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Episode 14 – Philip Colet from Teledyne DALSA

by | Mar 30, 2023 | Episodes

Episode 14 - David Dechow - Phil Colet

Episode 14
Philip Colet
Teledyne DALSA

Manufacturing Matters welcomes Philip Colet, VP sales and marketing at Teledyne DALSA, to discuss the latest in machine vision and imaging, including semiconductor inspection, SWIR/UV, line scan imaging, and more.

Colet talks about semiconductor inspection and how represents a strong market for the company, as they sell many products to inspection and manufacturing equipment OEMs. Additional topics include Teledyne DALSA’s line scan cameras –which generate very high-resolution images at a lower cost—as well as finding the right wavelength for an application.

For example, certain applications require sensors and cameras with SWIR or UV sensitivity to detect features and defects beyond the visible wavelength. Additionally, Teledyne DALSA is developing solutions for another expanding market: agriculture and food production. Colet discusses what needs to happen for farmers to adopt enabling technologies at a larger scale.

Episode 14 – Philip Colet from Teledyne DALSA: Audio automatically transcribed by Sonix

Episode 14 – Philip Colet from Teledyne DALSA: this mp3 audio file was automatically transcribed by Sonix with the best speech-to-text algorithms. This transcript may contain errors.

David Dechow:
Hello and welcome to another Manufacturing Matters by tech B2B. We’re here at the Vision Show in Boston, and I’m talking with Phil Colet of Teledyne DALSA. Welcome, Phil.

David Dechow:
Good to see you. Thank you. And we’ve known each other for some.

Philip Colet:
Time for a number of years now.

David Dechow:
That’s right. So great to have you on manufacturing matters. And I think a good place to start would be if you could just tell the listeners and tell me a little bit about the the general overview of what Teledyne told and also being a huge company, of course, but what Teledyne also is doing in the field of machine vision and imaging right now and where it stands with the with the company.

Philip Colet:
Well, for those of you who don’t know, Teledyne is a large financial company and they have a division they called Teledyne Imaging, which has a lot of different segments to it because they’ve gone on various acquisition sprees in the past. One of those acquisitions was Teledyne also, or Dulce, with expertise in line scan cameras and frame drivers and software that are used very much in the manufacturing environment. Of course, we have also purchased e2v with expertise in image sensors. Most recently about a year ago we acquired Fleer, so they became Teledyne Fleer with expertise in thermal, all things thermal, but they also had a division over in Vancouver who was also with expertise in machine vision for manufacturing.

David Dechow:
And where do you see the the most recent movement in the area of of imaging and cameras for manufacturing that that Teledyne also has been working strongly in or really helping the manufacturing base to move move their applications forward.

Philip Colet:
Right. That’s a great question. So one of our strongest markets is in the semiconductor equipment market. We just had this panel discussion where we’re talking about semiconductors. Semiconductors are ubiquitous, right? They are used everywhere. If you went back 20 years ago, they were not in cars. Now, cars are full of electronics cameras, digital cameras, cell phones. They are just absolutely everywhere. So I was just speaking with someone else by the year 2030, the expectation is that the semiconductor market will be about $1 trillion, which is places at number three, number four in terms of overall industries. That level of revenue is going to require a huge expenditure in infrastructure. That infrastructure will filter down to the requirements for equipment, for inspection equipment, lithography, equipment, imaging equipment. So a lot of flow down from those investments. Right. And so we’ve been that’s one of our largest markets actually, is the semiconductor equipment market. So we don’t sell to the Tsmc’s or the Intels or the Samsungs directly. We sell our stuff to people that make equipment, inspection equipment specifically or manufacturing equipment. So they will utilize our products in their products. So we’re kind of like the intel inside, but we don’t have Dolson inside or Teledyne inside, right? Yes. But we are core to their to their equipment.

David Dechow:
That’s incredibly interesting. And I have to admit, I didn’t know that about the semiconductor industry growth. It’s fascinating right from the point of view of sensors and cameras. What what I’m curious what kind of products and let’s see from a technology point of view, really serve that industry well, What what is what has been in demand or let’s say not in necessarily in demand, but what has been really enabling that that industry.

Philip Colet:
Right. That’s a good word. Enabling, yes, because imaging is an enabling technology to this manufacturing equipment. You cannot have a stepper or a lithography machine without machine vision as being part of that core. Some of the products that we make in terms of sensors and cameras would be what we call a line scans camera. So if you look at your cell phone, there’s a camera in there. It’s got an array of pixels, a line scan, cameras, just really one line, but that. Means that something has to move in front of it. The advantage you can generate an image which is very, very high resolution at a much lower cost. So we have a ton of these types of cameras that we manufacture and sensors that we sell to these equipment manufacturers. Now, the other thing to look at, another piece of this is the wavelength that you’re using. So we’re looking at features which are so small that visible light will just go right around them so you cannot see a defect. So that’s where we have to get into U.V. sensitivity or deep UV sensitivity or even now down at the extreme UV sensitivity. If you if you don’t have sensitivity at those wavelengths, you will not be able to detect these defects. And so our customers are using this capability that we built into our sensors and cameras in order to to build systems that find these defects.

David Dechow:
That’s amazing. That’s really amazing. And of course, I have to say, I know that Teledyne also is one of the leaders, if not the leader, of course, in line scan technologies. And that.

Philip Colet:
Is something.

David Dechow:
That is an amazing, amazing marketplace to use that technology. And but let me go a little bit further. We’re here at the Vision Show, of course, and we talk about a broad scope of marketplaces, of course. Where do you see sensors and actually where do you see sensors moving the movement of the sensor themselves in the marketplace? Because, of course, still that ideals with sensors of their own and in more of a general purpose context, how do you see the the movement of the camera components within Teledyne and also in the in our in our marketplace?

Philip Colet:
So getting outside of the semiconductor industry, which I think your question was, there’s a number of other industries which are demonstrating very high growth these days. I utilize these sensors. One of those might be logistics. So COVID hits, we all turn to online shopping. There’s an explosion in online shopping, right? Retail stores are closed. How do you get your goods? So that really drove a lot of building, of infrastructure, of logistics, with millions and millions of packages flowing through these facilities. You have to track them. You have to know where they are. That’s a demand from the consumer as well. Where is my package? So with that comes sensors to pick up and read all of those barcodes. And there’s a variety of different kinds of sensors that can be used for that. Again, line line scan sensors, but also the area scan sensors. So they’re used quite a bit in the logistics. Another important market, which is also growing is in agriculture and food production. Growing populations, we have to make food production much more efficient and safe and high quality. And so we see the movement of machine vision technology into the agribusiness, not only in post harvesting in terms of filtering or getting rid of the bad product, but also during planting, during seeding, during the maintenance of fields deposition of water, which is in many areas a very scarce resource. Where do I have to apply water and where do I apply pesticides and herbicides? We don’t want to broadcast this across the entire field. We want to use them selectively. So we see a lot of applications and a lot of growth in those types of applications. So some of the requirements there would be, again, hyperspectral or multispectral capabilities of the cameras and the sensors in order to pick up on specific wavelengths to differentiate in between what is a corn plant and what might be an invasive species.

David Dechow:
Right, exactly. I’m glad you mentioned that, that we’ve heard a lot about the growth in demand in agriculture for quality inspection, for precision agriculture. That’s I think that’s a huge, huge area. You mentioned multispectral and hyperspectral as well. Do you do you feel that those are they’ve been those technologies have been around a while, of course. Do you think they’re really going to come come into their own in the machine vision world? As we find an application like agriculture that really, really thrives on that kind of technology, is that where they’re going to where that’s going to really let those technologies blossom?

Philip Colet:
Right. So there’s a couple of aspects to that question. One of them is the drive the end user drive towards implementing these technologies. So we do see that happening. We do see agribusiness growing quality control. But the second part of it is the technology itself was perhaps at a price point which prohibited its use in those applications. Right? So if it was far too expensive, then farmers would never buy that equipment. It’s just cheaper to broadcast pesticides everywhere. Right, as opposed to using precision agriculture. So we are looking at, with the advancements of technologies, making these technologies less expensive and therefore expand their market reach.

David Dechow:
Marvelous. Yes, that’s good to hear. And I think a boon for the industry as well.

Philip Colet:
Absolutely. For humankind.

David Dechow:
Yeah, indeed. Indeed. Yes. Do you would you be willing to be kind of a fortuneteller, a future, a futurist, and say what your thoughts are on what the next the next couple of big things in imaging and maybe sensing and imaging or maybe camera components. Do you have any idea floating around on what you think the next couple of big things are going to be Right?

Philip Colet:
And I think we see it here at the Vision show. It’s all across the floor, which is AI or deep learning or what is a neural network. This was also popular about 40 years ago. Yeah. And it took a deep dive because the implementation of that technology just wasn’t ready. So we didn’t have the technology at that time to bring it to market. So a lot of companies started, but they failed. Given 15 years later, a lot of research driven by some big companies in California into AI, into deep learning, into the algorithms, but also the technology to execute those algorithms has now matured. So with the availability of GPUs, with very fast processors, this is now becoming a reality. So the big bold prediction is that everything that we see on the floor over here in terms of artificial intelligence and deep learning will actually see an application. And we are seeing applications right now, but it will become much more common. The great thing about this is that it can solve problems that we can’t solve in conventional machine vision algorithms. So it doesn’t mean it’s going to eliminate traditional mathematical machine vision, but it will supplement it’ll be another tool in our tool chest that will enable this. And this, I think, has great applications, even outside of machine vision, outside of the manufacturing floor. We can implement these techniques into any number of everyday applications. I was listening to some some sessions today about safety, about let’s take how many unfortunately how many children die in drowning incidents in the United States. This is terrible. Right. And they have lifeguards and everything, but they’re preoccupied and it’s very difficult. So can we not create a system that can detect somebody who’s struggling. Right. And alert the lifeguards to that incident? Man, this is just so exciting, right?

David Dechow:
That’s only the tip of the iceberg.

Philip Colet:
It’s only the really? Yeah, absolutely. It’s only limited by our imagination.

David Dechow:
Yes. Philip, would you say there’s anything that maybe we haven’t talked about that’s really on your mind for the people listening to manufacturing matters?

Philip Colet:
I think it might be the combination of AI, deep learning, machine vision and robotics. This triangle has is really starting to come together and we see it here at the Vision show, the combination of machine vision, the algorithms, plus also the robotics that is really, really maturing. And that also, I think will make manufacturing. More efficient. It’ll make quality control improved. Right. But also, a lot of people are fearing robotics. But I just saw a graph the other day that any time there’s robotics investments, employment actually goes up. Yes. Right. And that surprises a lot of people. But I think that’s also a benefit. Yeah, I think robots are taking jobs away, but in fact, they’re actually expanding the.

David Dechow:
Jobs, right?

Philip Colet:
Yes, indeed.

David Dechow:
Well, thank you very much, Phil. It’s been a pleasure to talk with you.

Philip Colet:
Thank you very much.

David Dechow:
I hope you’ve as much fun as I am. This is great stuff. Thank you all for listening. And we’ll see you again on another episode of Manufacturing Matters by Tech B2B.

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David Dechow: [00:00:07] Hello and welcome to another Manufacturing Matters by TechB2B. We’re here at the Vision Show in Boston, and I’m talking with Phil Colet of Teledyne DALSA. Welcome, Phil.

David Dechow: [00:00:19] Good to see you. And we’ve known each other for some time.

Philip Colet: [00:00:22] For a number of years now.

David Dechow: [00:00:24] That’s right. So great to have you on Manufacturing Matters. I think a good place to start would be if you could just tell the listeners and tell me a little bit about the general overview of what Teledyne DALSA, being a huge company, of course, but what Teledyne DALSA is doing in the field of machine vision and imaging right now and where it stands with the company.

Philip Colet: [00:00:50] Well, for those of you who don’t know, Teledyne is a large financial company, and they have a division they call Teledyne Imaging, which has a lot of different segments to it because they’ve gone on various acquisition sprees in the past. One of those acquisitions was Teledyne DALSA, or DALSA, with expertise in line scan cameras and frame drivers and software that are used very much in the manufacturing environment. Of course, we have also purchased e2v, with expertise in image sensors. Most recently, about a year ago, we acquired FLIR, so they became Teledyne FLIR, with expertise in thermal, all things thermal, but they also had a division over in Vancouver with expertise in machine vision for manufacturing.

David Dechow: [00:01:46] And where do you see the most recent movement in the area of imaging and cameras for manufacturing that Teledyne also has been working strongly in or really helping the manufacturing base to move their applications forward.

Philip Colet: [00:02:08] Right. That’s a great question. So one of our strongest markets is in the semiconductor equipment market. We just had this panel discussion where we’re talking about semiconductors. Semiconductors are ubiquitous, right? They are used everywhere. If you went back 20 years ago, they were not in cars. Now cars are full of electronics — cameras, digital cameras, cell phones. They are just absolutely everywhere. So I was just speaking with someone else, by the year 2030, the expectation is that the semiconductor market will be about $1 trillion, which places it number three, number four in terms of overall industries. That level of revenue is going to require a huge expenditure in infrastructure. That infrastructure will filter down to the requirements for equipment, for inspection equipment, lithography equipment, imaging equipment. So a lot of flow-down from those investments. And so that’s one of our largest markets actually, is the semiconductor equipment market. So we don’t sell to the TSMCs or the Intels or the Samsungs directly. We sell our stuff to people that make equipment, inspection equipment specifically, or manufacturing equipment. So they will utilize our products in their products. So we’re kind of like the Intel Inside, but we don’t have DALSA Inside or Teledyne Inside, right? But we are core to their equipment.

David Dechow: [00:03:57] That’s incredibly interesting. And I have to admit, I didn’t know that about the semiconductor industry growth. It’s fascinating. From the point of view of sensors and cameras, I’m curious, what kind of products, and let’s say from a technology point of view, really serve that industry well? What has been in demand or let’s say not necessarily in demand, but what has been really enabling that industry?

Philip Colet: [00:04:30] That’s a good word, “enabling,” because imaging is an enabling technology to this manufacturing equipment. You cannot have a stepper or a lithography machine without machine vision as being part of that core. Some of the products that we make in terms of sensors and cameras would be what we call a line scan camera. So if you look at your cell phone, there’s a camera in there. It’s got an array of pixels. A line scan camera is just really one line, but that means that something has to move in front of it. The advantage: you can generate an image which is very, very high resolution at a much lower cost. So we have a ton of these types of cameras that we manufacture, and sensors, that we sell to these equipment manufacturers. Now the other thing to look at, another piece of this, is the wavelength that you’re using. So we’re looking at features which are so small that visible light will just go right around them so you cannot see a defect. So that’s where we have to get into UV sensitivity or deep UV sensitivity or even now down at the extreme UV sensitivity. If you don’t have sensitivity at those wavelengths, you will not be able to detect these defects. And so our customers are using this capability that we built into our sensors and cameras in order to build systems that find these defects.

David Dechow: [00:06:07] That’s amazing. That’s really amazing. And of course, I know that Teledyne DALSA is one of the leaders, if not the leader, of course, in line scan technologies.

Philip Colet: [00:06:17] We like to think so.

David Dechow: [00:06:18] That is an amazing, amazing marketplace to use that technology. And but let me go a little bit further. We’re here at the Vision Show, of course, and we talk about a broad scope of marketplaces, of course. Where do you see sensors — actually where do you see sensors moving, the movement of the sensors themselves, in the marketplace? Because, of course, Teledyne deals with sensors of their own, and in more of a general purpose context, how do you see the movement of the camera components within Teledyne and also in our marketplace?

Philip Colet: [00:06:58] So getting outside of the semiconductor industry, which I think your question was, there’s a number of other industries which are demonstrating very high growth these days that utilize these sensors. One of those might be logistics. So COVID hits, we all turn to online shopping. There’s an explosion in online shopping, right? Retail stores are closed. How do you get your goods? So that really drove a lot of building of infrastructure of logistics, with millions and millions of packages flowing through these facilities. You have to track them. You have to know where they are. That’s a demand from the consumer as well. Where is my package? So with that comes sensors to pick up and read all of those barcodes. And there’s a variety of different kinds of sensors that can be used for that. Again, line scan sensors but also the area scan sensors. So they’re used quite a bit in the logistics. Another important market, which is also growing, is in agriculture and food production. Growing populations — we have to make food production much more efficient and safe and high quality. And so we see the movement of machine vision technology into the agribusiness, not only in post-harvesting in terms of filtering or getting rid of the bad product but also during planting, during seeding, during the maintenance of fields, deposition of water, which is in many areas a very scarce resource. Where do I have to apply water and where do I apply pesticides and herbicides? We don’t want to broadcast this across the entire field. We want to use them selectively. So we see a lot of applications and a lot of growth in those types of applications. So some of the requirements there would be, again, hyperspectral or multispectral capabilities of the cameras and the sensors in order to pick up on specific wavelengths to differentiate between what is a corn plant and what might be an invasive species.

David Dechow: [00:09:32] Right, exactly. I’m glad you mentioned that. We’ve heard a lot about the growth in demand in agriculture for quality inspection, for precision agriculture. I think that’s a huge, huge area. You mentioned multispectral and hyperspectral as well. Those technologies have been around a while, of course. Do you think they’re really going to come into their own in the machine vision world? As we find an application like agriculture that really, really thrives on that kind of technology. Is that going to really let those technologies blossom?

Philip Colet: [00:10:18] Right. So there’s a couple of aspects to that question. One of them is the drive, the end user drive towards implementing these technologies. So we do see that happening. We do see agribusiness growing quality control. But the second part of it is the technology itself was perhaps at a price point which prohibited its use in those applications. So if it was far too expensive, then farmers would never buy that equipment. It’s just cheaper to broadcast pesticides everywhere as opposed to using precision agriculture. So we are looking at, with the advancements of technologies, making these technologies less expensive and therefore expand their market reach.

David Dechow: [00:11:16] Marvelous. Yes, that’s good to hear. And I think a boon for the industry as well.

Philip Colet: [00:11:22] Absolutely. And for humankind.

David Dechow: [00:11:24] Yeah, indeed. Yes. Would you be willing to be kind of a fortune teller, a futurist, and say what your thoughts are on what the next couple of big things in imaging and maybe sensing and imaging or maybe camera components? Do you have any idea floating around on what you think the next couple of big things are going to be?

Philip Colet: [00:11:56] And I think we see it here at the Vision Show. It’s all across the floor, which is AI or deep learning or what is a neural network. This was also popular about 40 years ago. And it took a deep dive because the implementation of that technology just wasn’t ready. So we didn’t have the technology at that time to bring it to market. So a lot of companies started, but they failed. Given 15 years later, a lot of research, driven by some big companies in California, into AI, into deep learning, into the algorithms, but also the technology to execute those algorithms, has now matured. So with the availability of GPUs, with very fast processors, this is now becoming a reality. So the big bold prediction is that everything that we see on the floor over here in terms of artificial intelligence and deep learning will actually see an application. And we are seeing applications right now, but it will become much more common. The great thing about this is that it can solve problems that we can’t solve in conventional machine vision algorithms. So it doesn’t mean it’s going to elimiate traditional mathematical machine vision, but it will supplement, it’ll be another tool in our tool chest that will enable this. And this I think has great applications, even outside of machine vision, outside of the manufacturing floor. We can implement these techniques into any number of everyday applications. I was listening to some sessions today about safety, about how many, unfortunately, how many children die in drowning incidents in the United States. This is terrible. And they have lifeguards and everything, but they’re preoccupied and it’s very difficult. So can we not create a system that can detect somebody who’s struggling? And alert the lifeguards to that incident? Man, this is just so exciting, right?

David Dechow: [00:14:22] That’s only the tip of the iceberg.

Philip Colet: [00:14:24] It’s only limited by our imagination.

David Dechow: [00:14:28] Philip, would you say there’s anything that maybe we haven’t talked about that’s really on your mind for the people listening to Manufacturing Matters?

Philip Colet: [00:14:41] I think it might be the combination of AI, deep learning, machine vision, and robotics. This triangle is really starting to come together, and we see it here at the Vision Show, the combination of machine vision, the algorithms, plus also the robotics that is really, really maturing. And that also I think will make manufacturing more efficient. It’ll make quality control improved. But also, a lot of people are fearing robotics. But I just saw a graph the other day that any time there’s robotics investments, employment actually goes up. And that surprises a lot of people. But I think that’s also a benefit. They think robots are taking jobs away, but in fact they’re actually expanding the jobs.

David Dechow: [00:15:36] Right.

Philip Colet: [00:15:37] Yes.

David Dechow: [00:15:39] Well, thank you very much, Phil. It’s been a pleasure to talk with you.

Philip Colet: [00:15:42] Thank you very much.

David Dechow: [00:15:42] I hope you’ve had as much fun as I have. This is great stuff. Thank you all for listening, and we’ll see you again on another episode of Manufacturing Matters by Tech B2B.