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Sahar Ehsani with Intel
21st September 2021 • The Industrial Talk Podcast with Scott MacKenzie • The Industrial Talk Podcast with Scott MacKenzie
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On this week's Industrial Talk Podcast we're talking to Sahar Ehsani, Sr. Segment Marketing Lead - Discrete Manufacturing  about "AI, Machine Vision and Sustainability".  Get the answers to your "Discrete Manufacturing" questions along with Sahar's unique insight on the “How” on this Industrial Talk interview! Finally, get your exclusive free access to the Industrial Academy and a series on “Why You Need To Podcast” for Greater Success in 2021. All links designed for keeping you current in this rapidly changing Industrial Market. Learn! Grow! Enjoy!

SAHAR EHSANI'S CONTACT INFORMATION:

Personal LinkedIn: Sahar Ehsani | LinkedIn Company LinkedIn: Intel Corporation: Overview | LinkedIn Company Website: Intel | Data Center Solutions, IoT, and PC Innovation

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https://youtu.be/5o6Z_BCaEtA

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PODCAST TRANSCRIPT:

SUMMARY KEYWORDS manufacturing, intel, industrial, ai, sahar, technology, data, discrete manufacturing, absolutely, people, machine, industry, listeners, learn, happening, vision, line, processes, customers, factories 00:00 Industrial Talk is brought to you by NEOM that's NEOM.com they have a vision of changing the world for the better in almost every way. They are committed to that. They have a bold, a brave and daring greatly vision on how to change the world. For the better for all of us. They are committed to that. Go out to niobe.com get involved, you will be dazzled and you will not be disappointed. Big thinking going on there. And you know what's happening out there. Technology. Innovation is happening everywhere. And the speed at which is just absolutely blistering. You know who's leading the way Intel that's right Intel, they are leading the way with edge cloud. You name it industry for Dotto, right in their wheelhouse smart cities. Yes, robotics. Yes. And, and let's say digital transformation of the utilities. Yes, Intel is where you want to go go out to intel.com find out more and see how they can help you innovate. Welcome to the industrial talk podcast with Scott MacKenzie. Scott is a passionate industry professional dedicated to transferring cutting edge industry focused innovations and trends while highlighting the men and women who keep the world moving. So put on your hardhat grab your work boots, and let's go Alright, welcome again to industrial talk v number one location in the universe that celebrates you industrial heroes, you are bold, you are brave, you dare greatly you solve problems, you innovate like no other and you are changing lives and the community Do not forget that put that in your pocket because it is important because you got to believe we need you big big time in the hot seat in the Industrial Talk we have Sahar Ehsani, she is with Intel, we are talking about manufacturing technology. She is a senior center segment market lead discrete manufacturing. And, you know, we're gonna be talking about Yep, AI, machine vision, sustainability and how all that works to go there. Let's get cracking. So you get to join me on my educational Odyssey to learn from the very best in industry about that man, you get to join me, I again, I you know, you got you got incredible professionals, such as Sahar and, and she knows what she's talking about. And also people from Intel and others, that are just absolutely one. Thank goodness that they desire to truly develop, develop the innovations to be able to make our lives better, thank goodness. And you know what else is so great that they're willing to share their insights and wisdom for us, so that we can begin to learn you never stop learning? Each day, always learn that, I don't know, it doesn't sound so fantastic. But it is it got to there's it's all out there. And especially in industry, we've got to do that. Alright, let's talk a little bit about the industrial Academy. Real quick. The industrial Academy is absolutely dedicated to education. And the reason it's dedicated to education is because, well, that's something nobody can really take away from you. If you are dedicated if you are committed if you have a true desire to learn from the very best within industry, industrial academies where you want to be because we're we're talking about management leadership, we're talking about innovation, we're talking about the nuts and bolts of operations. And what are the strategies associated with not in a way that is like, Oh, my gosh, this is a 75 hour class and and it'll drive you crazy? No, no, the responsibility on your part is one, that you get the flavor you get to hear from the best that represents let's say IoT, or edge or cloud or reliability, whatever might be the best. And it's up to you because you have a spirit of learning is to go out and find out more all the contacts and information is out there. It is a big, big win for you continue to learn, grow, and and just, you know be the best you possibly can be because 04:39 for whatever reason, maybe I've got rose colored glasses. I can't tell you why. But I really truly in my heart of hearts, believe that industry is truly the key that can change lives, change communities and change the world. And it might be Pollyanna. It might be Well over the top. I like bold, brave goals. And and the industrial Academy is focused on being able to provide industrial education for people who need to know. So that their lives can be changed, their companies can be changed, their communities can be changed, and so on. And so the world. Alright. Let's get going. I get all Tingley about that type a type of conversation now. So hard, but it's been a bit of a long journey to get her on the podcast. But fear not she does not disappoint. great conversation, great insight, great stuff that's happening at Intel. I've got her form here, you go out and find her stat guard. All very impressive. So we're going to be talking and yeah, you're gonna say, Scott, Oh, you've already talked about AI? Yeah, we have. But it never stops, continues to grow continues to evolve, we never stopped. You know, we've talked about machine vision, looking at the ability to look at products and improve the quality and so on and so forth. And of course, sustainability. What does that mean? How does all this wonderful innovation help sustainability because it also has to sort of work hand in hand. If there's a gap that is missing from that particular value chain. Now, that's a problem. But Intel sohar team Intel are working diligently not just in manufacturing, but also in in the energy space and oil and gas all everything that you could possibly at the heart, you know, entails right there. All right. Enjoy this particular interview with Sahar Sahar, welcome to industrial talk. How are you doing? 06:47 doing very well. How are you, Scott? 06:49 It's been a long time in the making to try to get you on the podcast. 06:54 Yeah, sorry. It's my bad I might sign. 06:58 You don't need to you don't need to cower away from me. I was just I was so excited when we first met. And, but but business moves on people get busy. It's all about that. But you're here right now. And listeners, you're going to be impressed. She's got a mad statcard out there on LinkedIn. Absolutely. Of course, I'm looking at her form. And that's impressive, too. So you Listen up, learn educate with me, because I'm not the sharpest tool in the shed. But Sahar is she's a sharp tool in the shed. All right, for the listeners. So Mark, give us a little background on who you are. 07:34 salutely first of all, it's a pleasure to be here, Scott, and have this conversation with you. I'm very excited for this conversation. And about myself. I'm big global segment lead for discrete manufacturing industry at Intel IoT group. So basically what I've been doing in align my career in Intel, and outside of Intel, I've been engaged with manufacturing, all my career. And in my current role, what I do is of working with partner and manufacturing and customers to facilitate and accelerate the digital transformation that's taking place currently around the goal. It is listeners, it's really awesome. It's very exciting. We are just in the front of the line and helping everyone to make those cyphy in 08:35 the future baby in the future is now man, it's now 08:40 all those things that we were seeing in the movies is now happening. And it's very exciting. 08:44 It is. I was just watching Minority Report and and some of the things that they're going through. It's like, Oh, that's happening now. Oh, that's cool. Oh, you know, it's pretty exciting. Now, I'm not. Again, we've established I'm not the sharpest tool in the shed, can you define discrete manufacturing? How's that different than well manufacturing? 09:03 Absolutely, yes. So, when we look at the manufacturing Overall, we can divide it to two or three segments, let's say three segments, for the simplicity, one is discrete manufacturing, then you will have individual product as an outcome but those products can be assembled through bringing different parts from different location in one place. They can be built all in one place or they can be built around the globe apart and get assembled like automotive industries, right, like consumer goods, like electronic and devices. So all those parts some can be made in China, some in Vietnam, etc. They come out to another Assembly Facility and they get assembled and after their life is done, you can disassemble them again and cycle them. But when it comes to their hybrid, that's another section of manufacturing hybrid, which is the process and discrete manufacturing together. It has like some sort of batch processing like food and beverage. So for example, if you mix two chemicals with each other for pharmaceutical, you need to continue that process, you cannot stop it, you cannot ship it to somewhere else around the world. Because, yeah, so that's part of the process industry, but batch processing, because things get prepared in batches. And then at the end of the day, get they get packaged, which is part of the discrete manufacturing, that's what they call them hybrid. The other one is continuous process manufacturing, like oil and gas, right? You see a wealth of oil, you cannot stop it, that needs to continue, and you need to keep take care of those processes. They call it continuous processing. 10:59 I like it. That's a good explanation. Now, listeners, you're better because of that explanation. Now, you know, don't, don't come to me and say, Scott, I don't know. All right. One of the topics that we're going to be talking about, and what we're going to feature on this particular conversation is going to be talking about AI. AI is application to manufacturing, and, and artificial intelligence, this machine vision stuff, give us a little just sort of your definition of, of artificial intelligence, and its application and manufacturing. 11:32 Absolutely. Let me give you a little bit background on bringing in this technology to manufacturing Overall, we want to make manufacturing smarter. We know in some of those manufacturing, like automotive, there are lots of automations already going on. We know my factoring like silicon manufacturing, like silicon chip, like Intel, when you look at their main factories is really well automated. So what is AI is really bringing to the table for those very fully automated manufacturing. When you add AI, basically, you leverage tons of data that is being generated by those automatic automatic devices. So you get that data, you analyze it, you make a decision based on the result of that. So that's what artificial intelligence does. If you get the result, and immediately as a control rule, feed the information back to the manufacturing line, that's a closed loop control. And during that you have the real time control of the manufacturing production. And then all of this together improves the manufacturing processes and efficiencies improve manufacturing uptime, right. So if you want to look at the strategy of how the technology are coming to the manufacturing board, I believe personally, AI and machine vision are going to be the front of the line, because they are easy additions to the already existing technologies in manufacturing, whether very advanced manufacturing, like auto or semiconductor, or they manual type of manufacturing, like machine builders, so you can add or port builders or textile companies in China. So let me explain a little bit about how AI works. 13:31 But let me interrupt real quick, let me interrupt real quick. So what I hear you saying is that it's it starts, it starts with the ability to collect data, but there's a tsunami of data for lack of a better term, I me, Scott, is I'm not going to go through a spreadsheet, look at all the data that's coming off of machines or though or the line, I need some technology to help facilitate and make some decisions that allow good data to come through and throw away the bad data. Is that right? 14:02 Exactly. That's absolutely true. And that's artificial intelligence. You connect it on connected if they're not connected already. And then you collect the data, and you analyze the data. And based on that analysis, that happens automatically, you make a decision, what you want to do next 14:21 is your zero learning component to AI. It's one thing I can create parameters, I would imagine you're the expert, I can create parameters that certain data gets through is that can that can I learn and be and hone and be more refining? as I grow and be able to improve the analytics of that data for my my business? 14:45 Play? Yes, the data machine learning aspect of it. So the algorithm that you add to the computer that is running that algorithm basically, it gets better and better terabit more data, one of the main challenges that we currently have in the manufacturer is that they have a very high yield is finding bad parts. Because if you want the device to, to locate the bad part in a production line, you first need to teach that algorithm what a bad bad part is. So if a manufacturer has a very high yield means that they do not produce so many bad data. So sometimes it takes three months to collect bad data in order to train that algorithm. And those algorithms, they get better over time as we get more data through them. 15:42 And it I would imagine, so hard that that, if I want to be competitive going forward, if I want to be that, I want to have some sort of legacy sustainability, when it comes to my business, I'm going to have to embrace this, I'm going to have to figure it out. But you know what the problem I have, and help me understand this. I just think of costs, I think it's going to be expensive. I know today, what I'm looking at. And if you're telling me I got to go down this road, I have, I don't have that clarity, what what's the economics behind all this, that's 16:15 a very reasonable, actually concerned by any type of manufacturing managers or executives. So we all if you're living in a very competitive board, all the customers, they want perfect products, but cheaper, and everyone is trying to pay that. So in order to keep that profit margin for my factors and keep our business running, they need to have solutions that make business sense. And usually, that's why that I was thinking that AI and machine vision, powered by AI, our best solution to start speed, because you don't need to change much on your manufacturing line, you just add the machine vision, you assess the quality of your devices, and usually within eight to 12 months, you get the positive ROI. 17:07 Spectacular, you know that? That is without spectacular. I mean, if if I had I mean, I was evaluating investments that had a three to five payback, right? took three to five years just to start looking at things that are positive. And that's pretty common. Now, but I don't want to gloss over this. But explain what machine vision is? Oh, 17:31 yes, let me explain what machine vision is. So let's imagine that you have a factory line that has a product and you want to inspect it, you put a camera on it, and you connect the camera to a piece of compute. And machine vision actually is capturing those images, and analyzing those images through a AI algorithm on that compute. So there are different type of there are different types of technologies being used. anomaly detection is one of the paths that people take, basically, looking into good and bad data, the good data, you don't mind you just say good data good go away. You don't want to keep them but the bad data you can locate and you can say this part is bad. So that's how machine vision boards by looking taking images and being connected to compute that has AI algorithm on it. 18:29 So this is how I see it happening this I see it rolling out. If I am able to deploy AI deploy the machine vision in the right area, I might capture anomalies within my manufacturing quicker compressing that time, not waiting for it to get shipped off to my customer, who then finds out that it's not in line with their specification and have that absolutely awful conversation. 18:57 Yes, you nailed it. Those are the cost saving that we will get out of installation of machine vision. I like to add one more thing. On the machine vision we do have two different types of machine vision machine vision technology is based based on a camera and a separated PC. And then there are integrated a smart camera that they have a smarter chip, but it's integrated on the camera. So I want to be clear if any of the audience they have experience with smart cameras that compute based on algorithm is embedded in the camera itself. But around the effect of it. That's very true. When you do the quality inspection in advance to the processes. Let's imagine you have a silicon chip that you need to put a solder ball in and it goes through mold etc. Or I don't know even in automotive part when you are welding something and then it goes on it gets painted. Now at the end of the line then it's getting inspected and you see that defect on Do you need to do the reward on the whole car is a lot of manual engineering work, which is expensive. But if you had figured out that weld, defection early on in the processes, you could just remove it because it's so fresh and you can redo it and so you don't have the removing the paint, etc, in an automotive industry. So that's one part of it. The other part is customer credibility. You don't want to send defective products to customers. That's not good nowadays, for any 20:36 good for anybody. That's what I got Jeffery, not good. See, you know what's interesting, I believe, people like you, and others, Intel, whatever. This strive to be able to produce a to produce solutions that generate high quality products. Okay, we consumer, me and others. I'm telling you right now, we take that for granted. We take that for granted every week. I remember growing up, and I had a 57 Chevy, I still have it by the way. 57 Chevy, there are things that I just sort of accepted. The door didn't close, right? Doesn't matter. It's just that we would never, ever tolerate any, any flaws or problems with our cars. Even the inexpensive cars have a high-quality output. It just it's because of people like you. 21:35 Yes, absolutely. Because the world has changed computer is doing the job of human. And with this AI solution, they're really replacing those repetitive boring jobs, yes, to take the jobs away from employees. Actually, those type of jobs are very repetitive looking at every weld pieces to make sure that it's okay or not you might meet it is just like boring, there is not advancement for employees. So they can really give those jobs to the computers. And robots do that for us. And they do it with more accuracy and faster. 22:10 But sorry, you're you're bringing up an interesting point. And if I had a nickel every time somebody said, Hey, that AI is going to take away my job. I always say it'll take away and deal with the mundane. But the the intellectual component of your job must be done by you. 22:27 Exactly. Yes, absolutely. Actually, I think Ben, if you need to look at it this way. Maybe in the older generation, some people got used to those repetitive jobs. And kind of I would say people like to do like normal things forever. But not new generation. These people, they really grew up with computers and cell phones, etc. They don't like to work with 30 year old technology, they don't like to learn it. And they don't like to do a lot of physical job. So they really like to use their brain, they're into writing software's and thinking about designs and innovation, etc. And this new technology is a great fit for them, why it is a great fit for those leveraging the learning and that blast. When experiences that they had it the older generation. So they learned all of that they built the experiences, and now they need to transfer it to the newer generation. So some of these technology captures those learning as part of the AI solutions or trainings for these new generation. So those learning estates and would be leveraged years over years, 23:39 it I don't see any of your options. If I'm if I'm manufacturing, if I'm small man, whatever, whatever my manufacturing, business it I, I have to recognize that this I have to go down this road. I can't say business as usual, given the realities of what's taking place in the market, and the technology and the innovation that's coming out of, well, Intel right now I can't. And it's because if I do, then somebody is going to take over my job, somebody is going to put me out of business because they're going to be more efficient, more competitive, greater quality, everything that I want as a consumer, I will not be able to meet that. 24:25 I can give you an example you reminded me of a very good part of this technology, adapt adoption and transformation. A lot of smaller small medium companies they they really didn't want to adopt be the first one of adopting industry for Dotto in their manufacturers. They were waiting for others to adopted getting technology mature enough and adopting it and then suddenly pandemic hit and impacted all these smaller and medium businesses. Now they're taking get more and more seriously in Germany, in Australia, even in China, because they figured out that a lot of manual processes are happening between their factories. And now because of their pandemic and all those cocksure factories, they couldn't get enough risk center enough resources. And let me give you some use cases, that just gives you the understanding of application. For example, previously, the machine builders who build the equipment for automotive companies or, or any other factories, pharmaceutical companies, etc, they would build the machine sell it to them, and every year they would go to do software upgrade, or if there was issue, they could do their maintenance of equipment send an employee there, during COVID, that couldn't happen. So the equipment would go down. But with AI and connectivity, they can have access to the machine data, not the processes data that has the IP of the manufacturers, they can only get access to machine data and how the machine is performing. And when they see something is not working out very well, as expected. They catch it early. And they can do all these software upgrades, etc, remotely without sending any video. Just imagine how much of efficiency is in that just by adopting led by by adopting connectivity, let's say, 26:32 let's see, this was interesting, because that same in we spoke briefly about this asset reliability, I can take that same asset, collect the data, recognize the challenge, deploy somebody in maintenance, saying, Okay, now you need to screw this round piece and this whatever, you don't need anything else. That's what you need. Go out there. Do it done. You know, that that is that is so powerful. It's so impressive. It is happening now. It's now. Yeah, yeah, it's not pie in the sky. You know, Buck Rogers, stop, no, wait isn't done. All right. So So tell me, what are the roadblocks? I mean, either I'm just sort of all geeking out on all this stuff. And I'm all Yeah, I'm all in. But there are people that are pushing back? What What, what is that? roadblock? What? Why? 27:27 So actually, I think we talked about all of this goodness, that technology is bringing it to manufacturing. But how really, can we make it real? It's not a one company's job. They're an ecosystem. And actually, I think that's a beauty of the work that Intel does. We work with a broad ecosystem from software companies who build the algorithm, and is optimized an Intel silicon, we work with OEMs, who are already leveraging our silica and but we work with them to come up, come up with the flexible software defined as devices in a set of fixed function devices. We work with manufacturers itself to understand their pain points and address it in a way that really, really puts that pain point in consideration, not because technology is cool and nice. It's related to business cases for them. So this the I think, the Roadblock, the main Roadblock, is moving in synchronized way all together. Because we all need each other to make these to enable this technology and make the commercial version available for the customers to be able to deploy it. We do have that ecosystem partners. And we do have some of the solutions that are already available. But there's a still a long way to go. 28:52 So how are you you hit the nail on the head? I'm always talking about especially today. We need to collaborate? Not everybody has all the answers. No company has all the answers. No individuals have all the answers. And the only way that we're really going to continue to move forward in this brave new digital world, right? It is through collaboration. It is understanding problems. You're not going to just go out there and hey, I'm building this widget and it does this and nobody wants it. Because it's not doing anything and might solve something I don't know. But it is all about collaboration because you cannot innovate without that level of collaboration. You are absolutely on fire. so far. All right. Let's talk once again, we've got you know, we go out to industrial talk we try to promote and I know that you have some webinars coming up but we don't have really any date. So listeners, there are going to be some webinars that are going to be put on by Intel. And I think that it's important to be able to participate. Am I am I on point on there? 29:55 Yes, absolutely. We are going to have a series of webinars as you Intel industrial solution builders event. So we used to have all these in person, but because of the COVID now is virtual. And because we understand how people get bored quickly on virtual platform, we have these small, like one hour webinars that come with our partners. And we talk about the solution that are already available in the market. We talk about use cases, real world use cases. And we share the pain points and the path that these end customer manufacturing went through to find the right solution, right partner in cooperation. Fantastic webinar series is going to take place from beginning of October through mid December, please stay tuned, and we'll share the schedule with you. 30:47 Yeah, and I'll be able to let people know because that that, once again, is an important conversation to have. And listeners, you just got to keep learning, because we're all about educating, collaborating and innovating. And we've got to educate and why not learn from? I do I learned from Intel? Because I can and that's a good thing. It's not a bad thing. All right. Couple of cash questions. First off, I want to get a hold of you. How do I as a listener, get a hold of you? What's the best way? 31:16 Absolutely. I'm on LinkedIn, please feel free to send me messages. And I'd be more than happy to help. And I think that would be the best thing easiest and fastest in the world of technology. 31:31 exciting time. I'm telling you. There's a hobby that I like, of myself. I like I like cooking. If you can believe that. I love cooking. I love it a lot. Can you share with me because I'm such a bozo about this. A recipe. When I say recipe, what was one of your favorite foods growing up? 31:52 Oh, interesting. Well, I I from Middle East and Iran specifically. So kebab is my favorite foods. So it's K, A, B, or p. 32:07 Got it? kebab. See soap. Okay, see, I love that stuff. So I'm going to do this, I'm going to I'm going to cook some kababs. And then I'm going to demonstrate that I support her because I love cooking. And I love that you were fantastic. Spot on. All right, listeners, we're going to have all the contact information for Sahar, we're going to also be able to just just bear with me on the events that are being put out by Intel, they will be out there for you or not. It'll all be out there. Thank you so hard. Thank you very much for joining industrial talk. 32:48 Absolutely. It was a pleasure. And as you know, we all are very passionate about technology and the positive outcome that it brings. 32:59 Yeah, it's so funny. I get to talk to people who are not passionate. I haven't unfortunately for me, I haven't come across anybody that says, Yeah, we're just deploying some AI. No, nobody does that. everybody's like, Yeah, man. We're doing this. And we're doing that. And it's like, it's exciting. All right, listeners. Thank you very much. We're gonna be wrapping it up on the other side. Stay tuned. You're listening to the industrial talk Podcast Network. 33:31 All right. Oh, Hardy, eight, I mean, hearty Thank you to Sahar and Team, Intel. And what they are doing in the world of manufacturing is it's an exciting time, as I mentioned in the interview, exciting time, great time to be alive. Let's focus in on all the positives that are taking place. And just remember, industry, you're changing worlds, you're changing lives, that means you are doing great things. And we need you. We need you to educate that's again, go out to industrial Academy, right? It's out there on industrial talk.com. And if you want to participate in it, great. If you want to be an instructor, great. If you I'll try to make it as easy as I possibly can. We've got to get your information, your insights, your wisdom, out to the masses, so that we can educate as many people as we possibly can have all the exciting stuff, all of the cool tech, all of the innovations that have taken place. Be bold, be brave, dare greatly hang out with bold, brave and daring greatly. You're going to be changing the world. Thank you very much for joining. It does real talk. We will be back with another great interview.

Transcripts

SUMMARY KEYWORDS

manufacturing, intel, industrial, ai, sahar, technology, data, discrete manufacturing, absolutely, people, machine, industry, listeners, learn, happening, vision, line, processes, customers, factories

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Industrial Talk is brought to you by NEOM that's NEOM.com they have a vision of changing the world for the better in almost every way. They are committed to that. They have a bold, a brave and daring greatly vision on how to change the world. For the better for all of us. They are committed to that. Go out to niobe.com get involved, you will be dazzled and you will not be disappointed. Big thinking going on there. And you know what's happening out there. Technology. Innovation is happening everywhere. And the speed at which is just absolutely blistering. You know who's leading the way Intel that's right Intel, they are leading the way with edge cloud. You name it industry for Dotto, right in their wheelhouse smart cities. Yes, robotics. Yes. And, and let's say digital transformation of the utilities. Yes, Intel is where you want to go go out to intel.com find out more and see how they can help you innovate. Welcome to the industrial talk podcast with Scott MacKenzie. Scott is a passionate industry professional dedicated to transferring cutting edge industry focused innovations and trends while highlighting the men and women who keep the world moving. So put on your hardhat grab your work boots, and let's go Alright, welcome again to industrial talk v number one location in the universe that celebrates you industrial heroes, you are bold, you are brave, you dare greatly you solve problems, you innovate like no other and you are changing lives and the community Do not forget that put that in your pocket because it is important because you got to believe we need you big big time in the hot seat in the Industrial Talk we have Sahar Ehsani, she is with Intel, we are talking about manufacturing technology. She is a senior center segment market lead discrete manufacturing. And, you know, we're gonna be talking about Yep, AI, machine vision, sustainability and how all that works to go there. Let's get cracking. So you get to join me on my educational Odyssey to learn from the very best in industry about that man, you get to join me, I again, I you know, you got you got incredible professionals, such as Sahar and, and she knows what she's talking about. And also people from Intel and others, that are just absolutely one. Thank goodness that they desire to truly develop, develop the innovations to be able to make our lives better, thank goodness. And you know what else is so great that they're willing to share their insights and wisdom for us, so that we can begin to learn you never stop learning? Each day, always learn that, I don't know, it doesn't sound so fantastic. But it is it got to there's it's all out there. And especially in industry, we've got to do that. Alright, let's talk a little bit about the industrial Academy. Real quick. The industrial Academy is absolutely dedicated to education. And the reason it's dedicated to education is because, well, that's something nobody can really take away from you. If you are dedicated if you are committed if you have a true desire to learn from the very best within industry, industrial academies where you want to be because we're we're talking about management leadership, we're talking about innovation, we're talking about the nuts and bolts of operations. And what are the strategies associated with not in a way that is like, Oh, my gosh, this is a 75 hour class and and it'll drive you crazy? No, no, the responsibility on your part is one, that you get the flavor you get to hear from the best that represents let's say IoT, or edge or cloud or reliability, whatever might be the best. And it's up to you because you have a spirit of learning is to go out and find out more all the contacts and information is out there. It is a big, big win for you continue to learn, grow, and and just, you know be the best you possibly can be because

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for whatever reason, maybe I've got rose colored glasses. I can't tell you why. But I really truly in my heart of hearts, believe that industry is truly the key that can change lives, change communities and change the world. And it might be Pollyanna. It might be Well over the top. I like bold, brave goals. And and the industrial Academy is focused on being able to provide industrial education for people who need to know. So that their lives can be changed, their companies can be changed, their communities can be changed, and so on. And so the world. Alright. Let's get going. I get all Tingley about that type a type of conversation now. So hard, but it's been a bit of a long journey to get her on the podcast. But fear not she does not disappoint. great conversation, great insight, great stuff that's happening at Intel. I've got her form here, you go out and find her stat guard. All very impressive. So we're going to be talking and yeah, you're gonna say, Scott, Oh, you've already talked about AI? Yeah, we have. But it never stops, continues to grow continues to evolve, we never stopped. You know, we've talked about machine vision, looking at the ability to look at products and improve the quality and so on and so forth. And of course, sustainability. What does that mean? How does all this wonderful innovation help sustainability because it also has to sort of work hand in hand. If there's a gap that is missing from that particular value chain. Now, that's a problem. But Intel sohar team Intel are working diligently not just in manufacturing, but also in in the energy space and oil and gas all everything that you could possibly at the heart, you know, entails right there. All right. Enjoy this particular interview with Sahar Sahar, welcome to industrial talk. How are you doing?

06:47

doing very well. How are you, Scott?

06:49

It's been a long time in the making to try to get you on the podcast.

06:54

Yeah, sorry. It's my bad I might sign.

06:58

You don't need to you don't need to cower away from me. I was just I was so excited when we first met. And, but but business moves on people get busy. It's all about that. But you're here right now. And listeners, you're going to be impressed. She's got a mad statcard out there on LinkedIn. Absolutely. Of course, I'm looking at her form. And that's impressive, too. So you Listen up, learn educate with me, because I'm not the sharpest tool in the shed. But Sahar is she's a sharp tool in the shed. All right, for the listeners. So Mark, give us a little background on who you are.

07:34

salutely first of all, it's a pleasure to be here, Scott, and have this conversation with you. I'm very excited for this conversation. And about myself. I'm big global segment lead for discrete manufacturing industry at Intel IoT group. So basically what I've been doing in align my career in Intel, and outside of Intel, I've been engaged with manufacturing, all my career. And in my current role, what I do is of working with partner and manufacturing and customers to facilitate and accelerate the digital transformation that's taking place currently around the goal. It is listeners, it's really awesome. It's very exciting. We are just in the front of the line and helping everyone to make those cyphy in

08:35

the future baby in the future is now man, it's now

08:40

all those things that we were seeing in the movies is now happening. And it's very exciting.

08:44

It is. I was just watching Minority Report and and some of the things that they're going through. It's like, Oh, that's happening now. Oh, that's cool. Oh, you know, it's pretty exciting. Now, I'm not. Again, we've established I'm not the sharpest tool in the shed, can you define discrete manufacturing? How's that different than well manufacturing?

09:03

Absolutely, yes. So, when we look at the manufacturing Overall, we can divide it to two or three segments, let's say three segments, for the simplicity, one is discrete manufacturing, then you will have individual product as an outcome but those products can be assembled through bringing different parts from different location in one place. They can be built all in one place or they can be built around the globe apart and get assembled like automotive industries, right, like consumer goods, like electronic and devices. So all those parts some can be made in China, some in Vietnam, etc. They come out to another Assembly Facility and they get assembled and after their life is done, you can disassemble them again and cycle them. But when it comes to their hybrid, that's another section of manufacturing hybrid, which is the process and discrete manufacturing together. It has like some sort of batch processing like food and beverage. So for example, if you mix two chemicals with each other for pharmaceutical, you need to continue that process, you cannot stop it, you cannot ship it to somewhere else around the world. Because, yeah, so that's part of the process industry, but batch processing, because things get prepared in batches. And then at the end of the day, get they get packaged, which is part of the discrete manufacturing, that's what they call them hybrid. The other one is continuous process manufacturing, like oil and gas, right? You see a wealth of oil, you cannot stop it, that needs to continue, and you need to keep take care of those processes. They call it continuous processing.

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I like it. That's a good explanation. Now, listeners, you're better because of that explanation. Now, you know, don't, don't come to me and say, Scott, I don't know. All right. One of the topics that we're going to be talking about, and what we're going to feature on this particular conversation is going to be talking about AI. AI is application to manufacturing, and, and artificial intelligence, this machine vision stuff, give us a little just sort of your definition of, of artificial intelligence, and its application and manufacturing.

11:32

Absolutely. Let me give you a little bit background on bringing in this technology to manufacturing Overall, we want to make manufacturing smarter. We know in some of those manufacturing, like automotive, there are lots of automations already going on. We know my factoring like silicon manufacturing, like silicon chip, like Intel, when you look at their main factories is really well automated. So what is AI is really bringing to the table for those very fully automated manufacturing. When you add AI, basically, you leverage tons of data that is being generated by those automatic automatic devices. So you get that data, you analyze it, you make a decision based on the result of that. So that's what artificial intelligence does. If you get the result, and immediately as a control rule, feed the information back to the manufacturing line, that's a closed loop control. And during that you have the real time control of the manufacturing production. And then all of this together improves the manufacturing processes and efficiencies improve manufacturing uptime, right. So if you want to look at the strategy of how the technology are coming to the manufacturing board, I believe personally, AI and machine vision are going to be the front of the line, because they are easy additions to the already existing technologies in manufacturing, whether very advanced manufacturing, like auto or semiconductor, or they manual type of manufacturing, like machine builders, so you can add or port builders or textile companies in China. So let me explain a little bit about how AI works.

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But let me interrupt real quick, let me interrupt real quick. So what I hear you saying is that it's it starts, it starts with the ability to collect data, but there's a tsunami of data for lack of a better term, I me, Scott, is I'm not going to go through a spreadsheet, look at all the data that's coming off of machines or though or the line, I need some technology to help facilitate and make some decisions that allow good data to come through and throw away the bad data. Is that right?

14:02

Exactly. That's absolutely true. And that's artificial intelligence. You connect it on connected if they're not connected already. And then you collect the data, and you analyze the data. And based on that analysis, that happens automatically, you make a decision, what you want to do next

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is your zero learning component to AI. It's one thing I can create parameters, I would imagine you're the expert, I can create parameters that certain data gets through is that can that can I learn and be and hone and be more refining? as I grow and be able to improve the analytics of that data for my my business?

14:45

Play? Yes, the data machine learning aspect of it. So the algorithm that you add to the computer that is running that algorithm basically, it gets better and better terabit more data, one of the main challenges that we currently have in the manufacturer is that they have a very high yield is finding bad parts. Because if you want the device to, to locate the bad part in a production line, you first need to teach that algorithm what a bad bad part is. So if a manufacturer has a very high yield means that they do not produce so many bad data. So sometimes it takes three months to collect bad data in order to train that algorithm. And those algorithms, they get better over time as we get more data through them.

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And it I would imagine, so hard that that, if I want to be competitive going forward, if I want to be that, I want to have some sort of legacy sustainability, when it comes to my business, I'm going to have to embrace this, I'm going to have to figure it out. But you know what the problem I have, and help me understand this. I just think of costs, I think it's going to be expensive. I know today, what I'm looking at. And if you're telling me I got to go down this road, I have, I don't have that clarity, what what's the economics behind all this, that's

16:15

a very reasonable, actually concerned by any type of manufacturing managers or executives. So we all if you're living in a very competitive board, all the customers, they want perfect products, but cheaper, and everyone is trying to pay that. So in order to keep that profit margin for my factors and keep our business running, they need to have solutions that make business sense. And usually, that's why that I was thinking that AI and machine vision, powered by AI, our best solution to start speed, because you don't need to change much on your manufacturing line, you just add the machine vision, you assess the quality of your devices, and usually within eight to 12 months, you get the positive ROI.

17:07

Spectacular, you know that? That is without spectacular. I mean, if if I had I mean, I was evaluating investments that had a three to five payback, right? took three to five years just to start looking at things that are positive. And that's pretty common. Now, but I don't want to gloss over this. But explain what machine vision is? Oh,

17:31

yes, let me explain what machine vision is. So let's imagine that you have a factory line that has a product and you want to inspect it, you put a camera on it, and you connect the camera to a piece of compute. And machine vision actually is capturing those images, and analyzing those images through a AI algorithm on that compute. So there are different type of there are different types of technologies being used. anomaly detection is one of the paths that people take, basically, looking into good and bad data, the good data, you don't mind you just say good data good go away. You don't want to keep them but the bad data you can locate and you can say this part is bad. So that's how machine vision boards by looking taking images and being connected to compute that has AI algorithm on it.

18:29

So this is how I see it happening this I see it rolling out. If I am able to deploy AI deploy the machine vision in the right area, I might capture anomalies within my manufacturing quicker compressing that time, not waiting for it to get shipped off to my customer, who then finds out that it's not in line with their specification and have that absolutely awful conversation.

18:57

Yes, you nailed it. Those are the cost saving that we will get out of installation of machine vision. I like to add one more thing. On the machine vision we do have two different types of machine vision machine vision technology is based based on a camera and a separated PC. And then there are integrated a smart camera that they have a smarter chip, but it's integrated on the camera. So I want to be clear if any of the audience they have experience with smart cameras that compute based on algorithm is embedded in the camera itself. But around the effect of it. That's very true. When you do the quality inspection in advance to the processes. Let's imagine you have a silicon chip that you need to put a solder ball in and it goes through mold etc. Or I don't know even in automotive part when you are welding something and then it goes on it gets painted. Now at the end of the line then it's getting inspected and you see that defect on Do you need to do the reward on the whole car is a lot of manual engineering work, which is expensive. But if you had figured out that weld, defection early on in the processes, you could just remove it because it's so fresh and you can redo it and so you don't have the removing the paint, etc, in an automotive industry. So that's one part of it. The other part is customer credibility. You don't want to send defective products to customers. That's not good nowadays, for any

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good for anybody. That's what I got Jeffery, not good. See, you know what's interesting, I believe, people like you, and others, Intel, whatever. This strive to be able to produce a to produce solutions that generate high quality products. Okay, we consumer, me and others. I'm telling you right now, we take that for granted. We take that for granted every week. I remember growing up, and I had a 57 Chevy, I still have it by the way. 57 Chevy, there are things that I just sort of accepted. The door didn't close, right? Doesn't matter. It's just that we would never, ever tolerate any, any flaws or problems with our cars. Even the inexpensive cars have a high-quality output. It just it's because of people like you.

21:35

Yes, absolutely. Because the world has changed computer is doing the job of human. And with this AI solution, they're really replacing those repetitive boring jobs, yes, to take the jobs away from employees. Actually, those type of jobs are very repetitive looking at every weld pieces to make sure that it's okay or not you might meet it is just like boring, there is not advancement for employees. So they can really give those jobs to the computers. And robots do that for us. And they do it with more accuracy and faster.

22:10

But sorry, you're you're bringing up an interesting point. And if I had a nickel every time somebody said, Hey, that AI is going to take away my job. I always say it'll take away and deal with the mundane. But the the intellectual component of your job must be done by you.

22:27

Exactly. Yes, absolutely. Actually, I think Ben, if you need to look at it this way. Maybe in the older generation, some people got used to those repetitive jobs. And kind of I would say people like to do like normal things forever. But not new generation. These people, they really grew up with computers and cell phones, etc. They don't like to work with 30 year old technology, they don't like to learn it. And they don't like to do a lot of physical job. So they really like to use their brain, they're into writing software's and thinking about designs and innovation, etc. And this new technology is a great fit for them, why it is a great fit for those leveraging the learning and that blast. When experiences that they had it the older generation. So they learned all of that they built the experiences, and now they need to transfer it to the newer generation. So some of these technology captures those learning as part of the AI solutions or trainings for these new generation. So those learning estates and would be leveraged years over years,

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it I don't see any of your options. If I'm if I'm manufacturing, if I'm small man, whatever, whatever my manufacturing, business it I, I have to recognize that this I have to go down this road. I can't say business as usual, given the realities of what's taking place in the market, and the technology and the innovation that's coming out of, well, Intel right now I can't. And it's because if I do, then somebody is going to take over my job, somebody is going to put me out of business because they're going to be more efficient, more competitive, greater quality, everything that I want as a consumer, I will not be able to meet that.

24:25

I can give you an example you reminded me of a very good part of this technology, adapt adoption and transformation. A lot of smaller small medium companies they they really didn't want to adopt be the first one of adopting industry for Dotto in their manufacturers. They were waiting for others to adopted getting technology mature enough and adopting it and then suddenly pandemic hit and impacted all these smaller and medium businesses. Now they're taking get more and more seriously in Germany, in Australia, even in China, because they figured out that a lot of manual processes are happening between their factories. And now because of their pandemic and all those cocksure factories, they couldn't get enough risk center enough resources. And let me give you some use cases, that just gives you the understanding of application. For example, previously, the machine builders who build the equipment for automotive companies or, or any other factories, pharmaceutical companies, etc, they would build the machine sell it to them, and every year they would go to do software upgrade, or if there was issue, they could do their maintenance of equipment send an employee there, during COVID, that couldn't happen. So the equipment would go down. But with AI and connectivity, they can have access to the machine data, not the processes data that has the IP of the manufacturers, they can only get access to machine data and how the machine is performing. And when they see something is not working out very well, as expected. They catch it early. And they can do all these software upgrades, etc, remotely without sending any video. Just imagine how much of efficiency is in that just by adopting led by by adopting connectivity, let's say,

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let's see, this was interesting, because that same in we spoke briefly about this asset reliability, I can take that same asset, collect the data, recognize the challenge, deploy somebody in maintenance, saying, Okay, now you need to screw this round piece and this whatever, you don't need anything else. That's what you need. Go out there. Do it done. You know, that that is that is so powerful. It's so impressive. It is happening now. It's now. Yeah, yeah, it's not pie in the sky. You know, Buck Rogers, stop, no, wait isn't done. All right. So So tell me, what are the roadblocks? I mean, either I'm just sort of all geeking out on all this stuff. And I'm all Yeah, I'm all in. But there are people that are pushing back? What What, what is that? roadblock? What? Why?

27:27

So actually, I think we talked about all of this goodness, that technology is bringing it to manufacturing. But how really, can we make it real? It's not a one company's job. They're an ecosystem. And actually, I think that's a beauty of the work that Intel does. We work with a broad ecosystem from software companies who build the algorithm, and is optimized an Intel silicon, we work with OEMs, who are already leveraging our silica and but we work with them to come up, come up with the flexible software defined as devices in a set of fixed function devices. We work with manufacturers itself to understand their pain points and address it in a way that really, really puts that pain point in consideration, not because technology is cool and nice. It's related to business cases for them. So this the I think, the Roadblock, the main Roadblock, is moving in synchronized way all together. Because we all need each other to make these to enable this technology and make the commercial version available for the customers to be able to deploy it. We do have that ecosystem partners. And we do have some of the solutions that are already available. But there's a still a long way to go.

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So how are you you hit the nail on the head? I'm always talking about especially today. We need to collaborate? Not everybody has all the answers. No company has all the answers. No individuals have all the answers. And the only way that we're really going to continue to move forward in this brave new digital world, right? It is through collaboration. It is understanding problems. You're not going to just go out there and hey, I'm building this widget and it does this and nobody wants it. Because it's not doing anything and might solve something I don't know. But it is all about collaboration because you cannot innovate without that level of collaboration. You are absolutely on fire. so far. All right. Let's talk once again, we've got you know, we go out to industrial talk we try to promote and I know that you have some webinars coming up but we don't have really any date. So listeners, there are going to be some webinars that are going to be put on by Intel. And I think that it's important to be able to participate. Am I am I on point on there?

29:55

Yes, absolutely. We are going to have a series of webinars as you Intel industrial solution builders event. So we used to have all these in person, but because of the COVID now is virtual. And because we understand how people get bored quickly on virtual platform, we have these small, like one hour webinars that come with our partners. And we talk about the solution that are already available in the market. We talk about use cases, real world use cases. And we share the pain points and the path that these end customer manufacturing went through to find the right solution, right partner in cooperation. Fantastic webinar series is going to take place from beginning of October through mid December, please stay tuned, and we'll share the schedule with you.

30:47

Yeah, and I'll be able to let people know because that that, once again, is an important conversation to have. And listeners, you just got to keep learning, because we're all about educating, collaborating and innovating. And we've got to educate and why not learn from? I do I learned from Intel? Because I can and that's a good thing. It's not a bad thing. All right. Couple of cash questions. First off, I want to get a hold of you. How do I as a listener, get a hold of you? What's the best way?

31:16

Absolutely. I'm on LinkedIn, please feel free to send me messages. And I'd be more than happy to help. And I think that would be the best thing easiest and fastest in the world of technology.

31:31

exciting time. I'm telling you. There's a hobby that I like, of myself. I like I like cooking. If you can believe that. I love cooking. I love it a lot. Can you share with me because I'm such a bozo about this. A recipe. When I say recipe, what was one of your favorite foods growing up?

31:52

Oh, interesting. Well, I I from Middle East and Iran specifically. So kebab is my favorite foods. So it's K, A, B, or p.

32:07

Got it? kebab. See soap. Okay, see, I love that stuff. So I'm going to do this, I'm going to I'm going to cook some kababs. And then I'm going to demonstrate that I support her because I love cooking. And I love that you were fantastic. Spot on. All right, listeners, we're going to have all the contact information for Sahar, we're going to also be able to just just bear with me on the events that are being put out by Intel, they will be out there for you or not. It'll all be out there. Thank you so hard. Thank you very much for joining industrial talk.

32:48

Absolutely. It was a pleasure. And as you know, we all are very passionate about technology and the positive outcome that it brings.

32:59

Yeah, it's so funny. I get to talk to people who are not passionate. I haven't unfortunately for me, I haven't come across anybody that says, Yeah, we're just deploying some AI. No, nobody does that. everybody's like, Yeah, man. We're doing this. And we're doing that. And it's like, it's exciting. All right, listeners. Thank you very much. We're gonna be wrapping it up on the other side. Stay tuned. You're listening to the industrial talk Podcast Network.

33:31

All right. Oh, Hardy, eight, I mean, hearty Thank you to sohar. Team, Intel. And what they are doing in the world of manufacturing is it's an exciting time, as I mentioned in the interview, exciting time, great time to be alive. Let's focus in on all the positives that are taking place. And just remember, industry, you're changing worlds, you're changing lives, that means you are doing great things. And we need you. We need you to educate that's again, go out to industrial Academy, right? It's out there on industrial talk.com. And if you want to participate in it, great. If you want to be an instructor, great. If you I'll try to make it as easy as I possibly can. We've got to get your information, your insights, your wisdom, out to the masses, so that we can educate as many people as we possibly can have all the exciting stuff, all of the cool tech, all of the innovations that have taken place. Be bold, be brave, dare greatly hang out with bold, brave and daring greatly. You're going to be changing the world. Thank you very much for joining. It does real talk. We will be back with another great interview.