced system, and it’s almost like a living organism. And, just like in a human, if you have a stage-1 tumor, you can do a bunch of tests where that tumor is going to feel invisible. You’re not going to pick up on any signal. If you do a blood pressure or electrocardiogram or, sort of heartbeat to measure your heartbeat, you’re not going to you’re not going to see any, stage-1 tumor out there. But if you do an MRI or a CATL scan, it’s going to be very obvious. Right. And so it’s this idea that in batteries you have a whole family of defects that we call latent defects, meaning that they haven’t materialized yet into a measurable signal. And by signal, I mean electrochemical signal. Right. So you apply a voltage to the battery and then you read the response. so that defect is going to be invisible. It’s going to have zero electrochemical signatures. But it’s there and it’s latent. And if you keep using the battery using a battery means charging it and discharging it. Right. You drive your car, you charge it, you drive it, you charge it, and you cycle through the battery charge and discharge. eventually that stage-1 tumor is going to develop into a stage-4 tumor and is going to create real issues. And by the time you can actually read that issue, from an electrochemical standpoint, it’s too late. You have to change your entire battery. So that’s why CT is so relevant because you can catch those defects before they actually become, perceptible.

Jennifer Callahan: Okay. so the CT, I mean, just thinking of it from a medical standpoint, it’s cross-sectional anatomy that they’re looking at. I’m assuming that the CT scans for the batteries are the same. Same why? You’re doing, like, coronal and sagittal, sections? I mean, you might possibly be using different words. I’m not really sure.

Eric Moch: I guess we came up with what we thought was the most obvious, orientation. But you’re absolutely right. We’re essentially slicing the batteries in multiple directions. This sort of different orientation depends on the geometry of the battery. So if it’s a cylinder versus a rectangle, we slice it in different ways. But basically we want to capture as much of the information as possible, while sort of minimizing the data size. So we try and slice it intelligently so that the user gets as much information as they need while not carrying, hundreds of gigabytes of data around.

Jennifer Callahan: Okay. so these defects that are detected, I’m assuming it probably comes up in some type of number form, but are there images that are related to it that you can see that, is there like a crack inside of the battery or what?

Eric Moch: Sure. So that’s a family of sort of latent defects. come in different sort of shapes, and sizes, cracks, tears, sort of, bumps or pinholes. what else? Wrinkles. So, batteries are made out of electrodes. Sometimes, those electrodes will sort of fold on themselves or have wrinkles. for the particles. so a different sort of, typology of the effects. But most of them, if not all of them are observable by CT.

Jennifer Callahan: Okay, cool. So you guys have started in this? and what’s the development in the manufacturing of batteries that you feel, might be moving forward, that might make batteries possibly better?

Eric Moch: I think, I mean, this is a self-serving response, but I think better quality control, will help the industry overall. so that’s, that’s kind of the mission that we have at Glimpse. More generally speaking, I think there’s there are different chemistries, that are being developed or even industrialized, that I’m excited about. So we talk a lot about lithiion. This is another chemistry that has been developed over the past few years called sodium ions. So essentially you replace lithium sodium. This is a bunch of different changes in your sort of battery cell design. But, it’s got different trade-offs. So you know what is good for high energy density? and a long lifetime. The other is good for, a sort of lower energy density but lower cost. So it depends on your application. But I think people are developing those new recipes, and we can really hone in on a different on a given application. And by application I mean energy storage applications. So for instance, an EV is going to have different energy density and power requirements than, a grid battery that sort of pairs with a solar, solar panels where you want to store the, the energy that’s harnessed from the sun and you want to distribute it at night, for instance, those, have different needs. And so you can sort of tune, the chemistry for those different use cases. And I’m very excited about that because it sort of shows that the industry is maturing for various applications.

Jennifer Callahan: Right. And then the CATL scan can be used, for these future development of batteries that’s going on.

Eric Moch: Absolutely. We’ve, we’ve, sort of proven to ourselves because obviously the, we sit here a lot of times there’s only one way to find out. You have to scan the object and confirm. But yes, we are sort of chemistry agnostic, and we can produce the same level of image quality and generate the same level of insights, regardless of which chemistry you’re talking about.

Jennifer Callahan: I was, always doing some reading before I met with a guest. And, Eric and I were discussing, some of the other people that are on his team, and he had, although this isn’t technically radiology related, what they’re doing? they do have someone on their team who was part of the imaging science and worked in AI for, one of the larger companies out there, for imaging. How do you guys utilize, the AI portion of his background?

Eric Moch: Yeah. So, I think you’re talking about Jim. Jim had an extensive career. He worked with Keystream before, which, is a CT, company, for medical applications. Right, right. And, I think we have a lot to learn from the medical industry. I think the medical industry has pushed, the sort of full suite of hardware and software technologies pretty far. The consideration is a little different because when you scan a human body, you want to sort of maximize your signal while minimizing your dose of X-ray. Right. you care less about scan time. In the sort of battery industry at least, where you care about is throughput. So you want to scan as many parts per minute as possible, and so you care much less about the total dose that’s going to go through your battery, because that, X-ray up to a certain energy level will not, alter your battery. But what you care about is really going through as many products as possible. And so you can really go hard on sort of the X-ray dose. So those learnings will have to be translated and sort of refactored. But I think Jim is, is bringing a lot of those learnings. And yes, he has extensive experience in computer vision. and he’s sort of helping us build our technology from that standpoint.

Jennifer Callahan: It’s interesting how, you would think that two fields kind of aren’t related, but they are.

Eric Moch: A lot of the building blocks are. And again this slightly different equations to solve between those two fields. But if you solve that equation in the prior field you can and you understand how you did that, then you can sort of apply the same recipes and then apply your knowledge to the next industry, which is what Jim is doing. And it’s been really, really helpful for the team for sure.

Jennifer Callahan: AI mean, I’m sure he’s helping you, overcome some different challenges. what challenges in general, have you guys met since the start of the company?

Eric Moch: Oh, that’s a good question. what challenges? Haven’t we met? I think no, honestly, it’s been it’s been really. Well. Really well, I think the typical startup challenges, how how do we scale? How do we make the right decisions? I think especially over the past couple of years, startups have had to shift from growing as quickly as possible to actually generating revenue as quickly as possible. And even turning a profit, or at least proving that they can turn a profit. so typical challenges of startups. How do we go to market as quickly as possible? How do we generate revenue as quickly as possible? so that’s been one on the on the technical side. I think so we’re mostly a software company. We partner very closely with, hardware vendors. so, key vendors, we are not building CG ourselves. We are partnered with the hardware vendors. And so I think one of the challenges, was, finding out who are the best players to partner with and who are who are the what is the best portfolio of hardware that we want to integrate our software onto. So that’s been an interesting challenge. And I think we feel pretty good about where we are today. But obviously it’s going to be continuing because we’re not producing our own hardware. It’s going to be the constant question of, where the right partner is and what are the right technological choices that, they need to make to sort of work with us.

Jennifer Callahan: I think that’s a challenge, in all fields that are using, different technology. even I, I’m in a hospital and we’re putting in a new room and, they’re trying to figure out who is the best vendor to get the new machine from. So, I mean, that that same challenge that you have, I feel like is met across the board, in a lot of different areas. For people who are moving forward, in battery manufacturing and from the different scans that you’ve done, I mean, what would be your suggestion for them to help for the, better quality monitoring or to, I guess, not to say fix it before it happens, but, maybe a different quality control within within the factory. Have you ever thought about that?

Eric Moch: So, I think, for folks who are joining the battery industry, if I understand your question correctly. So sort of battery engineers, that will, consume CT data one way or another, I think, trying I’m trying to give tips that are not too self-serving, but obviously, we’re very biased here, but but I think, realizing that it is a very powerful tool. But, if you use it well, you can generate a lot of data per unit of time, say, per day or per week or per month, and then sort of data management becomes a bottleneck. Right. And if you’re a battery engineer, it’s not the case for every bad engineer, but it mostly most likely you’re you’re not a data scientist or you’re not a data engineer. Right. And so how do you do your job without being overwhelmed by the amount of data that a technology as powerful as CT generates? And obviously, Glimpse is doing a lot of work there so that battery engineers can focus on building better batteries without actually having to deal with, hundreds of gigabytes of files per day or every day. so that that’s one thing is sort of getting your making sure your partner with the right company so that data is not a bottleneck, to your work. And then, I don’t know if I’m answering your question directly, but another thing that we’ve seen in the industry.

Eric Moch: So for. In the battery industry. I think CT scanning again, there’s a consensus that it’s a powerful technology, but we see a lot of folks, making mistakes when they select the equipment. So we’re kind of going back to the point you made or the reflection that you had, buying the wrong piece of equipment. because I think a lot of city vendors are really good at marketing. They all are seeing this battery market as a very exciting, huge, growing market. And so they obviously want to want to want a part of it. and but if you’re, if you’re, purchasing or sourcing a piece of equipment like this, you need to put a lot of thought into what are you trying to do with it. And I think that’s what we did, a Glimpse. So I would say, open invitation, come talk to us. We’re not this is not just necessarily selling something. This is actually to help you if you’re purchasing equipment, whether you’re actually going to use our solution on top of it or not. talk to us. We’ve visited a lot of different vendors and we understand what makes a good CT scanner, and what makes a bad city scanner specifically for the battery industry. And we’re happy to share, those insights with you because it’s in our best interest that the industry choose the right set of equipments.

Jennifer Callahan: Have you guys since, you’ve been open and doing the scanning for the different types of batteries. have you had, like, a significant moment where you know that you’ve made, like, a difference? Like, that you’ve had a customer come and say like, wow, like the feedback that we got from you from the different scans, like, really made a difference. We’re going to go back and look at maybe at the way that we produce the batteries or something like that ever happened. Like a, almost like an aha moment, like for them really not for you.

Eric Moch: Yeah. Absolutely. yes. And we’re very proud of that. So, we just launched our product about two, two months ago. and we’ve been lucky to acquire a number of customers since then, and some are very large customers. And we’re obviously very proud of, working with those large customers because these are renowned and well-respected companies. But I think personally, my proudest moments were when we were working with startups that, cannot afford to, put half $1 million into a piece of equipment. And have them sort of the low end. Right. It can go up to a million, a million and a half, and they’re just not there yet in their journey. But they still need to check on their progress. Right? Is the battery that I’m designing is well-built? Does it have defects? Is it going to behave well, what’s the lifetime of the battery, and then how does the battery deteriorate over life as I’m charging and discharging it? And really, in order for them to acquire those insights, they either have to purchase equipment and it’s not just purchasing it, but it’s staffing it and then, running it, etc.

Eric Moch: Or they have to spend a significant of money for a couple of scans here and there. And so what we’ve enabled with, a Glimpse is really a low cost, high, high image quality, high resolution, CT scanning on-demand service. So you send us the batteries, we’ll scan them for you, and then we’ll send them back. and, instead of sending us 1 or 2 battery cells at a time, they send us, tens, 50, or hundreds of batteries at a time. And so suddenly they have access to all this information. And obviously we package it in a way that is very user-friendly and without, mentioning names. There are a few startups out there you could tell they learned something they didn’t know, and they got sort of some information about, things they need to care about. They didn’t care about it before. And I think it’s I was super proud because. In a way, we’re sort of doing our job in helping the entire battery industry. in the US to sort of, mature. And I think it’s, it’s it’s super cool.

Jennifer Callahan: I mean, from a person who uses batteries, I’m sure, just like you do. I mean, I have kids at home and, we’re always changing batteries and stuff. There’s nothing more frustrating than when your batteries die, you’re like, oh, I just changed this. Like, I don’t know is that if that’s a quality issue, from something that we’re discussing. But I mean, it’s frustrating with batteries in general. And I’m just talking about how household batteries are expensive. I mean, we want to make sure that what we’re buying is quality. yeah. I do want to go back to how you said, how many they send you, to be checked on. The people who were asking, to to send their batteries to you, to be checked. do they send them in batches from like, say like, they just produce, say 500 batteries at once? do they take, like, a small portion of that, maybe say, like like you said, like 50? They take a portion of that 50 and they send them to you for them to be checked.

Eric Moch: A great question. so the answer is yes, but not only so there are many different use cases that we see from our customers. Some of them, just like you said, have a small pilot line and they’re producing sort of batches in small quantities. The fiber itself is a small quantity in the battery world. Right? and they want to make sure that their production run or their pilot run went well and that they’re built according to specs. Right. And so the user services and they can access that data very quickly. other folks are sourcing batteries because they’re building, I don’t know, electric bikes or, new types of, scooter or you name it. And they want to make sure that the quality they’re getting from their suppliers is good, right? Or maybe they’re trying to downselect between three suppliers. And so they get three batches of batteries, and they want to make sure that sort of build quality is one criteria that they use to select their supplier. And so they send us those three batches. We scanned them, they can look at them and they can sort of quantify which supplier is good, which supplier is bad. So that’s another use case. And then another interesting use case that we found is I don’t know if you’re familiar, but there’s a whole industry of battery raw materials.

Eric Moch: So it’s sort of the raw materials that goes into making a battery cell. So typically those materials are anode cathode electrolytes. And those companies that are coming up with these, sort of breakthrough innovations, they’re producing a liquid, a powder typically, and they want to make sure that they can showcase their product. And so the way they do this is they use a what’s called a toll manufacturer or a third party manufacturer that will take their powder, or they will take their liquid and they would build battery cells with them. And then these companies, they’re going to take those battery cells and then try and sell, send them to their customer and say, ‘Hey, how look, how’s our material is doing in the full system in the battery cell.’ But as you’re outsourcing this sort of cell-building process, you’re kind of losing control of the build quality. So before those raw material companies send the cells to their customer for testing, they go through us to make sure that the build quality is good enough because you don’t want to sell. You don’t want to send the defective product to your potential customer. And so that’s another use case that we’re enabling. And there’s a couple of others. But sort of, you get you get an overview.

Jennifer Callahan: Do they share with the like potential customers that They, have gone through Glimpse and have had their batteries tested or the battery cells tested?

Eric Moch: It’s actually interesting because the way we, supply the data to our customers is through a secure web application. So it’s something that, you can sign up and you can sort of consume those scans, online. And so we can add as many users as possible as, as our customer wants. and, and also our customer can request us to add their customer to the same space. And so imagine you’re sort of start-up XYZ doing a new raw material. And then you’re sending cells to your customer and you’re asking your customer to test it. And as you’re doing this, you’re saying, ‘Hey, you can actually look, on the Glimpse portal, that this battery is well built.’ And so we can sort of add as many people as, as we want, as long as they’re authorized to view the data on that same portal so more people can access that, that data set.

Jennifer Callahan: That’s awesome. So it’s like the proof is there, you just don’t have to take my word for it.

Eric Moch: Exactly, exactly.

Jennifer Callahan: So this is all great that, your company is here, that you’re scanning as many batteries as possible. they can send them to your customers can send them in batches or smaller batches. but what if they wanted to not send you your batteries? Is there another avenue for them to be checked? Like, do you guys go out to their facilities, or what would be another avenue for them to have them check?

Eric Moch: Absolutely. So we essentially have two models actually, so that the first one we discussed, which we call a scan on demand. So, if you wake up on a Monday, you want to send us 30 batteries, and 300 batteries. You send them to us, we’ll scan them and then send them back. the second model is what we call on-premise scanning. So essentially, because, shipping batteries across the country is not a very scalable thing to do. And it has cost and sort of turnaround time associated with it. For the larger customer, what we offer is to actually deploy our software solution onto their scanner. So, some battery producers or battery buyers already have a scanner. Some are looking to acquire. Wire, a scanner. And so, if they want to turn their scanner from a lab instrument into a high throughput sort of battery quality monitoring tool, they would come to us and then we would deploy our software solution. We literally layer a software solution onto their scanner. And then suddenly, instead of having those like large data files and open and opening up the data locally on a, on a, on a desktop, everything becomes, web-based and they can have as many users as they want. And then our platform can host as many scans as they want. So as they evolve year over year, sort of this build this database of bad quality. And they can compare the past versus the future or different batches or different factories. If you’re like a large customer, you have multiple factories. So this is the second model that we’ve been working on. And I’m very excited as well because it really, it’s kind of one order of magnitude higher in terms of scale. You can scan so many more batteries and then the dollar per scan goes down right for our customers because they get to operate the scanner, they don’t have to ship batteries around. They can really scan as many batteries as they want.

Jennifer Callahan: That’s nice. To have it on site. But speaking of that, do you go out and have to do quality control for the scanners that you provide them? Do you have to go out and check them like, once every six months or once every year just to make sure that it’s functioning?

Eric Moch: We so there’s, we offer a sort of service, or maintenance, that comes with a service. But again, we’re mostly a software company. So, the person who’s going to check if your scanner is on spec or if it’s working well is actually the scanner vendor. That’s the company we partner with, right? The service that we offer is more related to the software provided and also sort of the data processing. so something I haven’t mentioned is there’s a lot of heavy, heavy lifting, sort of data processing that happens locally next to the scanner. And so when we deploy our solution we actually deploy a computing station. So think of it as a gaming station that’s going to take the data from the scanner and then process it locally and then send it to this, secure web application. So that’s what we offer service on. But the city scanner is actually our hardware vendors, partners, that do that.

Jennifer Callahan: That’s good, transition from, doing it in-house to, outsourcing it. so going from that, where do you guys see Glimpse moving in towards, for future developments or anything that you’re hoping to, hone down on in terms of quality monitoring?

Eric Moch: I think a big area of development for us is driving down scan time. For a given level of image quality, you can always trade image quality for scan time. If you run your scanner faster, then your image quality is going to get worse. So what we’re trying to do is reduce the time it takes to scan a battery while maintaining a certain level of image quality, so you can still extract value from these scans, from these images, and the way we have achieved that and we’re going to continue achieving this is really working, across the entire stack. And by stack I mean the technological stack. So, hardware, which are the components? What is the X-ray source? What is the X-ray detector? that gets you the, highest throughput? And then how you operate that scanner. So as you might be familiar with, there are so many parameters when you operate a scanner that you can tune. And a lot of them have trade-offs. So you can trade, I don’t know, contrast for noise or you can trade resolution for, sharpness, etc. And so how you operate that scanner is another lever that we pull and that we do a lot of optimization on. And then lastly how do you process that data?

Eric Moch:  I’ll give you a couple of examples. If you can make that data cleaner and crisper at the end of it, then you can deal with worse data at the beginning of it. And if you can deal with worse data, then essentially you can run your scanner faster. Right? And so pulling on the oldest lever is really an optimization across the technological stack that enables us to drive down scan time. And so we’re working with other hardware side. We’re working with very forward-looking, city vendors that are, working on integrating new components. As I said, an X-ray source produces the same level of image quality faster. But then we have a software company, we have to do our part in, making sure that we can process this data because essentially there’s more data now right per unit of time. So process this data and still provide a good user experience for our customers. So that’s a big area for us. and then just sort of honing in on our two business models scan on demand premise scanning and trying to serve as many customers as possible.

Jennifer Callahan: Do you have a good amount of customers that, have been interested in the on-premise scanning?

Eric Moch: Yeah, we’re working on our first, deployments. So we’re very excited about this. and there’s going to be some announcing later this year, talking with a number of, of customers. and, these are larger companies, obviously, they typically already have a scanner. They want to sort of, 10X it in terms of what we can do with it. And so, very exciting avenue. You really can feel that you’re creating value there.

Jennifer Callahan: Well, everybody, this is Eric Moch with me tonight, sharing with us a different way to use CT scanning, not so much for bones and abdomens and things like that, the batteries that you’re using either in your car or in your household appliances, is actually being quality checked. So don’t think that they’re not. Eric, thanks for being with me tonight.

Eric Moch: Thanks, Jen. It’s been a pleasure.

Jennifer Callahan: All right, everybody, we’ll see you next week. Make sure that you check us out on YouTube Spotify or Apple Podcasts. You’ve been watching The Skeleton Crew, brought to you by xraytech.org. In the next episode, join us to explore the present and the future of the Rad Tech career and the field of radiology.