Beyond Silicon: The Power of X-Ray Metrology in Advanced Packaging

X-ray technology reveals what the naked eye cannot see - the intricate world of semiconductor interconnects that power our digital lives. In this deep dive with Ben Peecock, Senior Director of Business Development at Nordson Test and Inspection, we uncover the critical differences between x-ray inspection and metrology that keep semiconductor manufacturing on track.

With nearly three decades of experience in the industry, Peecock guides us through the evolution of semiconductor inspection technologies. While silicon itself remains transparent to x-rays, the metal interconnects between components provide the perfect canvas for quality assessment. As advanced packaging pushes toward smaller, more complex structures with 3D stacking and chiplet architectures, the need for sophisticated inspection has never been greater.

We explore how inspection (focused on imagery) and metrology (centered on precise measurements) serve complementary roles across the semiconductor manufacturing ecosystem. From R&D laboratories perfecting new processes to high-volume production lines seeking zero defects, these technologies help manufacturers identify issues before they become costly failures. The conversation ventures into the distinctions between 2D inspection (optimized for speed) and 3D analysis (delivering comprehensive structural information) and when each approach proves most valuable.

Particularly fascinating is Nordson's approach to vertical integration, developing their own specialized x-ray sources and detectors optimized specifically for semiconductor applications. This expertise extends to their innovative work integrating artificial intelligence to accelerate inspections while maintaining accuracy. Their thoughtful approach to data security gives customers options to protect proprietary information while still benefiting from AI's capabilities.

Discover how these technologies are already supporting emerging trends like panel-level packaging and learn about Nordson's unique radiation management solutions that protect sensitive components during inspection. Whether you're a semiconductor professional seeking quality control insights or simply curious about the technologies that ensure your electronic devices function reliably, this episode offers a fascinating glimpse into an invisible world of quality assurance.

Nordson Test and Inspection
Delivering best-in-class test, inspection, and metrology solutions for semiconductor applications.

Disclaimer: This post contains affiliate links. If you make a purchase, I may receive a commission at no extra cost to you.

Chapters

• 0:00 Podcast Introduction and Sponsorship
• 1:30 Meeting Ben Peacock from Nordson
• 5:23 X-Ray Inspection vs. Metrology Explained
• 9:28 Advanced Packaging Trends and Needs
• 14:26 2D vs. 3D X-Ray Technologies
• 19:00 Nordson's X-Ray Solutions Portfolio
• 25:07 AI Integration and Data Security
• 30:00 Radiation Management and Closing Thoughts

Transcript

Françoise von Trapp: 0:00

This episode of the 3D Insights Podcast is sponsored by Nordsen Test and Inspection. Leaders in acoustic, optical and x-ray inspection and metrology systems for the semiconductor and SMT manufacturing markets. Nordsen's next-generation 3D x-ray inspection software, dynamic Planar CT, reveals incredible details for Nordsen's zero-defect strategy. Nordsen's advanced software is two times faster than planar CT, with enhanced detail quality, superior reconstruction and a larger field of view for increased coverage and shorter cycle times all to improve yields, processes and productivity. Learn more at Nordsoncom. Hi there, I'm Francoise von Trapp, and this is the 3D Insights Podcast. Hi everyone, welcome back to the 3D Insights Podcast series on x-ray inspection and metrology for wafer level and advanced packaging. This is the third episode in a series with our elite member Nords Intestine Infection. Now, in previous episode we explored first the acoustic microinspection and we talked about dynamic planar CT imaging. Now in this episode we're tackling the differences between x-ray inspection and metrology. So here to help me is subject matter expert Ben Peecock. Welcome to the podcast, ben.

Ben Peecock : 1:32

Hi, thank you. Thanks for having us. Nice to meet you.

Françoise von Trapp: 1:35

So I'm really excited for our conversation today. I think that this is one of the most interesting elements of the advanced packaging space, because it's so critical. But before we dive in, can you tell us about yourself and your role at Nordson?

Ben Peecock : 1:50

Sure, I am currently the Senior Director of Business Development for the Nordson Test and Inspection Group of Companies. I've been with the business for over 29 years. I was acquired by Nordson 20 years ago, so yeah, a long history. I have been through the business from the very earliest days of X-Ray, kind of right through. I've worn a number of hats in my time, starting in R&D as a mechanical design engineer and then going through operations, finally through into business development, where I am today.

Françoise von Trapp: 2:23

Okay, you know, in the earlier days of advanced packaging and please correct me if I'm wrong it seemed like x-ray inspection was really mostly for the R&D end of things, not so much used in manufacturing. Has that changed?

Ben Peecock : 2:38

We definitely support all different areas of the semiconductor industry, so right through from early R&D development for new products, but also going through into semiconductor volume manufacturing and then right through into final use. So we also have equipment that's going right down to PCBA or even some final assembled, tested products. So testing at the full spectrum and again, that has been there for some time. Obviously, with every change in technology there's a new opportunity, and so we kind of start the cycle again, initially with R&D and then following through into volume production as those products start to ramp up.

Françoise von Trapp: 3:24

Okay, I think one of the reasons I always latched on to x-ray inspection is it's something that I could understand, having had x-rays on bones and what you look for. And I remember early on learning that, okay, silicon isn't something that you can x-ray, so that's not really what you're looking at. You're not looking for defects in silicon when you're doing these x-rays. You're actually looking for either anomalies or defects in the actual interconnects. Is that correct?

Ben Peecock : 3:51

Correct. Yeah, as you say, silicon is very translucent to x-rays, so we can't see the silicon itself. But, as you say, as we're moving into advanced packaging, it's all about the interconnects between the different devices, the different layers, and that's where we have a really good imaging from the x-ray to be able to see those, the bumps and the tsvs and the various interconnects and and the quality of those and the alignment of those and how they're all stacked up and looking for specific defects within them. We're using x-ray not just in the way of medical x-ray where we're looking through an object. We're actually using x-ray as a microscope, so using the principle of geometric magnification, by getting our samples very close to the x-ray source, it then projects a large view of the object under inspection. So being able to see through it, being able to see a very high magnification, it gives us the ability to look inside these advanced package devices.

Françoise von Trapp: 4:49

You mentioned TSVs and you mentioned micro bumps. Now, before that, 20 years ago, it was wire bond. The bumps were bigger, the features sizes were larger. What are some of the trends and dynamics in wafer level and advanced packaging today that you've seen shift over the years?

Ben Peecock : 5:09

The reality now is that advanced packaging is really driven by the high power computing, the whole AI world, the need for very complex devices starting to move from a 2D into a 3D space All those really driving the performance of the device, meaning that those bumps and those interconnects getting smaller and smaller, a lot more layers being added. So now the criticality around not just is there a good connection, but the alignment of those. Are they all aligned? Also, the fact that these devices now, because they are getting more complex, they're getting much higher value. So finding defects early is critical because obviously if you've gone through the process and you're right down the end of the chain and you've got multiple dyes all interconnected and then you find a defect, the cost of failure is much higher. So the importance of inspection and that quality control is even more critical.

Françoise von Trapp: 6:07

So are you seeing more use of x-ray inspection than previously?

Ben Peecock : 6:14

Yeah, absolutely, as we have new technologies and as the sort of global market changes and the need for different countries' independence of their own supply chain, that there's a lot of parallel activities working on developments of these technologies. So, again, not so much industry standard lots of new ideas and new processes being developed, and so lots of opportunities for those processes needing to have quality control to make sure they are solid when they ramp up into high volume production.

Françoise von Trapp: 6:50

So one of the things we've been talking about is x-ray inspection. How is that different from x-ray metrology?

Ben Peecock : 6:57

So typically x-ray inspection is looking at an image, so the device is inspected under x-ray and an image is produced, and originally it was all then an operator reviewing that image to make a determination of good and bad product, and as time's gone on that's become more automated, but it's still fundamentally based around an image. Metrology is actually about measurements, the, the physical sizes of devices. So using those same x-ray techniques, but actually using it to give measurements, and then the output of the tool being data files rather than a bank of images, and so it's not requiring a human intervention to make a determination on good or bad. The data is the data which is then typically fed back into the customer's host computer to feedback the quality of the products and manage the quality control of their processes.

Françoise von Trapp: 7:55

What you're looking for is different and from inspection you're looking for a bad, good and sorting situation where you're removing and is metrology actually used to refine processes?

Ben Peecock : 8:09

I mean they can both be used for refining processes. But metrology typically is a volume production mechanism. It's all about how fast we can push the process. We can measure all of the product and identify any bad parts within the product. The inspection can be used in the same way. You have to determine what you're saying is a good and bad product, whereas in metrology you're just getting measure the size of the bump, measure the size of the TSV, then measure the size of the void, within that the fill level of the TSV, size of the voids within that, the fill level of the tsv, and then, of course, the determination can automatically be applied that says an acceptable limit is a, is a void of two microns or below, or a percentage fill of 98. Is data driven as opposed to image.

Françoise von Trapp: 8:58

Image output and so in the inspection you said there is a manual operator involved.

Ben Peecock : 9:04

That's where the industry started. Everything was done with a human operator and as time has moved on we've automated that. So we're still taking images, but then automating some of those measurement features. The fundamental, the output, is an image, typically, then, which will have an overlay, which will identify the good and bad product and identify the voids. So then an operator can review that data. They can look at the image themselves and say the system has determined this has got a void of a certain size or it's passed fail. An operator can then look at that image and make a qualification. So it doesn't need to have an operator, but the images allow that to be reviewed at a later stage.

Françoise von Trapp: 9:47

So on the metrology side, you're measuring the bumps and the voids and the TSVs. Are you looking for anomalies only, or are you also? I guess I'm trying to understand how that data is then used. Once you've gathered it, what do you do with the data?

Ben Peecock : 10:03

So it can be used for a whole range of different inspections. So from a simplest form, it might be just the bumps on a wafer. So a 2D inspection how big are the bumps? Are there any missing bumps? Are there any bumps that are joined? Are there any that are the wrong size? And then what is the voiding? Is there any air pockets inside those solder bumps which could then cause a problem later on the process? So that's kind of from the simplest level. But then we go into a full 3d where we might have a package further down the line and we're now looking at tsvs and a tsv alignment with a micro bump. Are those correctly positioned? Are they off-center? Is the shape and the size giving us a clue about the quality of that interconnect joint? It's used both in the 2D and the 3D space for, again, very simple to highly complex specific measurements which might give us an indication of a specific type of failure.

Françoise von Trapp: 11:03

Okay, so there's a lot of uses then for x-ray metrology in the advanced packaging and wafer-level packaging space.

Ben Peecock : 11:10

Absolutely yeah.

Françoise von Trapp: 11:12

You know, basically from R&D all the way through volume manufacturing.

Ben Peecock : 11:16

So typically we get involved with our customers during product development.

Ben Peecock : 11:21

So we will have some early projects where they're looking for specific applications and then typically we then also put those tools into the volume production where they're looking to manage their yields. So in R&D it's about developing a product and a process. When it then gets into full production it's about managing the yields and making sure their production lines are operating efficiently, they're not going out of alignment or control that need any any corrections, and making sure that the good products identified and, where there is a where there is an issue in the production line, making sure they're not spending any more time adding value to a product which has already failed. So again, if you look at a wafer which has got maybe hundreds of dyes on there, it will be able to identify those which are bad and then feeding that back to the process tools to say, right, ignore these specific dyes because they have a defect and there's no point adding any more value, adding any more process steps to those. All the others are good and continue through to final product.

Françoise von Trapp: 12:28

When, would you say, is the ideal time to use 2D versus 3D?

Ben Peecock : 12:32

So typically 2D has the advantage of speed. I mean, when we're talking 2D, what we're basically talking about is a single image. So we are either looking at a straight 2D straight through the object, a bump from top down, and again, if that gives all the information that's needed, that's by far the fastest way. We can have a large area detector. We can inspect a high quantity of devices very fast.

Ben Peecock : 13:02

When we start to get into the 3D space, this gives us the added dimension which, in our, was to start to look at those interconnects in the vertical space. When you're then looking at TSVs, for example, or if you're looking at interconnects, you need to see not just straight through but an oblique view image. And if you're taking multiple oblique view images, we can then turn that into a 3d model which, once you have then a model constructed, then you can perform a sort of sectioning of that model, removing parts of the device that are not clear or get in the way so you can actually see the area of interest. So potentially having a vertical slice through a TSV which will show a lot more information than just a plain top-down view which you would get from a 2D inspection. So typically 2D is all about speed. 3d is when you need more information about the inspection point, which will take longer but will give you a lot more data.

Françoise von Trapp: 14:00

And that would be more in the development side of things then.

Ben Peecock : 14:04

No, that can also be in full production, obviously in full production. The challenge is throughput. Everybody's looking for these tools to run as fast as possible. But yeah, there are some inspections which will always need a 3D inspection point, whether it's in R&D or in full volume production.

Françoise von Trapp: 14:22

I would imagine in full production that you have to sample. You can't inspect every single device that goes through.

Ben Peecock : 14:29

Again, depending on the customer and what they're looking for, that's certainly an option. We do have some customers that just want to run batch inspection. They want to inspect four points on a wafer just to make sure. In general, things are progressing, but when they're a high reliability, high value product. We're now seeing more drives to do 100 inspection. But one of the things we've been working on is is looking at ways to get the benefits of 3d but running at 2d line speed, and there's been a real focus of how we integrate the artificial intelligence into our equipment to really leverage that, because we have images and models of good and bad devices. We can then use AI, train a model to make a determination and that's able to spot parts of the image in a 2D inspection, which might give us a good representative of a 3D quality inspection but at much faster line speed, and so that's a big area of focus for us right now is how we're leveraging that AI.

Françoise von Trapp: 15:31

What are the different types of inspection and metrology platforms available at Nordson for x-ray metrology?

Ben Peecock : 15:39

When we started developing X-Ray products, we really wanted to not just be an X-Ray company. We wanted to be focused around the electronics and semiconductor space. We recognized that the technology was underdeveloped and so what we really focused on is that imaging chain the X-ray source and the detector, which are the key elements for creating an x-ray image and really bringing that design in-house and then optimizing it around our specific application needs, the application needs for an electronic semiconductor x-ray very being very different from a medical x-ray. So that was kind of where we came from and that's always been a key part of our technical differentiation that we are vertically integrated. We own our own technology and we're constantly driving to push that forward to give us the very highest quality imaging chain in our particular space.

Ben Peecock : 16:36

So what we've then done? With that as the base platform, we've then built the different systems, ranging right through from a manual inspection tool, where it really is all about an operator using it, typically in contract manufacturing, pcba, where they are looking for something where they've got a wide array of different customer products and they want to inspect maybe the quality of the bga device, soldering and an edge connector for solder fill, um. So starting at that entry level on the manual inspection tools, going right through into the automated tools, which is all about, again, typically PCBA or some semiconductor device inspection, and then right through into the metrology tool, which is the big wafer inspection tool which, again, we're now moving from not just inspecting wafers but also moving to panel level inspection as that industry starts to develop.

Françoise von Trapp: 17:42

So covering the full spectrum, okay. And when you say that you do everything vertically, do you develop then your own X-ray source?

Ben Peecock : 17:50

Yeah, so we've been manufacturing X-ray sources around design for over 20 years and again we've optimized the design specifically around the type of devices we're inspecting in our industry and again that really helps us get a very high magnification and very high resolution X-ray source and then on the detector side, a very low noise, high resolution detector, so we can get very high magnification, very high resolution images with relatively low radiation dose.

Françoise von Trapp: 18:25

So the source is the same throughout your systems, but the systems are designed for the specific applications, such as in the PCB and wafer and advanced packaging space. Can you talk a little bit about some of specific application examples, maybe share some specifics from a customer perspective?

Ben Peecock : 18:45

From sort of the entry level typically it's PCBA, where we're doing void analysis in BGAs and solder fill volumes in edge connectors In our automatic inspection lines, typically again PCBA, but quite often they'll be for high reliability applications, so aerospace, automotive, defence-type applications where reliability is critical. So you might be doing the same types of inspection points but you're doing 100% inspection and you're doing it in very high volumes. And then through into the wafer level inspection points, but you're doing 100% inspection and you're doing it in very high volumes. And then through into the wafer level where we might be doing the co-OS type products, where again looking at these advanced packages, looking for interconnect quality measurement of voids in bumps and TSV voiding and again a lot more recently, on things like the alignment of the chip, so chip gap height or chip alignment with the bumps.

Françoise von Trapp: 19:51

How about, like in the chiplet space? Do you do anything there? Or there's the embedded bridge sky. Is that an application that would benefit from X-ray metrology?

Ben Peecock : 20:01

We can cover any wafer-level product. Again, we either do it at wafer level or sometimes when it then breaks out into singulated devices. Quite often we have some customers that are then inspecting them at that latest step where there's another layer of interconnect being added and they're looking for those final inspection points and an inline system.

Françoise von Trapp: 20:24

So you mentioned panel and panel level. Packaging is a hot topic. I don't know at this point how much is actually in production at the panel level, but then there's also been a lot of talk about the different substrates, like the glass panels versus organic or other organic and silicon. So how do all of these developments impact your decisions and your development process?

Ben Peecock : 20:48

to support that, so we work very closely with our customers and, as we said, we're fortunate to be working in both the production space but also some of the R&D projects. We've already developed and supplied a panel version of our metrology tool and we're working on sort of expanding that range in terms of different panel sizes and different materials as they start to roll out. As you say, it's a hot topic. At the moment it's relatively small volumes. So there's lots of activity in R&D, not so much in volume yet, but we're certainly seeing indications that within the next couple of years that will ramp exponentially. So at the moment, fairly small but significant growth coming. And, as I say, we're able to reuse the same technology, the same core technology, which we continue to develop. We continue to generate the next X-ray sources and detectors to improve that resolution. But fundamentally, the same tool then can be modified to handle panels rather than wafers, just different robot loading, different chucks and contacts for those.

Françoise von Trapp: 22:00

Do you already have an automated panel tool or are you developing that as it evolves from R&D into panel level?

Ben Peecock : 22:10

No, so we've already manufactured a version of our metrology tool as a panel device and we have that. It's up and running, it's at a customer site, operating, and we have multiple projects expanding on that with different panel sizes and different materials. So, yeah, we already, we already have a design out there that's coming.

Françoise von Trapp: 22:30

So now is this your XM8000 AXM system that we're talking about.

Ben Peecock : 22:36

Yeah, so that's when we talk about panel and wafer level metrology. It's the XM8000.

Françoise von Trapp: 22:41

Yeah, okay, and so is it the only solution, or are there alternative solutions on the market?

Ben Peecock : 22:47

There's not a lot of other products out there doing the combination of the very high resolution devices, the clean room, compatible automatic handling for the wafers and panels and then accelerating with AI. So, in terms of all of those key elements, that there isn't anything out there that is competing in that space.

Françoise von Trapp: 23:11

So can you talk about some of the competitive advantages that it might have in that space.

Ben Peecock : 23:15

So can you talk about some of the competitive advantages that it might have. Yes, because we control that imaging chain, we are manufacturing our own sources, again really optimizing it around the samples we're looking at. So typically when you're looking at higher resolution x-ray sources, you're putting a lot of energy into a very small focal spot and the challenge with that is generating enough X-rays to produce an image. So because it's optimized around our products, we say optimize that spot size and then we have the detector which can then have the sensitivity to pick up on a very low level of X-ray photons to be able to generate an image. So controlling that imaging chain and really focusing on this key market is what's kind of giving us the edge on the image quality and, as I say, it's years of experience in how we're processing those images and models to make measurements and then make determination about good, bad, defects and defect classification.

Françoise von Trapp: 24:17

And what role does software play in all of this? Because we've been talking about AI, and is AI a software element?

Ben Peecock : 24:24

So the classical algorithms for determining from an X-ray image the quality of the product is, again, it is something we've built over decades of experience and again, we have a team of experts that developed a whole host of algorithms for all sorts of different types of defects.

Ben Peecock : 24:45

But what we're now doing is accelerating that. So, using that industry knowledge and that host of algorithms we already have, using ai to accelerate that and actually saying, okay, there are some of those algorithms where, where, if you have an image with multiple layers and multiple objects in the field of view, if we can then use ai to actually determine which is the areas of interest, which which layers of the bga are we actually wanting to inspect, so a combination of the classic algorithm with AI technology to identify what we're trying to inspect, we can get either faster throughput, more reliable on our results or even, as I said before, using 2D inspection where typically 3D would be the more traditional way of achieving that. Ai by itself is not enough. It needs to have that background of enough. It needs to have that background of understanding.

Françoise von Trapp: 25:37

It needs to be trained right, right. So AI is another hot topic right now, and we hear a lot about generative AI, and we also hear a lot about generative AI not being accurate because of the data that it's receiving, right? So I'm assuming that when we're talking about AI here, you're actually working with closed data sets, so the accuracy or the intelligence is actually maybe smarter than what we're getting just out on the internet with generative AI.

Ben Peecock : 26:08

Yes, exactly Because we are controlling the data that's being used to train the models, we can ensure that the quality of that data is. I mean, with the AI engines, they can just pull all that information from the internet good and bad, true and untrue and so that's where we can sometimes lead to false results, but where we have control of that, the training model, what we're putting into it. We also recognize that not all customers are happy for their information to go into those models or even to use that. So we also offer the ability for customers to effectively train their own models on site, having their own images that they capture and classify themselves, or they can update and improve the quality of the models that they're running.

Françoise von Trapp: 26:57

So that's a really good point, because if you're training your tools on available customer data, there's a lot of proprietary information there that you can't really use right. You have to be really careful about you, know. Yeah about.

Ben Peecock : 27:18

You know. Yeah, yeah, absolutely, and I think that's. There's a balance to be had between the benefits of the larger model having a more general and higher capability than a smaller niche specific model. But again, depending on what the device is. So a contract manufacturer using their machine to just look at the quality of inspection of a BGA on a printed circuit board, there's nothing proprietary about solder bumps at that level. Whereas if you're looking at advanced packaging, where there is a specific, unique process being developed by one semiconductor manufacturer, that might be something that those images won't leave the fab. So we need to be able to cover the full spectrum.

Françoise von Trapp: 27:56

Do you offer tools available with or without AI?

Ben Peecock : 28:00

Yes, so our standard tools are available with the classical algorithms and again we're adding AI as an additional bolt on and again, but on the basis that AI is growing. We have a number of features that the AI is already delivering for us today, but we have a whole roadmap of additional functionality that we're going to continue to add, to build on. So it's something that is not static, so we wanted to separate that from the main software.

Françoise von Trapp: 28:31

I'll tell you where this question is coming from. I recently bought a new washer dryer and the last thing I need on my washer dryer is AI. But it's there because you can't seem to get the other things without it, you know. So it's AI enabled and it's also Wi-Fi. Another thing I don't need on my washer dryer is Wi-Fi, and I'm assuming that this washer dryer is not going to last very long because the electronics panel is only warrantied for a year. So where I'm going with this is do these tools actually need to be connected to either an intranet or the internet to use the AI?

Ben Peecock : 29:12

No. So what we have is basically the runtime model, so the software that's doing the AI piece, that can be anywhere, that can be on the cloud, that can be on a customer's central server, it could even be on the same PC of the machine. The location of that is not critical, obviously. If you're connected to the cloud, then you have the ability of the automatic updates and that can happen a lot faster. But it doesn't need to be, and certainly that's that's. One challenge that anybody in the industry faces is that people don't want to connect some of their production tools onto the cloud, and they are very strictly prohibited. So yeah, we're having the flexibility to be able to have the runtime sitting directly on the tool itself really gives us that flexibility, okay.

Françoise von Trapp: 29:59

Is there anything else that we've missed that you want to make sure people understand?

Ben Peecock : 30:04

Yes, there is. Another area of focus for us is radiation management. So one of the challenges that has been known about for a long time is the potential damage of radiation on certain semiconductor devices, and so we have spent a lot of time around dose management and have a number of different solutions, whether it's about the monitoring and measurement of that dosage, so we can accurately report the level of radiation that each component has received. We can also use the same tool to effectively do that modelling, so before we put a sample into a machine we can model what the dose expectation would be. But we've also been focusing a lot recently on how we can provide automatic dynamic shielding for key areas of the device. So we know there are some components which are more sensitive to radiation than others. So a big area of focus for us is a patented solution for radiation dose shielding on wafer level devices, which really opens up the capability of inspecting a lot more products a lot further through the production chain.

Françoise von Trapp: 31:20

And is this unique to Norton?

Ben Peecock : 31:23

Yep. So this is a Norton patented technology and it's rolling out now in live product today Excellent. Where can people go to learn more? Live product today, excellent.

Françoise von Trapp: 31:33

Where can people go to learn more?

Ben Peecock : 31:35

We're attending a number of trade shows. We'll be in Semicon Taiwan, semicon West. Obviously, our website's full of information and we have our full regional sales and distribution service team that can connect people to answer any questions they might have for a range of demonstration.

Françoise von Trapp: 31:54

Excellent. We will put some links in the show notes and, yeah, this will be out before SemiCon Taiwan, so thank you so much for joining me today.

Ben Peecock : 32:04

Thank you very much.

Françoise von Trapp: 32:10

Next time on the 3D Insights podcast, I'm joined by members of the IMAPS committee to talk about the upcoming IMAPS Symposium taking place September 29th to October 30th. There's lots more to come, so tune in next time to the 3D Insights Podcast. The 3D Insights Podcast is a production of 3D Insights LLC.