NDE 4.0 Podcast | Transcript | Dr. Nick Brierly | Episode 17

NDE 4.0 Podcast Transcript

Episode 17 — CT & NDE4.0

Our Guest: Dr. Nick Brierly

Editor’s Note: In the interest of time, this transcript is still in rough format and has not been edited for proper grammar and punctuation. If you have a need for a fully edited transcript, please contact us.

Episode 17

[00:00:00] Nick Brierly: Welcome to Floodlight Software’s podcast, where we interview various experts in industry 4. 0 concepts, issues, and technologies for non destructive testing and inspection. This show is the place to go to learn about the biggest challenges and opportunities around NDE 4.

[00:00:30] Nasrin Azari: 0 from some of the smartest people in the industry.

[00:00:34] Nick Brierly: So sit back and be prepared for a really thought provoking discussion. Hope you enjoy the episode.

[00:00:52] Nasrin Azari: Hello everyone, and welcome to today’s episode of Floodlight’s NDE where we post five questions to NDE 4.

[00:01:00] 0 experts and explore the benefits and challenges in this emerging field. Today, we are joined by Dr. Nick Brierly, who leads the R&D team at Diondo, a leading manufacturer of x ray computed tomography systems in Germany.

[00:01:13] Nasrin Azari: As part of his role, he is heavily involved in various committees related, relating to NDE 4. 0, including as chair of the NDE 4. 0 group of the British Institute of NDT, a role acquired during his previous employment. Prior to joining Diondo, Nick spent six and a half years at the Manufacturing Technology Center in Coventry, United Kingdom, where he was a principal research engineer responsible for the x ray imaging activities, usually in the context of metal additive manufacturing.

[00:01:44] Nasrin Azari: As the MTC hosts the National Center for Additive Manufacturing. Nick holds a doctorate in NDT from Imperial College, London, and an MA in natural sciences, physics, and management studies from the University of Cambridge. Welcome

[00:02:00] Nick, Nick to our show today. Thank you. Thanks

[00:02:03] Nick Brierly: for the introduction. Thanks for having me.

[00:02:05] Nasrin Azari: So Nick and I have participated in a few NDE 4. 0 meetings together, and I’ve always been super impressed by his knowledge around many topics surrounding NDE 4. 0. So I’m really excited to dig into the session with him today. So let’s get started. Nick, let’s start with a basic question to set the stage for our audience.

[00:02:25] Nasrin Azari: Can you describe CT and explain the connection between CT and NDE 4. 0?

[00:02:32] Nick Brierly: Yeah, sure. So, um, CT, the field that, um, my company focuses on, um, is, uh, an advanced 3D volumetric x ray inspection technique, um, that the basic principle is you acquire a significant number of transcripts. Okay. X ray projection images, uh, moving the sample in a [00:03:00] known manner between these projection images, typically by rotating the sample on the turntable.

[00:03:06] Nick Brierly: And then these 2D projection images are fed into a reconstruction algorithm to produce a 3D projection. model, a voxel volume, um, of your sample. Um, that’s the technique in a nutshell. Um, and it’s a very advanced NDT technique. Um, For starters, it is also a fully digital method by definition. I mean, it is called computer tomography, right?

[00:03:41] Nick Brierly: So, um, and and it relies on algorithms to enable it. It relies on significant computational power, um, and it therefore has a head start on many more traditional

[00:04:00] entity techniques in the world of 4. 0. Um, four dot zero. Um, It lends itself particularly well to things like, uh, systematic data analyses of, uh, data series for then providing feedback to manufacturing.

[00:04:23] Nick Brierly: Um, it also serves frequently as the ground truth inspection method for other techniques and, um, 4. 0 is frequently about fusing different, uh, methods. Inspection modalities and drawing those together. Um, it also bridges the world of NTT and the world of dimensional metrology. So, so x ray computer tomography can be used in both fields and in the realms of NDT 4.

[00:04:58] Nick Brierly: 0 and Industry 4. 0. [00:05:00] Um, there is a significant interest in, in pulling together, um, these disparate aspects of, of. Quality control. Um, and then there are perhaps another few aspects one could mention. So, for instance, X ray computer tomography is really an enabler of metal additive manufacturing, given the highly complex geometries that can be created by metal AM and additive manufacturing is Um, one of the, the, the key manufacturing techniques of industry 4.

[00:05:37] Nick Brierly: 0, enabling, um, part customization, et cetera, et cetera. So, so there’s a, you know, another link there. Um, and, um, one could also highlight that because industrial computer tomography, it has. Uh, the, the, the links to, um, it’s [00:06:00] clinical counterpart and that the fact that, uh, computer tomography is used in a clinical setting, um, means that we can actually borrow some of the, um, advances made in a clinical sense in terms of interoperability, um, and, uh, uh, exploits, um, some of the, those capabilities.

[00:06:25] Nick Brierly: So, so, so fundamentally, X ray CT is an advanced NDT technique and it has, uh, numerous features which lend itself particularly to the world of 4. 0 more so than a traditional wet inspection technique.

[00:06:50] Nasrin Azari: Really interesting. You know, one of the things that we talked about prior to this To doing this interview, uh, was how CT could be used to create digital [00:07:00] twins.

[00:07:00] Nasrin Azari: And I find that really fascinating too. Can you talk about that? How can CT be used to create digital twins and with what applications?

[00:07:09] Nick Brierly: Absolutely. So, um, another really good point. Um, so, uh, the, the data provided by an x ray CT inspection, um, is, is very rich and particularly, um, varied in its possible, um, applications.

[00:07:29] Nick Brierly: And so, um, It has immediate uses for the purposes of, uh, creating or populating, um, a, a digital twin of a, of a component or, um, a, an assembly. Um, so, for example, well, maybe we should take a step back. So, so a digital twin, um, in its, its, uh, most basic form, um, is, is a virtual representation of a, a physical [00:08:00] entity.

[00:08:00] Nick Brierly: And. It, at some level, is informed by the physical entity, and then at some level, um, insights obtained from the virtual world, from the digital twin, are then exploited and used in the physical world. So there’s, there, at least in my definition of that term, there’s some level of synchronization between the virtual and physical worlds.

[00:08:32] Nick Brierly: Um, And, um, one, and so, so CT can be a key resource for generating and, uh, populating, as it were, that virtual representation because we obtain a 3D model of the component. And so, um, also, for instance, if you happen not to have, um, a CAD model [00:09:00] of the component, um, In the case of a CT scan, you can then use that CT scan to, to obtain a geometry model, nonetheless, and use that as your basis for your digital twin, because the geometric description of your component is likely to be a key input for your digital twin.

[00:09:28] Nick Brierly: Um, And then once you’ve, um, created your, your virtual representation, depending on exactly what kind of, uh, component or sample you have, you have scanned, that can be exploited in, in numerous different ways. So, for instance, um. This can be used for so called image based modeling where you virtually load your [00:10:00] component.

[00:10:00] Nick Brierly: So you effectively generate, uh, a finite element model from your image data from your CT scan, and then you can work out, for instance, whether the defects that you have in your physical component are actually critical or how critical they are. And that in turn then means that even parts which are not completely in spec, as it were, or fundamentally are imperfect, um, that you can Work out in what sense that component is still useful and so you can reduce your scrap rates.

[00:10:45] Nick Brierly: That’s really interesting. Another application looking more towards dimensional metrology is virtual assembly. So having Uh, obtained a, a surface model [00:11:00] of your component, including internal surfaces because this is one of the great, uh, advantages of CT that you, you can inspect internal features. Um, you can then produce a, a virtual assembly combining your, your surface from the.

[00:11:19] Nick Brierly: obtained from the physical instance with the surface models of other components that need to slot together. And you can work out whether the, the stack up of your tolerances and so forth is still going to work in that assembly. And then based on that, you can work out for instance, which instances of the different parts in your assembly, you should combine for the overall best fit.

[00:11:49] Nick Brierly: So again, rather than relying on hard specifications, which in many cases might be Somewhat over [00:12:00] conservative or even a just just slightly arbitrary, frankly, you can really work out with respect to the final function, which parts can still be used in watch configuration.

[00:12:14] Nasrin Azari: Yeah, so you’re optimizing your use of your materials and your components so that you’re not throwing away.

[00:12:22] Nasrin Azari: Unnecessarily items that might be slightly defective, but still usable as a whole.

[00:12:28] Nick Brierly: Absolutely. So that’s just one possible usage of a digital twin of a component. So other examples would be just to provide a baseline for future inspections as well. So if you then have a component which will be inspected after X many thousands of hours in service.

[00:12:49] Nick Brierly: Um, and you want to be able to track where. And so forth. This gives you a baseline from which you can then start to track where, [00:13:00] um, these are all sorts of possibilities that then become.

[00:13:04] Nasrin Azari: So I think you’ve sort of started touching on this already, but, um, any additional comments about how these digital twins that are generated can be used to improve or advance a business?

[00:13:16] Nasrin Azari: Thinking of it from the business perspective.

[00:13:19] Nick Brierly: Yeah, absolutely. So, so yeah, I tried to address that in part already, um, but, um, certainly the, the aspiration is to be able to reduce scrap rates, um, by. Making, uh, imperfect parts usable, um, by finding a use for them by, for instance, um, a, a component part might be perfectly adequate as a replacement in an assembly, which is only going to have a remaining service life of X number of hours.

[00:13:57] Nick Brierly: Um, and, and you, you might be able to [00:14:00] prove. Through a suitable simulation that even though the component doesn’t meet the nominal specification in a conventional sense, um, it’s perfectly adequate for that because by the time meets that that that defect size grows to a critical length or similar, the whole assembly will have been, um, taken out of commission

[00:14:23] Nasrin Azari: anyway.

[00:14:24] Nasrin Azari: Yes, yeah. Yeah. Now, what about the digital twin of the inspection?

[00:14:29] Nick Brierly: So, this is another interesting aspect. So, um, we’ve been working on, uh, the digital twin of a CT scan. Um, because digital twins can refer not only to components and assemblies, but also processes. Um, and, uh, CT is, is, uh, Uh, complex inspection technique and and so there is an interest in having a digital twin, um, especially for inspection [00:15:00] planning and optimization.

[00:15:02] Nick Brierly: Um, and so one of the things that we’ve been working on is, is, uh, enabling an optimization of the, uh, component orientation, for instance, in. The CT scanner, uh, which has a significant impact on your overall, uh, inspection quality, um, and so forth. Um, and is, is, um, potentially, um, hard for a, um, for, for an expert to, uh, assess, I should say hard, even for an expert to assess, let alone a novice user.

[00:15:42] Nick Brierly: And so, uh, part of the, the, um, aspiration there is, is to be able to help new users of the technology through suitable, uh, aids. Facilitated by a digital twin of the inspection. That’s

[00:15:59] Nasrin Azari: interesting. I mean, [00:16:00] I think this is kind of the first time I’ve actually thought about creating a digital twin of a process versus a physical entity itself.

[00:16:08] Nasrin Azari: So it’s almost like you’re creating a model that can be used for simulation sort of.

[00:16:13] Nick Brierly: Yeah, absolutely. So, uh, you know, to me, at least a digital twin is a virtual representation, which has some kind of links to the physical world, some level of synchronization. And so we would calibrate our simulation model of the inspection process of the CT scan, and then feed insights gained from that virtual representation back into the.

[00:16:40] Nick Brierly: physical world to inform the practical physical inspection on the machine.

[00:16:45] Nasrin Azari: Yeah. That’s very interesting. So let’s move to our next question, which is about the challenges. So we’ve talked a lot about the benefits and some of the applications of digital twins and using CT to create these digital twins.

[00:16:59] Nasrin Azari: What do you [00:17:00] think are some of the challenges in using digital twins in these ways? And how do you think these challenges can be best tackled?

[00:17:08] Nick Brierly: Um, so obviously it depends a bit on exactly what kind of digital twin you’re talking about, and what kind of application you’re pursuing, uh, but one, uh, frequent challenge if we’re now focusing perhaps a bit on on the sort of component level, uh, digital twin is that at present.

[00:17:30] Nick Brierly: There certainly isn’t one piece of software that delivers a digital twin for you. It’s, it’s, uh, generally speaking, uh, a matter of daisy chaining together different pieces of software using information and data from different sources, um, which then means also, Um, that the interfaces become critical and really interfaces are at the core of 4.

[00:17:59] Nick Brierly: [00:18:00] 0, right? Uh, it’s about enabling, uh, consistent interoperable, um, data flows. Um, and, and that feeds certainly into, into these challenges here. Um, so, um, yeah, another aspect, for instance, is. That, um, you, you would, it’s not unusual to then have, um, data from different sensor systems, different inspection systems, um, and that you wish to.

[00:18:35] Nick Brierly: Merge, uh, overlap, or otherwise fuse in your digital twin to form a holistic view of, of the state of your, your component to otherwise. And that is a not insignificant, uh, registration challenge, in fact, um, and, and so, uh, one, perhaps particularly, um, popular, um, [00:19:00] Prominent, uh, example of that is, is, is from the world of metal additive manufacturing, where you have various sensor systems on your, um, metal 3D print system, be it laser powered bed fusion or, or similar.

[00:19:17] Nick Brierly: Um, and you, you collect data during the print process and then you do some kind of, uh, validation inspection afterwards, typically using an x ray CT scan. And then you want to. Validate the signals. Um, the interpretation of the signals from the 3D print process, and you want to, uh, correlate the signals from the in person monitoring with the post build inspection, um, and first thing you have to contend with is this registration challenge, right?

[00:19:55] Nick Brierly: Getting data from two completely different sensor systems, [00:20:00] uh, into one, the same coordinates system. Um, so you can, uh, make reasonable. Uh, deductions about, um, what your sensor systems are telling you. And from the CT perspective, that particular, uh, challenge described in the context of 3D printing is something that we at DeOndo have been, um, also working on.

[00:20:22] Nick Brierly: So trying to make sure, for instance, that we can deliver the CT data in the coordinate system of the component, uh, which then makes subsequent, um, Registration, uh, significantly easier. Okay,

[00:20:38] Nasrin Azari: so that’s something that where you think that the challenges can be tackled. You’ve also touched on. Interfaces when you were talking about the fact that you need multiple software systems to, um, you know, sort of generate these digital twins versus just having sort of a single piece of software.

[00:20:59] Nasrin Azari: And I know [00:21:00] that in your role at BINDT, you’ve been helping to lead the push for common interfaces such as Dicondi. Can you talk a little bit about the state of those efforts and your thoughts on where standardization will go in the next couple of years?

[00:21:15] Nick Brierly: Yeah, absolutely. Um, so, yeah, as mentioned, um, really connectivity interoperability, uh, standard interfaces are core challenges, um, for NDE, uh, 4.

[00:21:32] Nick Brierly: 0, um, and there are multiple different, um, groups working on this in different ways. And I almost certainly only have a partial overview of what’s going on in this domain. Um, but, uh, certainly, um, two key, uh, efforts relates to, uh, Dicondi, um, which is [00:22:00] derived from the, the medical DICOM standard, um, Uh, and the OPC UA standards, which is derived, um, or originates from the world of robotics.

[00:22:13] Nick Brierly: Um, and both these standards are being, uh, extended, expanded to meet the demands of, uh, NDE 4. 0 and, and enable some of the workflows that, um, we’ve been talking about really. Um, And, um, so, so, and as already mentioned, um, the world of x ray CT has a head start there because, uh, there’s a clinical counterpart as in clinical x ray CT.

[00:22:50] Nick Brierly: And so, because the Diconde standard builds on the Dicom standard from the medical domain and CT is established in medical domain, [00:23:00] um, X ray computer tomography is already reasonably well accommodated, um, in the Dicondi, um, and the same cannot be said for some more, uh, traditional techniques and some, uh, advanced NDT techniques for which there are no clinical counterparts.

[00:23:24] Nick Brierly: Right. Um, so, so, uh, certain ultrasonic methods, for instance, um, are the focus of. The current efforts really, um, so, so, um, I, there’s been a, uh, an effort to put forward a, an extension to the Daikondi scheme to account for, um, these, these, uh, advanced ultrasonic, um, Methods, um, but the other thing to, to, to bear in mind was, was that [00:24:00] those are, um, all these, these efforts concerning OPC UA and, uh, Dicondi are certainly, um, important and it is worth, I think, bearing in mind that, um, not all

[00:24:22] Nick Brierly: Workflows that, in fact, we’ve been talking about or people are interested in pursuing in the context of ND 4. 0 will be possible based solely on OPC UA and So there are other data points and information elements rely on us as a community, um, interacting more with the, the adjacent fields. Um, so I already mentioned dimensional metrology, um, but another key.

[00:24:55] Nick Brierly: Uh, domain that we need to probably reach out [00:25:00] to is, is the materials community, right? So, um, information about material composition, for instance, is, is a, a key input for many simulations. Mm-hmm. and Yeah. Makes sense. That needs to be communicated in a standardized manner. Mm-hmm. . So that people can exploit that information, um, automatically, digitally, um, and, and so forth.

[00:25:27] Nasrin Azari: So do you think that the sort of the nirvana around this interoperability, do you think it’s a single standard, like, for example, Daikondi that’s been expanded to account for some of these additional, um, requirements on, on, of data formats that need to be supported, or do you think it’s really more a combination of, um, Different standards.

[00:25:52] Nick Brierly: It will almost certainly be a combination, um, given different, [00:26:00] uh, original design remits and so forth, um, yeah, it’s hard to imagine a single standard encapsulating everything people might want to, uh, communicate, document, um, archive, So,

[00:26:21] Nasrin Azari: It’s a very complex topic around NDE 4. 0. I think this whole standardization and the communication, you know, challenges between because we’re just, we’re sort of progressing at the same rate as we’re trying to progress the standards,

[00:26:35] Nick Brierly: right?

[00:26:36] Nick Brierly: Yes. Yes. Um, yeah. I mean, standardization is, is difficult fundamentally, I think that indeed, um, and, Because there are already various existing efforts. Um, it’s also a matter of looking at which bits can be reused or how to [00:27:00] avoid duplication and as mentioned also about, um, linking up with some of these other domains that we perhaps haven’t spoken to too much in the past.

[00:27:11] Nick Brierly: Past decades. Right, right, right. Um, yeah. And, and, you know, using some of the, the initiatives that are coming out of those spaces as well.

[00:27:23] Nasrin Azari: Oh, fantastic. So let’s move to our last question, which I know you’ve touched on. This already. So maybe just sort of sum this up and give us your thoughts on, um, pulling things together.

[00:27:37] Nasrin Azari: How do you envision that common interfaces might help advance the usage and benefits of X ray computed tomography systems?

[00:27:47] Nick Brierly: Yeah, so, um, we really would hope that even more value can be obtained from our CT data [00:28:00] through. These common interfaces and so forth. Um, so, so, for instance, that, um, the, the data that our machine obtains can seamlessly be fed into digital twins of, of, uh, components and be exploited directly in image based simulations, um, and, uh, virtual assemblies and all these good things that we’ve, we’ve spoken about.

[00:28:25] Nick Brierly: And at the same time, then, um, the, the processing processing. is, is far more streamlined, the user experience is simpler, um, and there’s less need for, for expert input, um, the machine can, for instance, to a large extent, self configure for new, new components, uh, do its own inspection planning to a large extent, um, these sorts of things.

[00:28:55] Nick Brierly: Wow,

[00:28:56] Nasrin Azari: yeah. No, that’s, that’s, [00:29:00] that’s so interesting. Um, one of the things I love about doing this podcast is how much I learn from every guest. And I feel like I have learned a lot today, Nick. So thank you so much for participating today and thanks for your insights. Very, very educational. Thank you so much for having

[00:29:18] Nick Brierly: me.

[00:29:18] Nick Brierly: It’s been great.

[00:29:19] Nasrin Azari: Yep. And I hope you listeners enjoyed that discussion today as much as I did. As usual, we will post contact information for Nick if you are inspired by his ideas and would like to get in touch with him directly. And if you have any feedback or would like to nominate an individual or an organization to be a guest on a future episode, please send a message to me directly.

[00:29:39] Nasrin Azari: At an Azari at floodlightsoft. com, or you can submit the contact us form on our website at www. floodlightsoft. com. Thanks again for joining us and we’ll see you next time. Thanks, Nick.[00:30:00]

[00:30:01] Nick Brierly: To learn more about NDE 4. 0, emerging technologies, and digital transformation, please visit www. floodlightsoft. com for additional resources, including our blog and several relevant white

[00:30:14] Nasrin Azari: papers.

[00:30:15] Nick Brierly: If you have any questions about today’s episode or suggestions for future episodes, please send an email to info at floodlightsoft.

[00:30:23] Nick Brierly: com. Thank you so much.


For more expert views on NDE 4.0, subscribe to the Floodlight Software blog at floodlightsoft.com.

Scroll to top