Utilizing Artificial Intelligence for Efficient Data Collection with Akshat Thirani

Episode 194 | Challenges: Leadership Growth Process Workforce Technology

ai

Data collection has taken many forms in the history of manufacturing, and now is the time to embrace the most efficient form yet - artificial intelligence. Guest speaker, Akshat Thirani, shares how he solved the software disparity between computer engineers and manufacturers and created a tool to enable manufacturing leaders to meet their goals as efficiently as possible. AI isn’t something to fear. Without change - nothing will happen in your business!

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From India to Chicago: Akshat’s manufacturing journey

Growing up in India, Akshat’s childhood was saturated in the manufacturing industry. All of his family and friends had some part in the local manufacturing and production business, and his father raised his children with a manufacturer's mindset. With manufacturing in his blood, Akshat set off for college at the age of 17, studying design engineering and computer software. It was at school that he first noticed the gaping disparity between what computer software engineers were utilizing and what leading manufacturing engineers were using - even though the manufacturers were handling some of the most complex and technical work in the world. Akshat knew he needed to create a tool that would enable manufacturers to work and live to their full potential - a tool that would help them track production time, maintenance, and the data produced by their machines. 

 

 

Why manufacturers need to embrace AI and more efficient data collection 

Akshat understood that it was no trivial thing to join an AI tool to a machine and start collecting data. Many shops utilize both old and new machinery - making the job of AI more difficult. Akshat knew that the tool he was creating needed to be simple and able to read the “heartbeat” of each machine and distinguish what job was being completed. 

The “heartbeat” of a machine is the signature electrical current that it produces. During his senior year in college, Akshat and some of his colleagues created the prototype AI tool he had dreamed of. It eventually became the answer to the machinist’s problems with efficient data collection. Instead of jotting down on pieces of paper or having to manually insert data about a machine or job into an Excel spreadsheet, AI can be hooked up to a machine and learn the heartbeat of specific jobs and functions. AI then transmits that data to a centralized, online platform through cellular data - allowing the manufacturing team to quickly read the pulse on their machinery and work. 

 

 

Meeting the needs of the Metal Working Nation through artificial intelligence 

Every individual on a manufacturing team has expertise that is wasted when they are required to spend time collecting, recording, and analyzing data from each machine. Instead of having the professionals do the busywork, AI can read, transmit, organize, and analyze the data outsourced by the machinery. Providing real-time data to team members, Akshat’s AI tools can record the speed of each machine being used, which machines need maintenance, the estimated timetable for a piece or job, and the reasons why a machine is not running at optimum capacity. Meeting the core manufacturing goals of simplicity and practicality, AI is something that the leaders of the Metal Working Nation need to be taking seriously and educating themselves on. 

 

 

Ensuring that your technology fits your company goals

 Every manufacturing business will have different long-term goals and immediate needs. Akshat encourages listeners to walk through their shops and talk with their team members to identify what needs to be accomplished through an AI tool such as Akshat’s. Calculating the cost of integrating AI into the system may be surprisingly less than what is being spent on manual data collection. Identify what you need to accomplish work more efficiently - and then make it happen.

 

Because if you’re not making chips, you’re not making money! 

 

BAM!

 

 

Here’s The Good Stuff!

  • If you don’t change, nothing will happen. 
  • Artificial intelligence is helping manufacturers pave the way forward. 
  • Guest speaker Akshat Thirani - CEO of Amper Technologies. 
  • Akshat’s love for manufacturing is a generational story. 
  • Solving the disparity between online software and manufacturing tools. 
  • Solving the code of machinery heartbeats. 
  • Creating a more efficient workspace for all members of the team. 
  • Know what the goal is - then take action. 

Tools & Takeaways

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This Week’s Superstar Guest: Akshat Thirani

 

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Jason Zenger: Jim, I heard you muttering something about a sheet metal job. Are you doing sheet metal now? I know you're a C&C machine shop but-

Jim Carr: We're specialists in three and four axis C&C machining, however, when our customers send a big package to us and they happen to just throw in a couple of sheet metal jobs, I use Xometry to quote the job and do it for me. It's really great. I don't have to say no to that line item because, let me tell you, procurement wants to do business with people that are easier to work with.

Jason Zenger: They want to deal with nice guys like Jim and Jason too.

Jim Carr: Exactly. If I have a job in part of a package that has a sheet metal job in it. I can use Xometry as my partner to do that work from me. And I-

Jason Zenger: They also do plastic injection molding and 3D printing.

Jim Carr: They do, they're experts at three, four and five axis-

Jason Zenger: Five axis.

Jim Carr: ... C&C machining in close tolerance and finishing as well. But no, definitely you can use them for sheet metal. It's great, just go to xometry.com. X-O-M-E-T-R-Y.com.

Jason Zenger: You bet.

Jim Carr: Check it out.

Jim Carr: Welcome to Making Ships. We believe that manufacturing is challenging, but if you are connected to a community of leaders you can elevate your skills, solve your problems, and grow your business.

Jim Carr: I'm your host, Jim Carr, and I'm joined by my co-host Mr. Jason JZ Senger. How you doing?

Jason Zenger: I'm good. You did a good job of reading that introduction-

Jim Carr: Thank you.

Jason Zenger: ... but still think a robot would do a better job than you.

Jim Carr: You think so?

Jason Zenger: I do, yeah.

Jim Carr: I didn't even have my glasses on and I read it, but I brought up the text font really big so I could see without my readers on.

Jim Carr: How you doing?

Jason Zenger: A robot would do a better job.

Jim Carr: How are you doing?

Jason Zenger: I'm good. How are you?

Jim Carr: Good. We are here at Fusion OEM in Burr Ridge, Illinois today. We're doing a remote recording with a really dynamic that's going to talk about artificial intelligence.

Jason Zenger: And data collection.

Jim Carr: And data collection, and where automation of the machine shop is heading, right?

Jason Zenger: Yeah, I'm excited.

Jim Carr: Because that's really important to me as an owner of a machine shop and I know it's important to you, and I know it's important to a lot of people that listen to the show, so-

Jason Zenger: Yeah, but it's got to make everybody a little bit nervous because it's high tech and it's not-

Jim Carr: I'm not nervous.

Jason Zenger: I think you are.

Jim Carr: I'm not nervous.

Jason Zenger: I think you're just-

Jim Carr: Do I look nervous?

Jason Zenger: You're trying to act like a tough guy, but I think you're ... I only say this because the manufacture leaders out there, they're really good at what they do, but now we're starting to incorporate so many technologies into the industry that are just like, wow, artificial intelligence and robotics, all this ... It's just different.

Jim Carr: Oh, it's so-

Jason Zenger: Definitely different. Well if we do not change, nothing's going to happen.

Jim Carr: Yes.

Jason Zenger: Our culture that we live in and breath in, and work in is susceptible to change. If we do not change and we do not advance we're going to be-

Jim Carr: I agree.

Jason Zenger: ... a country and an industry that is not going forward.

Jim Carr: I agree.

Jason Zenger: It's imperative that we change, so we've got to do it and it's really important.

Jim Carr: Every time we read about news as it relates to robotics, or artificial intelligence, or whatever else in manufacturing, they always talk about China's going to have five times as many robots. But hey, listen here, in the United States we should not be counted out. I think that we can compete here and we just need to learn and we need to try and we need to figure it out, and we can do it better.

Jason Zenger: I agree. I could not agree more.

Jason Zenger: Anyway, it's good to be here at Fusion with our friend Craig Zoberis is doing a show today on co-bot technology which is much like robotic technology, it's collaborative robots, which is going to be interesting. We're going to have him in the study after this interview, but man, he's got a great turnout today and it looks like it's going to be a really good day.

Jason Zenger: The only thing is we're dead smack in the middle of summer and it's like 100 degrees outside. But it's always great to be here with Craig. He's a little nervous. Did you see him when we walked in?

Jim Carr: He's just busy.

Jason Zenger: He's busy. You're nervous, he's busy.

Jim Carr: Well, I don't know about that.

Jim Carr: But anyway, Jason, what is keeping you awake at night? We always talk about this. We changed it up a little bit and now we're talking about what's keeping us awake, not what's new at your company, not what's new with Zengers. What's on your brain?

Jason Zenger: A lot of times when you know that you're making the right decisions for your company it's still any kind of change that you're making keeps you up a little bit.

Jim Carr: You had a bad week, didn't you?

Jason Zenger: No, I didn't have a bad week. It's been a great week actually. When you make personnel changes and they're necessarily, and you have a direction for your company that you're going into, it's exciting but it's a change and some of those people changes are tough, but they're good. I'm excited and the future is good, and-

Jim Carr: Did you have 36 hours of pain?

Jason Zenger: No, I-

Jim Carr: You didn't?

Jason Zenger: I had a couple hours of pain.

Jim Carr: Okay, so then it was the right decision for you sure.

Jason Zenger: Yeah, for sure.

Jim Carr: For sure, okay good.

Jason Zenger: There's some decisions that are easier than others.

Jim Carr: Yes, I agree.

Jason Zenger: Especially when you're wronged, then it's easier to make.

Jim Carr: Yes, then it is, I agree.

Jason Zenger: We could talk about this on a future show, you just have to have the right processes in place when you make those kind of decisions.

Jim Carr: I agree.

Jason Zenger: What about you? What's keeping you up at night?

Jim Carr: Basically the same thing. We're very busy at Carr and it's all capacity issues right now. We're near capacity. With capacity issues comes talent, infrastructure, do we have enough floor space, do we have enough machinery and equipment, developing layers of leadership because as you grow you have to put in layers of leadership in between chs one and that one to-

Jason Zenger: That's a big change for you.

Jim Carr: That's a big change for me. It's going to be a struggle, but I'm welcome to it and I look forward to it. But it's definitely a challenge.

Jason Zenger: I-

Jim Carr: It definitely keeps me awake at night.

Jason Zenger: I always had this joke with my dad because when Zengers was only say like a dozen people, we'd be in the tool store and he'd look to the left and look to the right and he'd see 90% of his employees, now we have 45-50 people and it's not like that and it brings us challenges. You grow beyond where you're at now, you're going to have some of those same challenges.

Jim Carr: I know, I know.

Jason Zenger: I was actually thinking about you when I was in the gym recently because-

Jim Carr: Why, because I work out harder and I'm in better shape than you?

Jason Zenger: Well, no.

Jim Carr: Okay.

Jason Zenger: I saw a thing about retirement on the TV. It was just as I was working out you're walking by and you see the TV monitors and stuff. I listen to podcasts while I'm working out, but-

Jim Carr: You do?

Jason Zenger: I do. But it rated the top places to retire and Nebraska was number one. I was like, oh Jim always talks about-

Jim Carr: That shop owner in Nebraska, part of the middle [crosstalk 00:06:44].

Jason Zenger: And maybe as your capacity go up maybe Nebraska should be not only your retirement location, but also where you open up-

Jim Carr: I don't know.

Jason Zenger: ... Carr Machine South or West, or whatever.

Jim Carr: West. Honestly, I've only been through Nebraska when we did a lot of camping and we were coming back from the West, but never really spent a lot of time there, so I don't know. Would you call that a metaphor when I say a shop in Nebraska or when I make that relation? I don't mean anything negative, I just mean that's a very rural area. To me, it seems very rural and I always feel like I'm talking to that guy.

Jason Zenger: You can call it a metaphor if you want to.

Jim Carr: Thank you.

Jason Zenger: When you miss words it's cute.

Jim Carr: I know.

Jason Zenger: It's fine.

Jim Carr: It is cute. It is cute. What's going on with the Boring Bar? Does the metalworking nation know what the Boring Bar is [crosstalk 00:07:29].

Jason Zenger: I want you to explain.

Jim Carr: Is it a place where I can go, you could go, or the metalworking nation can go and get a shot and a beer, or a bottle of wine?

Jason Zenger: It will be eventually, but before then, what is it now?

Jim Carr: What is right now? Well I know what it is, it's our weekly newsletter and there's a lot of good information there. There's a link to every single week's podcast there. There's curated news articles with [crosstalk 00:07:50].

Jason Zenger: How do you get access to the Boring Bar?

Jim Carr: All you have to do is text chips, C-H-I-P-S, to 38470 or you can go to makingchips.com and subscribe right there. The texting thing is really cool. We just started that about four weeks ago and man, as soon as I did that it was like boom, I was signed up in no time. All you got to do is text chips, C-H-I-P-S, to 38470 and you are done.

Jason Zenger: I'm going to do it right now.

Jim Carr: Anyway, Jason, what is our manufacturing news for this week?

Jason Zenger: It's got to be relevant and timely.

Jim Carr: It is. Our manufacturing news is from americanmachinist.com.

Jason Zenger: I know that publication.

Jim Carr: I actually don't.

Jason Zenger: You don't?

Jim Carr: No. But I'm happy to have been acquainted with them. The title of the article is "How AI and IOT Will Provide Insights for Manufacturers" and-

Jason Zenger: Can we define what those two acronyms are?

Jim Carr: Sure. AI is artificial intelligence. In a nutshell, artificial intelligence would be getting non-human machines, computers, stuff like that, to make decisions and act like humans, essentially. Like an AI podcast host that I'm going to replace you with, eventually.

Jason Zenger: Good, good. Well-

Jim Carr: I'm going to have the computer listen to all the past episodes.

Jason Zenger: Just make sure that you send that electronic pension check right into my checking account-

Jim Carr: Got it.

Jason Zenger: ... every week.

Jim Carr: I think that they can imitate your voice and I'll have it listen to past episodes and be just like you except better.

Jason Zenger: Good. And IOT?

Jim Carr: IOT is the Industrial Internet of Things. They mention it here as IIOT. I don't really here it that much [crosstalk 00:09:19] as IOT. Most people say IOT, which is the Internet of Things and they apply it to the manufacturing space. Once again, when I talk about being nervous, it's not actually nervous, but I think that manufacturing leaders out there really need to do some research and see how these types of technologies can impact their business, but what we're talking about here is you're collecting data and then essentially with these IOT devices, then you have your acritical intelligence, which instead of just displaying the data, it can actually help you to make decisions, or make decisions for you.

Jason Zenger: I guess a simple way of describing it Jim would be like if you were able to use artificial intelligence to manage your supply chain, so when to buy materials and stuff like that.

Jim Carr: What do you think the percentage of the metalworking nation out there right now is using some form of AI?

Jason Zenger: Very little.

Jim Carr: Is it less than 10%.

Jason Zenger: Yeah, I would say so. I'm not saying that people need to be nervous right now that they're not. I'm just saying, just read about it, start there, read some articles, find out about it.

Jim Carr: Educate yourself.

Jason Zenger: Educate yourself. We're going to have a guest on today that's going to help us to understand a little bit of the technology and just start to understand it, and see where it can be applied to your business soon. But I think very few manufacturing leaders are actually implementing artificial intelligence into their ships, but they need to at least start thinking about.

Jim Carr: There are a couple paragraphs that I want to highlight that says "Artificial intelligence provides the ability to automate tedious tasks and enables machines to learn, alert, improve, advise, and sometimes even make decisions. You were spot on with your defining. Manufacturing organizations are continuously looking for ways to increase productivity and operational efficiency looking to the new growing technology. The industrial Internet of Things, manufacturers are realizing that artificial intelligent technologies are becoming a fundamental enabler of IIOT".

Jason Zenger: I would say that the best way to think about this, like two great examples would be do you remember, oh my gosh, this must have been decades ago when IBM came up with their great super computer, and they were going to have the best chess player in the world this IBM computer. That would be a basic version of artificial intelligence. Or an even more advanced version could be the way that some of these new cars, like the Tesla cars, how the car can drive itself without you having to do it.

Jim Carr: Autonomous.

Jason Zenger: Yeah, like autonomous driving, that's artificial intelligence being-

Jim Carr: Now you talk about being scared.

Jason Zenger: ... equipped into the car in order to navigate through traffic. Well the Tesla doesn't scare me, it's the freight trucks. They're going to be driving autonomous eventually. That would scare me the most.

Jim Carr: I agree, I agree, and motorcycle.

Jason Zenger: Why don't we move on?

Jim Carr: Yeah, let's introduce our guest. He's really a dynamic guy.

Jason Zenger: I'd love to.

Jim Carr: I talked to him last week and I said, "Dude, this is going to be a great episode," because he's like me, he's got a lot of charisma, and he likes to talk, and he's super intelligent, and-

Jason Zenger: I don't know if he wants to be associated with you [crosstalk 00:12:29].

Jim Carr: You don't think so?

Jason Zenger: No.

Jim Carr: Oh, I think so. He's happy. He's happy he's here with us. You're going to introduce him, right, to the metalworking nation?

Jason Zenger: Well we have with us on the today Akshat Thirani. Akshat is the CEO and co-founder of Amper Technologies. He's also the recipient of Crain's Chicago Business 20 in their 20s, and the SMEs 30 under 30. From growing up in manufacturing with his dad who owns an automotive manufacturing company in India to his formal education with his bachelor's degree in computer science from Northwestern University, which is also my alma mater, to living in China and San Francisco. This man has traveled the world and he has started a company, and he is just coming into the manufacturing industry in a storm, and going to change things for the good there.

Jim Carr: Wow.

Jason Zenger: Akshat Thirani from Amper Technologies, welcome Akshat.

Akshat Thirani: Thanks for having me here.

Jim Carr: Hey, you're welcome. It's a pleasure to have you. I'm excited about the interview, and I look forward to equipping and inspiring the metalworking nation with the knowledge you have, and the product that you've developed, and how it is really bringing manufacturers better together to automate and run their shops more efficiently. I really think it's a great brand, and it's a great idea.

Akshat Thirani: Thank you for inviting me. I appreciate it.

Jim Carr: Yeah, no problem. Congratulations on the credentials, man. You're such a young guy and already the Crain Chicago Business 20 in their 20s and SMEs 30 under 30. I got to ask, did they approach you, did you apply or what? I know it's off, but I'm really interested to here how that all came about.

Akshat Thirani: In both these cases with Crain's and in SMEs Advanced Manufacturing magazine I was lucky enough to have been reached to. I had a couple of other media mentions, which I believe is how they came across me. But very lucky and honored to have been on both those lists.

Jim Carr: I bet. I bet it really helped elevate the PR and your business, would you think it would?

Akshat Thirani: I would say it did. It also internally helped me understand what our position might be with the company. Overall, it's been great. Got to meet a lot of new folks through that.

Jim Carr: Cool. In addition to that, you can tell the metalworking nation better than we can tell your story. When I talked to you last week on the phone I really thought it was a great story. Why don't you tell everybody that's listening to the show your manufacturing journey from growing up as a young man in India.

Akshat Thirani: Absolutely. Until college I lived in India and I've grown up over there. Pretty much the town that I lived in was centered around manufacturing. The whole economy there was driven by manufacturing, so all my friends in school, all the people that I knew were in some way or another related to production. I've been lucky enough to grow up in a family with four generations of manufacturing right from sand paper to auto components, to plastics, and so on. It's really been in my blood, seen it growing up, worked summers over there. Funnily enough, learned 5S when I was probably in-

Jim Carr: Oh you learned 5S?

Akshat Thirani: ... fifth grade from my bedroom on how do I clean it up.

Jim Carr: No kidding?

Akshat Thirani: Yeah.

Jason Zenger: It sounds like your dad and my dad were very similar in that way because I had to learn 5S. I didn't know I was learning at the time from my dad too, so I agree.

Akshat Thirani: Oh yeah, like what's the takt time in making eggs, all kinds of fun things.

Jason Zenger: India is a manufacturing economy, much like the United States there's a lot of computer science going on there, but there's also a ton of manufacturing going on there. When did you have that a-ha moment where you're like I've got a product that I can make, and it's going to tie both of those worlds together?

Akshat Thirani: Coming into college I started studying manufacturing and design engineering. My goal, long-term, was to run manufacturing operations and build products. I actually really started liking computer science a lot, but as I was graduating I saw that there's a massive difference in technology tools that typically software companies use and those that manufacturing companies use. And so-

Jason Zenger: Are you seeing a disparity between [crosstalk 00:16:43] they're more progressive, is that what you would say?

Akshat Thirani: Not even as much as the people are more progressive, but all of us in the room got to use iPhones that have really advanced capabilities, whereas, in a lot of shops, including my dads, you see paper reports and a lot of manual ways of operating. Maybe not the most modern tools, a lot of Excel and so on. That's where I was like okay, there's a big difference in the quality and how modern a lot of tools might be.

Jim Carr: That's when the light bulb went off in your head like there's this big disparity. Manufacturing is just lagging behind everybody else and the technologies that we use. We're using these highly sophisticated iPhones minute by minute every day, right?

Akshat Thirani: Yeah.

Jim Carr: But yet, manufacturers are still using Excel spreadsheets and paper in their businesses.

Akshat Thirani: Yeah, exactly. On the flip side, really complex operations running in manufacturing, especially in a high mix, low volume where you're coordinating all these different tasks, using really advanced machines to produce components. It just felt odd that for some reason, software technology in particular, to manage operations day to day hasn't advanced as much as a lot of the other things have.

Jason Zenger: Beyond the introduction of C&C, that period where C&C was introduced until about now, there wasn't a gigantic jump like we're going to see in the future, would you agree Jim?

Jim Carr: I would. That's the fourth industrial revolution [crosstalk 00:18:09].

Jason Zenger: That's why they call it a revolution.

Jim Carr: That's what they're saying is what really is it going to be. It could be robotic [crosstalk 00:18:17].

Jason Zenger: Artificial intelligence, data, all that kind of thing. It's happening.

Jim Carr: It's happening.

Jason Zenger: Metalworking Nation, get on board, do your research.

Jim Carr: There is a shift that is definitely happening, there's no question about it.

Akshat Thirani: Here's the funny thing, I started looking into all right, how do I collect this information from these machines. I've studied computer science. I know how to program and yet, it was really challenging. It's not a trivial thing to connect up a machine and start producing data, especially when you have all these different machines types out there. Some of them are old, some of them are new.

Jim Carr: You mean like C&C machines like you might have on 1998 Fidel vertical machining center, versus a brand new 2019 Okuma or Mazak or whatever?

Akshat Thirani: Exactly. The total effort that goes into the idea that I want to collect some information, just some basic things, are my machines running in auto, whatever that might be, to actually getting that, is a lot of work. That was really frustrating. I was like what is the simplest way to collect information from a machine? Basically, through a lot of iterations we arrived at every machine has a heartbeat of electricity. Almost every machine in the world uses electricity in some way or another. That is the a-ha moment, which was every machine has a pulse that we can tap into and capture the most important things that really matter.

Jason Zenger: When you talk about a heartbeat are you talking about because machines run on alternating current, is that what you're referring to?

Akshat Thirani: Yeah, as every part is made it creates a signature and maybe it's a cycle time of a minute or maybe it's an hour, whatever that might be. But anytime parts are made there's a draw in electricity and that tells that some action is happening.

Jason Zenger: Before we get into the product end of it, I want to know more about you grew up in India and then you moved into the states when you were how old Akshat?

Akshat Thirani: I was 17 when is started college.

Jason Zenger: You're 17 when you started college and you started college where?

Akshat Thirani: At Northwestern University, which is right outside Chicago.

Jason Zenger: Gotcha. You did your four year degree there and then you moved on to China, or San Francisco, or am I mixing those up?

Akshat Thirani: First in Shenzhen, China, for about three months and then San Francisco.

Jason Zenger: What did you do in both those locations?

Akshat Thirani: My senior year, spring quarter and I'm like all right, I'm going to start this company, I'm going all in, and had the chance to join a program, a three month long accelerator. Essentially got to live in Shenzhen for a little bit, see what it's like to create electronics. That's where a lot of the electronics of the world are produced. It was really fascinating. We were developing a hardware and software product. It was really interesting learning about how do you launch a hardware internet connected hardware product. Really neat program, it's back by a U.S. venture capital firm and there's over 60 companies working out of that 1 space from all over the world, so I had a really exciting time?

Jim Carr: Were you there by yourself?

Akshat Thirani: I was with my two co-founder.

Jim Carr: Oh, wow, wow.

Jason Zenger: Now, as a part of being in this program did you get venture capital that was invested into Amper in order to get started?

Akshat Thirani: Yeah. Right out of the gate, as part of the program, they made an investment in us. That was really exciting. And then-

Jason Zenger: That validates you.

Akshat Thirani: Yeah. You're a senior in college, and you get this investment, it's super exciting and really no reason not to do it. After the program decided to join another program in San Francisco, which was really beneficial for me personally because it was more focused around starting up a business, not just how do you create a product. Learned a lot around managing a company, getting sales started, operations and so on.

Jason Zenger: Here in Chicago there is, for lack of a better word, a hub of making physical products. Have you ever gotten involved with mHUB?

Akshat Thirani: Yeah. After a year of travel between living in Shenzhen and San Francisco, we decided to grow our company. We really wanted to be in the Midwest in Chicago, it's like the perfect blend of talent and manufacturing, and technology, and so on. Decided to relocate, move back here, and we actually started working out of mHUB, which is-

Jason Zenger: Oh you did start working out of mHUB?

Akshat Thirani: Yeah. We were actually based over there for close to a year before going into our own space. mHUB is more of a co-working space with a lot of shared equipment. It helped us get our initial prototypes and versions out of the door, but as we've been growing, we got our own space and it's been really exciting.

Jason Zenger: Is it on the share drive, is it on the Google drive, is it on the Dropbox, is it on the E drive, the C drive? Makes me nuts.

Jim Carr: You have no idea. I'm telling you Jason, before we converted to ProShop ERP, we had things everywhere. It was in Word, it was in Google, it was on that drive, it was on the other drive. Right now, since we converted to ProShop ERP, everything is in ProShop. It's our one source for all information.

Jason Zenger: That takes the pain away.

Jim Carr: It certainly does.

Jason Zenger: Go to proshoperp.com for more information. Bam.

Jason Zenger: Now, what exactly does your product do and why should a manufacturing company have a light bulb moment and say, "I need to implement something like this?"

Akshat Thirani: To get the context of what we're trying to solve is around focus. Every company has limited resources and to really identify what is the most important thing to work on, you need to have data and facts to back up what is the 80/20 that drives-

Jason Zenger: Yeah, making your decisions.

Akshat Thirani: Yeah, so that's really the ultimate goal, which is to empower people on the floor and in manufacturing companies, to really make better decisions and be more focused. In terms of the way the product works is essentially it's a real-time tool that tells what's happening on the shop floor.

Jason Zenger: Going back to that heartbeat.

Akshat Thirani: Exactly. It tells you about how your machines are performing, about your efficiencies, what are the leading root causes to downtime, to job costing, and so on. It's a tool that helps identify what's happening on the floor and reports this is in a really modern, simple way.

Jim Carr: Let's break that down a little bit. When you first started installing this efficiency tool or automation, you were obviously doing it probably pro bono just to see how it was going at the beginning [crosstalk 00:24:45] because you had no data to back it up, you had no idea what it was going to ... What did you learn, what were you like, "Oh my God, this is awesome. This is going to be big"? Tell me how you evolved the product brand because you had this product in your head. You said this is where I'm going to go with it. Then you started to develop it, then you actually put it in a real-time shop and started using it. What was the initial response that you learned from that?

Akshat Thirani: There were several key moments in the lifetime of the business. One of them was about the technology itself, BLC integration, or connecting of the controllers of the machines is really hard. As you mentioned, we have the chance to deploy this for free for a customer and saw that it actually worked-

Jason Zenger: As well as you thought it was going to or better than?

Akshat Thirani: Better. In a way, it was really intriguing because we had a hypothesis that when parts are made on a machine they produce electrical signals, and that makes sense because a spindle is working harder as it's making parts. That is the hypothesis behind this idea-

Jim Carr: So simple hypothesis, right?

Jason Zenger: Jim, are you familiar with the whole notion of a hypothesis?

Jim Carr: Yeah, I am [crosstalk 00:25:58].

Jason Zenger: I'm not being condescending, I'm just asking.

Jim Carr: No, that's fine. It's fine.

Jason Zenger: It's like you have a thought and you're like I think this will happen, and then [crosstalk 00:26:05].

Jim Carr: Got it Jason.

Jason Zenger: Let's test it.

Jim Carr: I could Google that in two seconds. But yes, thank you Mr. Zenger for helping out there. I'm really intrigued by what Akshat has developed. Tell me, when you put this on the machine tool, it's like you're a week, a month, two months, three months in and you're like, "Oh my gosh." You go to your partners, you're like, "I had no idea we're going to be getting this kind of result, this data." Every night you must have been laying in bed and think, "This is going to be huge".

Akshat Thirani: Yeah. First of all, the reason we were able to do this was because several really forward thinking manufacturers that allowed us to work with them in the early stages. But yeah, it's like you looked at raw data and you could suddenly see all these patterns that really made it look very clear that parts are being made, that cycles are happening on a machine, and really neat things that you could see just by analyzing that is a moment where we like okay, we have the ability to actually launch this product. On the flip side, as we were talking to these folks and walking around the shop floors, we kept seeing people write down my machine was down from 8:03 to 8:50-

Jim Carr: On a piece of paper.

Akshat Thirani: On a piece of paper and key that into Excel and then key that into their ERP system. Man, I would say-

Jim Carr: I bet it just drove you nuts. You probably went through the ceiling.

Akshat Thirani: Yeah, I was like, "This is insane". You have some really skilled people that are wasting a lot of their precious time and then what is worse off was I would see these stacks of paper lying around and to me, that was no one's really looking at it. Those are two things that I noticed that made me believe that there is value behind this in saving time and adding time back to everyone's day. Secondly, showing what you can do with that sort of information. It was all happening on the shop floor, that's where the company was being born, in a way.

Jim Carr: What year was that?

Akshat Thirani: That was mid-2017.

Jim Carr: Mid-2017.

Jason Zenger: Going back to what the product does, you're essentially capturing the heartbeat of the machine, though for somebody say that's the CEO of a manufacturing company, what information of that are they going to get when their shop floor connects this device to their machines? Simplified data, you didn't want to spend a lot of time seeing all the heartbeats, he just wants to know, boom, these are the three things that I need to pay attention to [crosstalk 00:28:29].

Jim Carr: I want to know as a machine shop owner are the spindles running, are we keeping the spindles running, and am I making money. Really because that's all that the leader, the CEO, the owner of the company wants to know. They want just real time, simple data.

Akshat Thirani: Exactly. I think you got it exactly right, which is fundamentally it starts telling you what machines are running, what is the utilization like, what is your downtime really like. You can start identifying which machines are running the most, running the least. More importantly, for ones that aren't running a lot, you can understand what are the reasons your machines were down. Was it because of setup? Was it because you [crosstalk 00:29:09] didn't have an operator available, or you didn't have a job scheduled for it. Whatever that might be, so-

Jim Carr: It's only tracking if it's under power, is that right?

Akshat Thirani: Correct, yeah.

Jim Carr: We've mentioned this a couple times on MakingChips, about a six hour round table industry 4.0 at the [inaudible 00:29:26] headquarters a year ago-

Jason Zenger: We did-

Jim Carr: ... or so ago. One of the statements that was made was if you are not implementing some kind of data collection and utilization [crosstalk 00:29:37].

Jason Zenger: ... in the next five years-

Jim Carr: ... in the next five years-

Jason Zenger: ... you're going to go out of business.

Jim Carr: You're going to go bye-bye. It's kind of like that [crosstalk 00:29:43].

Jason Zenger: I was really offended by that.

Jim Carr: It's like that old sentiment that if you don't get an old C&C machine and replace that, this is what I thought of, and replace that bridgeport or that lathe, you're going to go out of business too. To a certain extent, that has come true. It probably takes a little bit longer than five years, but I would say that those factors you brought up are probably the simplest things to collect.

Jason Zenger: They made the statement and I asked the question, well is this really complex, do I need to collect 20 pieces of data or can I just collect one. Everybody on the panel was like, "Just collect one or two pieces of data. Don't make it complex." In the piece of data they talked about, the uptime and everything, the utilization, those are the pieces of data that said collect that first and start analyzing it.

Akshat Thirani: Manufacturing, at its core, is about simplicity and practicality. The moment I start a lot of terms like IOT, industrial 4.0, personally, I don't really understand what that means and that makes me, as someone in this industry, really skeptical of what I'm being sold or told I should do. Until I can fully understand the facts, I'm pretty skeptical. That's why, in fact, if you go to our website, you won't see the word IOT, industry 4.0, mentioned because I don't understand what it means and so-

Jim Carr: Yeah [crosstalk 00:30:56]. I love that. You're being authentic. You know what you're doing? You're connecting two that shop floor manufacturer because a lot of shop floor manufacturers, like myself, really don't understand what all these acronyms-

Jason Zenger: I thought you liked buzzwords.

Jim Carr: Well I like buzzwords, but I don't like acronyms because it confuses me and I don't really know what it means and I got to look it up. It's just a lot of stuff.

Jason Zenger: Coming out soon the MakingChips Guide to Acronyms.

Jim Carr: Yes.

Jason Zenger: You're on that right? That's one of your rocks for the next quarter, right?

Jason Zenger: What I like that you've done, Akshat, is you've created a product that's going to be really simple for the CEO, the top level guy, that's going to be taking this data, that is extracting from the machines and it's going to be put into an easy format for them to digest and make changes.

Akshat Thirani: Literally in just a quick spiel, you clip the sensor around the power cable. From that, it starts reading the electrical signals and it's transmitted over the cell network, so it's not crazy IT integration and ERP integration.

Jason Zenger: You don't even need to hook it up to Wi-Fi.

Akshat Thirani: No. You just clip it on, it starts transmitting. Now-

Jim Carr: Via Bluetooth?

Akshat Thirani: Cellular data.

Jim Carr: Oh cellular data.

Akshat Thirani: Yeah.

Jim Carr: Oh interesting.

Akshat Thirani: On your phone you start getting real time data telling you about your utilization, your downtime codes, it tells you when your machines need maintenance based on actual run times, not just every [inaudible 00:32:24].

Jim Carr: That's probably more of that artificial intelligence that's telling you those things, right?

Jason Zenger: No, I don't think so.

Akshat Thirani: It's more so on true hours.

Jason Zenger: Right. [crosstalk 00:32:32].

Jim Carr: The machine's programming the hours into it, okay.

Akshat Thirani: The technology leap is that the system just works across any kind of machine type. The kind of parts you make in a shop, Jim, look very different then any other shop because there's a million types of components in the world. It's their infinite electrical signals being produced. The leap in technology that we've developed is that we can look across any kind of machine and it learns the patterns as it goes long and produces that real time data. That's where the innovation is in the product.

Jim Carr: When you hook up this to a Haus, or a Fidel, or a Mazak, or a Nokuma, is there a learning period? Is it like a one week, two months, one year?

Jason Zenger: It's usually like-

Jim Carr: What is it?

Jason Zenger: Within a week.

Jim Carr: Within a week this adaptor, this ancillary tool that we're collecting data from is learned how the machine is running.

Jason Zenger: Exactly.

Jim Carr: It's watching and collecting, and analyzing, and within one week you can discern how the machine is operating.

Jason Zenger: Exactly.

Jim Carr: Okay, very interesting.

Jason Zenger: How do you take the amps and collecting the simple information into so many other pieces of information for the machine?

Akshat Thirani: It's really interesting because it's a lot of signal processing. On a very simple level, it's like a heartbeat every time a part is made.

Jim Carr: [inaudible 00:33:59] assembly, yeah.

Akshat Thirani: Just imagine a cycle on a Swiss machine, it's made a part and it creates an electrical signal that just keeps repeating every single time that same part is made.

Jim Carr: The spindle turns on it goes 20,000 RPM, there's going to be a lot of ample-

Jason Zenger: That has a different kind of code as to something else.

Akshat Thirani: Exactly.

Jason Zenger: When you engage into a cut that probably has a different code as well.

Akshat Thirani: Exactly. That's how it's working, but at the end of the day, that's just a means to an end. What you actually end up getting at its most fundamental level is Pareto charts that tells you which machines have the most downtime and why so that you can start targeting the top areas that lead to downtime and what you mentioned earlier on capacity, what's really going to unlock more capacity for you. Now you could focus on what those reasons are and not on things that may seem like symptoms but aren't really the major contributors to downtime.

Akshat Thirani: This is exciting for me which is to empower people on the floor to make decisions. For example, you can have your operators know what's happening, so you don't need to micromanage anyone and they can make their own decisions. Let's say the run an unattended run, they can have an alert that if it's down for five minutes, I want to get a text message and it's immediately fired out to them.

Jim Carr: Very cool.

Akshat Thirani: They can make their own decisions rather than you having to walk around or have someone else do that.

Jim Carr: Akshat, how granular does the data get? In regard to amps, I'm not an electrician but how do the algorithms know that if the machine tool amps increase 1, 100th that something has changed? How do you identify and isolate that metric?

Akshat Thirani: It comes out down to-

Jim Carr: Tough, question right?

Akshat Thirani: It's definitely on the more technical end of how does it interpret these signals and there's a lot of science that goes behind it, a lot of algorithms.

Jim Carr: No, be honest, yeah.

Akshat Thirani: Essentially, we've collected 100s and 100s of machine's data and build these models based on that massive data set and done training on that. I'm not the expert on how to develop these algorithms, but essentially it's by looking at a lot of signals and developing these models.

Jim Carr: Akshat, what does your future look like and what is the vision for Amper?

Akshat Thirani: Our goal is to essentially build really simple and practical tools for manufacturers. When I walk into a shop floor there's just a million problems that can be solved. Our goal it to stay true to our pieces, which is make it simple and really practical in the way that people use products by making a consumer product like tool for manufacturers. There's so many problems around quality control, around training people up, around tool [crosstalk 00:36:46] cutting tools. We have a pretty extensive product roadmap when it comes to tools from manufacturers, we call it a factory operating system or factory OS. That's our roadmap and we're really excited, we have a really interesting team right across from hardware, software, manufacturing expertise.

Jim Carr: You're in West Town in Chicago very near to mHUB, right?

Akshat Thirani: Correct, yeah.

Jason Zenger: We've talked a lot about what the manufacturing leaders out there need to do in the future, what advice would give to the Metalworking Nation out there about what they should be thinking about as it relates to IOT and data collection, and data utilization?

Akshat Thirani: My advise would be to first understand what the goal is, which is to ship good parts on time at the coded cost and to look at technology tools that really help achieve that, and help people on the floor. As I mentioned, I'm somewhat skeptical of a lot of terms like IOT, industry 4.0, being thrown around, so I would really drill into to get that goal what kind of metrics do you need for your team and to focus on that.

Akshat Thirani: The second would be often the cost of taking on these projects is a lot more, like IT resources, PLC upgrades, integration, so factoring in the lifetime cost of such a product.

Akshat Thirani: Finally, talking to the people on the floor because ultimately, those are the folks that are going to use it the most, so really understanding what is it that will unlock their time or their potential as a leading indicator.

Jim Carr: Well Akshat, what a pleasure to meet you today. Thank you so much for showing up at the Fusion event. I know you're partnering with Craig on this in some capacity. It's been an absolute pleasure to learn how you develop the product and you've had such great success at such a young age. I'm very proud of you and I wish you the best of luck, I genuinely do.

Jason Zenger: Absolutely Akshat, and if the Metalworking Nation out there can hear maybe the machines buzzing or the applause going on, as soon as we're done here Akshat, we're going to go watch your presentation which is going to be on Maker Machines Ruthlessly Efficient, so you're going to make that presentation. Jim and I are going to go watch you and we're going to learn even more than what we just learned now.

Jim Carr: You bet. Thank you so much.

Jason Zenger: Thank you so much.

Akshat Thirani: Thank you so much.

Jason Zenger: Jim, are you ready [crosstalk 00:38:59] are you ready to put it in?

Jim Carr: I want to be just like Akshat when I grow up, I really do. He's a smart guy.

Jason Zenger: I think you're already grown.

Jim Carr: Yeah, I know, I know, but I love millennials in this industry. I think they're bringing a bright light into our industry.

Jason Zenger: A different perspective.

Jim Carr: A different perspective [crosstalk 00:39:14].

Jason Zenger: Bringing the iPhone to the see and see machine.

Jim Carr: Yeah. If the Metalworking Nation would like to reach out to Akshat I'm sure he wouldn't mind linking up or connecting on LinkedIn. You spell his name A-K-S-H-A-T, last name is spelled T-H-I-R-A-N-I. You can go to his website, it's amper.xyz.

Jason Zenger: Yeah, cool website.

Jim Carr: It's not a .com, it's amper.-

Jason Zenger: Amper.xyz.

Jim Carr: ... xyz. That's easy to remember.

Jim Carr: If you liked this episode please help to equip and inspire other manufacturing leaders by leveraging a kind review on Apple iTunes about this show. Leave your positive ratings, it really helps us. It make Jason smile. It makes me smile even wider. It's always a pleasure to equip and inspire you. If you have any questions about the show give us a shout at info@makingchips.com and don't forget to subscribe to our weekly Boring Bar newsletter. Text chips to 38470. Jason?

Jason Zenger: At the end of the day, if you're not collecting data-

Jim Carr: You're not making money. [crosstalk 00:40:17].

Speaker 4: Metalworking Nation, listen up, manufacturing is challenging. You need to think differently. The day to day whirlwind of urgencies, the pressure to grow, customer demands, workforce development, new machine tools and robots, the list goes on and one. It is possible to stay ahead of the game with manufacturing because you can't do it alone. We're here to give you access to exclusive content from other leaders, as well as videos, blogs, show notes and more resource that are designed to equip and inspire you on making chips.

Jim Carr: It's impeccable that we change.

Jason Zenger: No, it's imperative.

Jim Carr: It's imperative that we do change.

Jason Zenger: You just really [crosstalk 00:41:07].

Jim Carr: I know, I shouldn't have done that shot.

Jason Zenger: Start one more time.

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