• Benjamin Moses

AMT Tech Trends: From Scratch

Updated: Apr 14

Release date: 13 March 2020


Ben and Steve tip their hats to International Women’s Day! Steve talks about some cobot programs run on the testbed. Ben brings up how AI and ML can businesses from the enterprise side of things. Steve found a hobbyist CNC buying guide! Ben speaks on behalf of NISTs research regarding the economics of additive. Lastly, Steve geeks out about motorcycle metrology and then some.

Benjamin’s Linked In www.linkedin.com/in/benjamin-moses-b13b44a2/ Amateur Machinist Blog swarfysteve.blogspot.com/ Music provided by www.freestockmusic.com



Transcript:


Benjamin Moses: Hello everybody, and welcome to the Tech Trance Podcast. I am Benjamin Moses, the Director of Manufacturing Technology. And I'm here with ...


Stephen LaMarca: Stephen LaMarca, the Manufacturing Technology Analyst.


Benjamin Moses: Hey, Steve. Ready to discuss the latest manufacturing technology research and news?


Stephen LaMarca: Always, man. I can't shut up about it.


Benjamin Moses: Awesome. We've had a pretty great month going on.


Stephen LaMarca: We really have.


Benjamin Moses: Yeah. I'm excited for ... What year are we? 2020. The future?


Stephen LaMarca: 2020.


Benjamin Moses: We're living in the future. I don't have too much to talk about in terms of home automation, except my robot vacuum cleaners keep getting stuck. Part of it ... I mean, it is my fault. What are the robot cleaners going to do? I just haven't solved the problem yet. It just gets stuck on the rug and some places I need to fix.


Stephen LaMarca: Right. They don't have off-road tires, man. You can't help that.


Benjamin Moses: No, no. You'd be surprised, they're pretty robust.


Stephen LaMarca: Really?


Benjamin Moses: I mean, there's always the meme of "I left my front door open, I'll never see my robot again. It's gone to the wilderness."


Stephen LaMarca: Has that actually happened to people?


Benjamin Moses: I'm sure it has.


Stephen LaMarca: That's actually a genius meme.


Benjamin Moses: Why would you leave your front door open? Maybe through the cat door or something, or dog door.


Stephen LaMarca: Yeah.


Benjamin Moses: But yeah. For today, I wanted to talk about International Women's Day. We missed Women's Day due to recordings, so we just overlapped with the day and I want to talk about an interview I saw from Women and Manufacturing. They interviewed Missy Miller, and she had some pretty good takeaways about career development. I just wanted to mention some of the takeaways that I've noticed, and they're pretty solid.


Benjamin Moses: So, one, she's currently the regional operations' director for Atlas Molded Products. She has a couple of good takeaways. One is if you feel like you're underutilized, just step up and do something about it. She made the point of ... during this presentation to some of the executives and senior management, and from there, that kind of propelled her into her new role.


Stephen LaMarca: So she utilized herself.


Benjamin Moses: Yeah, exactly.


Stephen LaMarca: She felt under utilized, she utilized herself, and then later, come a review or something, she was like "Look at all this that I did without you telling me to do it and we're in a better spot because of it."


Benjamin Moses: Exactly. I made this happen. Yeah.


Stephen LaMarca: Awesome. That makes sense.


Benjamin Moses: And then the second ... The other thing was about mentors. Mentors is a big buzz word everyone. Not buzz word, it's an actual term. It's an actual thing that exists. But in terms of applying it to everyday life, there's still a struggle of how to find a mentor, how to find a mentee. So the actual number of people that are involved in that kind of relationship is really, really low. Compared that everyone that talks about it. Everyone says you should have a mentor, which I don't agree with because I've never had a true mentor that I would say is, yeah, that's the one that trained me.


Stephen LaMarca: Yeah.


Benjamin Moses: I have had a bunch of managers that did good observation in terms of defining a couple things I should work on, but someone that I can say is a mentor? Probably not.


Stephen LaMarca: Yeah. I agree, because I feel like a lot of people would probably want to be lured into seeing somebody as a mentor that is really just a good friend, and to some degree a good leader as well. But you don't always want a mentor to be your best friend. At the same time, that's actually ... I'm backpedaling a little bit, because your best friends can tell you the hard truths.


Benjamin Moses: Yeah maybe.


Stephen LaMarca: Sometimes your best friend needs to break you down.


Benjamin Moses: Depending on your best friend. They could be enablers, they could be good habits.


Stephen LaMarca: Oh my God. Yeah, you don't want an enabler. It's tough.


Benjamin Moses: In my current role, I do see myself as a mentor for other people, or a developer, or a coach. But she makes a really good observation. If you don't have someone that you can say is a mentor, just look around you. She uses her peer group and managers to identify ... help her identify problems in areas of opportunities. She does the same thing as with the first thing. She solves those problems. Just looks around and says, I'm in a slower boat, I don't have a mentor, but there are other ways I can learn, other ways I can improve. Just look at my peer group and let's look at the managers that are willing to spend time with me, and went about and solved that problem.


Benjamin Moses: Then one thing that I do find useful is the concept of observational learning. If you don't have someone that says these are things that you should learn, just look around you and observe people. What are they doing well and why are they going it? Just copy what they do. Nothing wrong with that. So just something to think about. The big takeaway from Missy is solve your damn problems.


Stephen LaMarca: Solve your problems. Wow. I wonder when robots are going to solve your own problems and when they're going to see humans as mentors, and when robots are going to see other robots as mentors. Okay, this is too far.


Benjamin Moses: That's too much meta.


Stephen LaMarca: Yeah, okay. We're nowhere near that so we don't need to worry about any of that yet.


Benjamin Moses: Nowhere near that. So the link to her interview will be posted in the show notes. I recommend checking that out.


Stephen LaMarca: That's awesome.


Benjamin Moses: What's going on in the test bed, man?


Stephen LaMarca: There's a lot that's been going on in the test bed. Seemingly, this year is flying by. So let's talk about it. Charob has coded two amazing program for our robot arm. He refuses to use the cobots HMI software, which I think is X Arm Studio.


Benjamin Moses: Sure.


Stephen LaMarca: I've been using that. I've been having a great time with it just fiddling with the settings, just learning the robot, learning the software, feeling it out, just being safe with it.


Benjamin Moses: Charob doesn't want anything to do with that.


Stephen LaMarca: Charob is just like, I've worked with robots in the past, I want nothing to do with that software. I'm using command lines.


Benjamin Moses: He wants to be in the matrix.


Stephen LaMarca: Yes, so much dark screen with green text. That's exactly what he's doing. So he wrote some great programs, and the first one which I published last week ... no, the week before last week. His first program, he used command lines to engage the cobots teach mode.


Benjamin Moses: Oh, okay.


Stephen LaMarca: So he engaged it using his code, or using codes. Then physically grabbed the robot arm, moved it to one location, then moved it to another location, had it do something, and then it stopped on the recording, and then sent it home and wrote that all in one long program code.


Benjamin Moses: Cool.


Stephen LaMarca: With doing that, he essentially controlled or commanded the robot to

throw away a soda can into the trashcan.


Benjamin Moses: That's awesome.


Stephen LaMarca: Just take it from you, go around to the other side of the table and drop it clean into a trashcan.


Benjamin Moses: That's cool.


Stephen LaMarca: It was really fresh, but a great move and motion. But because it was manually articulated by him, and I'm thinking the teach sensitivity on the arm wasn't high enough. So by turning up the teach sensitivity on the robot arm, when you go into manual mode, that basically dictates how easy it is to move the arm.


Benjamin Moses: Oh, okay.


Stephen LaMarca: So you can give it a gentle push to move it wherever you want it to go if the sensitivity is high. Or if you turn down the teach sensitivity, you've really got to shove it into place.


Benjamin Moses: Right.


Stephen LaMarca: So I don't think the sensitivity was high enough, and because of that you can see the arm actually shake where Charob is struggling to move it into position. So it looks really sketchy, but the code is not flawed and it works. So when I explained that to him, he was just like well I'm just not going to do the manual movement anymore. I'm going to redo this code. So this week or last week, I published his most recent code which was just, forget manual articulation manipulation of the arm. He just sent it to coordinates. He just used coordinates.


Benjamin Moses: Sure, right.


Stephen LaMarca: The product of that program is a much more fluid smoother movement.


Benjamin Moses: Sure.


Stephen LaMarca: If you go to my blog, you will see that most recent code. The code is actually published on the blog. In that same update, I posted a YouTube video of the actual program running.


Benjamin Moses: That's a good point. One thing that I was thinking about as you go through that is, if you're teaching the robot through positioning it manually, if that doesn't work out well, you can always get readouts. So you move it to the position you want, determine where that position is, and then come back and use that position location that it tells you in the readout to reprogram the robot using the HMI or code.


Stephen LaMarca: Yeah.


Benjamin Moses: So that's another kind of work around it. But that's cool. It sounds like it worked well.


Stephen LaMarca: In his code ... So I published the code because it's really clean. Then he has comments in there showing it's like-


Benjamin Moses: It seems straightforward, doesn't it?


Stephen LaMarca: Yeah, it seems so straightforward because he's so good at writing code. He throws in comments that tells you exactly what each digit means. You can see the coordinates he's moving to or he's moving the arm to. It's just really clean and well done.


Benjamin Moses: That reminds me of when I first started doing some programming on the single board computer. Some of these are pies, but they had protons or something that was released a bunch of years ago.


Stephen LaMarca: Right. The photon?


Benjamin Moses: Photon.


Stephen LaMarca: The spark photon?


Benjamin Moses: The spark, yeah.


Stephen LaMarca: Those things are cool.


Benjamin Moses: So I tried the program and I followed the instructions, which is two or three lines of code. I never could get it to work. It seems so simple when I'm looking at it on the instructions, and I think Charobs is very similar. I'm looking at it. I could do this. When I actually try to do it, nothing works.


Stephen LaMarca: Yeah. I feel your pain.


Benjamin Moses: It's just me. I have bad luck.


Stephen LaMarca: I feel your pain. In college, we did a little bit of coding studying physics and my lab partner that I worked with was great at just generating code himself, writing lines. I could never do it because it's just ... It takes a certain degree of creativity.


Benjamin Moses: Sure.


Stephen LaMarca: To generate that stuff. What I was good at in college was editing his code. If he had a problem, if he ran into something, it was really easy for me to clean it up and fix it. Then I could bring his 100 line code down to like 20. I was good at that, but I could not generate it from scratch the way he could.


Benjamin Moses: What else we got going on?


Stephen LaMarca: Next thing this week, I have been experimenting with using the HMI for the cobot to control the arm to actually open and close the pocket NC enclosure, and I've been successful at safely opening and closing the enclosure to the pocket NC.


Benjamin Moses: This is without the end of arm two line?


Stephen LaMarca: Correct, this just with the stump.


Benjamin Moses: Okay.


Stephen LaMarca: Just nudging it with a stump, making sure no collisions. Everything is happy. Collision detection is on. So, if it noticed a ... If it sends a pressure that was a little too high, it would have thrown me a code.


Benjamin Moses: Well, it's misleading because there is a collision because you're hitting the-


Stephen LaMarca: It's a controlled collision in this case.


Benjamin Moses: But their hinges are fairly lubricated well.


Stephen LaMarca: Right.


Benjamin Moses: So it's not much friction.


Stephen LaMarca: The hinges are smooth, and also it goes back to a previous test bed update on experimenting with collision detection.


Benjamin Moses: Yeah.


Stephen LaMarca: If you have a certain degree of ... We're at the Goldilocks collision detection sensitivity.


Benjamin Moses: Awesome.


Stephen LaMarca: So it will detect something that doesn't fell right. So if you grab onto the enclosure yourself and you pull it up to open the enclosure, you can feel how it's supposed to open.


Benjamin Moses: Sure.


Stephen LaMarca: You know not to push forward or push back. No, you just go straight up. As it's opening upwards, then you push it rearward. If you have the collision protection on the arm set just right, the robot will know when it's applying pressure or movement, or force in a direction it shouldn't be.


Benjamin Moses: Oh, gotcha.


Stephen LaMarca: So we've got that collision detection sensitivity dialed in perfectly.


Benjamin Moses: Cool.


Stephen LaMarca: I just need to record points and actually make it a program to open and close it. But other than that, once I figure that out by reading instructions, we'll get that and that will go up this week.


Benjamin Moses: Good luck.


Stephen LaMarca: Another thing that was really fun, Charob and I have been working with IT. So Jesse, the director of IT here at AMT, and his minion Sean. I always say his minion, not to be insulting, but because I forget his title. He actually just got a title change.


Benjamin Moses: Good for Sean.


Stephen LaMarca: Yeah, we're proud of him. He's really stepped up with networking and the test bed has its own secluded network.


Benjamin Moses: Nice.


Stephen LaMarca: Because we don't want to ... There's a lot of other people here at AMT that do a lot of work on a daily basis and, if we crash a network and they can't update anything on the server, then we're really SOL and I'm going to get a stern talking to.


Benjamin Moses: That sounds like something Russ did about four years ago.


Stephen LaMarca: Fortunately he just did it on the mobile network.


Benjamin Moses: True.


Stephen LaMarca: So it wasn't downing computers. It was just nobody's cellphone worked on the-


Benjamin Moses: On the wifi.


Stephen LaMarca: Yeah, wifi. But yes, Russ did do that with, not a raspberry pie. He did it with an enclosure, if you will, network switch because he needed to use a router or something like that.


Benjamin Moses: Right.


Stephen LaMarca: So they're working on the network and we're getting everything squared away so that we can just ... instead of me going over to the test bed or Charob going over to the test bed and plugging in an ethernet cable to our computer, or if I want to use the pocket NC, I plug in a USB cable to my computer. We just want to, from our desks, be able to log into the test bed wirelessly, but everything in the test bed is wired together to a sonic wall.


Benjamin Moses: Sure.


Stephen LaMarca: So it's protected, it's stable. We've got good cyber security, cyber physical security. So everything is safe over there, but we have ease of use to not have to play with cables all the time.


Benjamin Moses: Awesome.


Stephen LaMarca: So IT is helping us out greatly with that, and they mentioned that you guys have a lot of little devices. There's only three devices on the test bed, but there's a lot of boxes down below. They know what they are, but they're just pointing it out. Well we do have a raspberry pie for every device on the test bed, and the raspberry pie is our MT connect agent.


Benjamin Moses: Oh sure.


Stephen LaMarca: It's running our MT connect agent, the adapters code that is written and installed on the devices themselves. But the agent has to be run separately. It doesn't have to be, but it is run separately in our case on raspberry pies to monitor and stream all that data coming from the machines.


Benjamin Moses: Yep.


Stephen LaMarca: We've got three raspberry pies just lying around.


Benjamin Moses: Just hanging around.


Stephen LaMarca: Raspberry pie doesn't have an enclosure from the factory, so we've got these open circuit boards just chilling underneath the test bed actually. So I went ahead and bought this cluster enclosure and put all the raspberry pies together in a neat little stack. It is now the most adorable server, network server you've ever seen.


Benjamin Moses: We should definitely call that our data server.


Stephen LaMarca: Yeah.


Benjamin Moses: Agent server.


Stephen LaMarca: I walked over to IT when I assembled it and I was like, behold the most adorable server you've ever seen in your life. Then this is running MT connect.


Benjamin Moses: It's a pack of about four playing cards high?


Stephen LaMarca: Yeah, exactly. Four playing card stacks or sets high.


Benjamin Moses: That's awesome.


Stephen LaMarca: Doug was over there at the time. He's like, wow that's cool, you should really put that on the blog so that we've got more content. So yeah, I'll post pictures of that so everybody can see that.


Benjamin Moses: It's interesting how much IT infrastructure is required for manufacturing equipment.


Stephen LaMarca: Oh yeah.


Benjamin Moses: Just the quality of life being able to remotely access the equipment from here. The infrastructure required is surprisingly high. I've done some home network so I'm fairly familiar with all the stuff there.


Stephen LaMarca: I'm sure.


Benjamin Moses: But you wouldn't really think about it. So if I wanted to buy a piece of equipment, I wouldn't think of the several hundred dollars extra required for switches. You just bought a bunch of power strips and a bunch of USB power adapters for the pies and the pies themselves.


Stephen LaMarca: Yeah.


Benjamin Moses: So it adds up fairly quickly. More industrial grade equipment is a little different, but there are [inaudible 00:16:57] hardware that you really don't think about that's required to support.


Stephen LaMarca: But one of the reasons why we have the test bed is so we go through all this, because if we are experiencing it, people in the factories actually producing stuff are going to experience this when they implement stuff. I like to tell people, full disclosure, we have published a white paper in the past on how easy it is to dive into developing your own test bed for research and development and it doesn't cost a lot, but man it's a lot easier if you have an IT department.


Benjamin Moses: Good point. Good point.


Stephen LaMarca: So as much as I like to hype up having a test bed, have an IT department first. I'm sure there's some brains that can totally do that by themselves though.


Benjamin Moses: The article I wanted to get into ... Is it okay if I get into the next one?


Stephen LaMarca: Yeah, go for it man.


Benjamin Moses: This article is from Sloan Review from MIT. It talked about artificial intelligence and machine learning, more towards the business side. So the past bunch of episodes we've been talking about specifically manufacturing applications for artificial intelligence and machine learning. This one I want to stray a little bit away from the pure manufacturing side of it and look at manufacturing is really just a business. So you've got all these other processes, all this other overhead that's required to accept POs, generate new business, HR department. All that stuff exists to run a business. You just happen to be a manufacturing company, so your specialization is producing parts.


Stephen LaMarca: A business thrives on financial transactions and business either makes profit by either selling a good or service, and we're just in the manufacturing of the goods.


Benjamin Moses: Exactly, yep. The article talks about the AI tools for the business side of things. It talks about a couple use cases. I thought it was a fairly good article. The machine learning and artificial intelligence is kind of embedded into those applications. So they talk about ... Here's a quote from the article. Hold on, before we get into it, there's a new buzz word.


Stephen LaMarca: Tell me.


Benjamin Moses: The new buzz word is enterprise cognitive computing.


Stephen LaMarca: Dude, cognitive in general, people love throwing cognitive. Don't get me wrong, I heard cognitive a while back when graduating college and looking for a job. Everybody was like, well do you have cognitive problem solving skills? It's like, shut up man. That just means you can ... Never mind. They're using cognitive automation.


Benjamin Moses: Yep.


Stephen LaMarca: It's the term that they're using for third gen robotics. So we're going from industrial robots to collaborative robots in the next step. Implementing AI in a collaborative robot will be called cognitive robotic or cognitive automation.


Benjamin Moses: Yep.


Stephen LaMarca: It's like, shut up man. You can't do that because a cognitive robot is still a cobot. We need a new term.


Benjamin Moses: Yeah. So let's see, enterprise cognitive computing, ECC. ECC applications can automate repetitive formulaic tasks and, in so doing, deliver orders of magnitude improvements in the spread of information analysis, and the reliability of accuracy of outputs. There's a couple key terms in there that I want to highlight. So basically they're applying machine learning or artificial intelligence, whatever depending on whatever layer you're working on.


Stephen LaMarca: Sure.


Benjamin Moses: But they hit on automated repetitive formulaic tasks. So they're jumping right into the applications of they're not solving cancer through artificial intelligence. They're not improving the world magically. They're saying, we're just automating processes so the less humans are involved in this.


Stephen LaMarca: Yeah. They're taking care of the busy work.


Benjamin Moses: Yeah, exactly. Then the second part of it is the reliability to accuracy of the output. So they've got this agent that's suggesting things, that's helping you solve this problem faster and quicker. Just like if I'm putting a robot to attend a machine. A human doesn't have to load the material. The AI is doing that automative task for you. It hit on a couple of good use cases on the business side. So let's see. Let's talk about call centers.


Benjamin Moses: So the first layer before you actually get to human is some level of bot that will handle your call. The use case that they talk about solves like 90% of the calls, but they're able to go to 24 hour support, 365 days a year theoretically through that. So I thought that was pretty handy. Loan processing to help reduce fraud was another application. Legal applications for developing case precedence. I thought this was really interesting and there's potential applications to manufacturing. So if a job shop is receiving purchase orders or receiving jobs, this legal application is basically that of I have this new thing, have I done this before in the past.


Stephen LaMarca: Right.


Benjamin Moses: So comparing what I have now to my other cases is basically what they're doing.


Stephen LaMarca: Right.


Benjamin Moses: That can help solve bidding quoting time and reliability, and that type of stuff. The other case ... obviously they're talking about investment applications for buy sell recommendations. So the big takeaway here is there's opportunities on the business side. It's automating processes, that's what it's meant to do. It's a journey. It requires data for you to build these tools. If you have a call center, you're not going to implement this call center right away to have them talk to a bot. You've got to teach the bot everything about your company. So you've got to document a couple of months worth of calls, put that agent in to your mathematical model. Then the output is your solution, an automated task. So it's a journey. That's a big takeaway.


Stephen LaMarca: I think call centers and 800 numbers, toll free numbers, have really come a long way.


Benjamin Moses: I agree.


Stephen LaMarca: You call a number and sure you get an automated answer at first, but I think they use it kind of as a vetting process.


Benjamin Moses: Right.


Stephen LaMarca: If you get through enough of the menus, and a good one doesn't have too many menus, but once they determine where you need to go, instead of sending it to a front desk receptionist who needs to determine themselves, who may not have that much information on you or who you need to talk to, and having them play the guessing game and potentially send you to the wrong person who then has to send you to the right person. Instead of talking to three different humans, you talk to a robot who sends you to the right human right away.


Benjamin Moses: Correct. That's valuable.


Stephen LaMarca: That's really valuable. That's the current state. I think that's where they are now because of stuff like this.


Benjamin Moses: You have layers to that too. You have the voice recognition side of it, so being able to talk to the robot, having it understand what you're saying.


Stephen LaMarca: You don't even need to use the keypad.


Benjamin Moses: Then making the decision to say, hey I can't solve this problem, but Joe in the back room can.


Stephen LaMarca: Yeah, or we know where to send this.


Benjamin Moses: Exactly.


Stephen LaMarca: Or even in some cases, do you even need to talk to a human? Can the machine, can the robot take care of this for you right now? Do you even need to waste another human's time?


Benjamin Moses: Yep. You see that a lot on websites that have a very robust chat bot.


Stephen LaMarca: Oh yeah.


Benjamin Moses: But to create those chat bots, it's got to ingest all that information that you've collected as a human before.


Stephen LaMarca: You know where I think the next step is?


Benjamin Moses: I'm listening.


Stephen LaMarca: Instead of call centers and toll free numbers, keeping doctors and dentists honest.


Benjamin Moses: Oh maybe.


Stephen LaMarca: You schedule a doctor's appointment at 10:00 AM. You get there at 9:45 because you want to make sure the check in is right, and then you end up waiting an hour and a nurse doesn't come gather you until 10:45 once they've found your charts or whatever that means. Then they pull you into the room, take your weight and height, and then you wait another 15 minutes to actually talk to the doctor who doesn't even make eye contact with you. If I make an appointment at 10:00, I want to talk to the doctor at 10:00. If I'm late, shame on me. That's my fault. But I think this kind of automation and AI can help out a lot with something like a doctor's office.


Benjamin Moses: Improving the user experience.


Stephen LaMarca: I think that's ... Because calls, we just talked about. Calls have come a long way and they're pretty awesome right now.


Benjamin Moses: I agree. I hate going to the doctor.


Stephen LaMarca: I don't think anybody likes it.


Benjamin Moses: I feel bad-


Stephen LaMarca: I've got a great dentist. I like my dentist.


Benjamin Moses: Actually, I enjoy going to the dentist because I can text them to schedule an appointment.


Stephen LaMarca: Dude, we are so weird.


Benjamin Moses: You and I?


Stephen LaMarca: We're probably the only people who like visit the dentist.


Benjamin Moses: Oh yeah.


Stephen LaMarca: Think about that man.


Benjamin Moses: That's true. That is kind of wack. What's the next article?


Stephen LaMarca: All right, man. So this awesome little article is less so an article and more of a buyers guide. This came up on tech trends. I was surfing through tech trends and I see this title, but anyway, it's a buying guide to these cheap Chinese engraving machines. While it's not American manufacturing technology, what's really cool about this is I'm just looking through this very elaborate guide onto how to buy a good and cheap engraving machine that, will this work for you. We're talking hobbyist level, so $100-200.


Benjamin Moses: Wow.


Stephen LaMarca: CNC engraving machine and this guide goes into detail on, so what are you trying to do. What kind of machine do we need to get you to it can be motted to what you're trying to do.


Benjamin Moses: That's cool.


Stephen LaMarca: Can the spindles be upgraded? Even though they're talking right off the bat about engraving machines, these machines can be upgraded to be three axis CNC milling machines. You can swap out the spindle for a laser cutter. They're hugely modular. The modularity is the coolest things about these wish.com CNC machines. It's absurd. I wouldn't want to talk about this at all normally because we're talking about Chinese equipment and we're association for manufacturing technology for American manufacturers, American manufacturing technology builders. But the coolest part about this was I just went to San Francisco not too long ago to visit some startups who have residencies at auto desk in San Francisco.


Stephen LaMarca: A lot of the startups that are trying to do something or they're doing something that's really innovative and that has anything to do with milling or engraving, or making a CNC machine in general, they all have one of these.


Benjamin Moses: Oh wow.


Stephen LaMarca: A square one. Some form or another as their first prototype.


Benjamin Moses: Okay.


Stephen LaMarca: It's one that's heavily modified, but they just needed a template to go off of. What needs to be improved? Everything, but that was their starting point.


Benjamin Moses: Yeah, I think you mentioned a proof of concept as very low entry for testing something out.


Stephen LaMarca: Yeah, going back to what I was saying earlier about coding, I could never ... It's impossible to start from scratch, but even if you start with a god-awful terrible example of something, it's easy to point out what needs to be fixed and you just tackle what needs to be changed one at a time.


Benjamin Moses: Sure.


Stephen LaMarca: This buying guide goes into that.


Benjamin Moses: That's cool. That's a handy tool.


Stephen LaMarca: It's really, really cool. I can't wait to share that link.


Benjamin Moses: It sounds like it's a great way to pick up stuff for a small desktop test bed, or if you're willing to explore that.


Stephen LaMarca: Dude, whether you just want a little CNC toy to wrench on in your own garage at home or desktop for that matter, or you have an idea to create your own startup, or if you want a test bed.


Benjamin Moses: Test a little robot in between the solutions, that's awesome.


Stephen LaMarca: Exactly, that's what this thing is for.


Benjamin Moses: The next article that I got is from the National Institute of Standards in Technology.


Stephen LaMarca: We love NIST.


Benjamin Moses: Right down the street.


Stephen LaMarca: Got to love them.


Benjamin Moses: Up the street, the one across that bridge.


Stephen LaMarca: Easy drive.


Benjamin Moses: Not during rush hour. That will kill you.


Stephen LaMarca: No, we're going against it.


Benjamin Moses: I guess. It sucks either way for me.


Stephen LaMarca: Fair enough.


Benjamin Moses: So they talk about the economics of additive manufacturing. So this is a research paper that was published in 2013. It's still very relevant today. They talk about the overall macroeconomics about additive manufacturing. It has a couple of key elements that are still super relevant today. It covers current state, what was going on in terms of technologies, who the stake holders are, potential use cases, and change agents. Another really good excerpt from the abstract. Let's see, change agents for that of a manufacturing industry can focus their efforts on three primary areas to advance this technology, cost reduction, accelerating the realization of benefits, and increasing the benefits of additive manufacturing.


Benjamin Moses: So before I read the rest of it, I thought those are really key things that say the technology creators of additive equipment can really focus on is, hey your equipment is expensive. That stuff has got to come down. Now some of it, you're building big environmental chambers, plus the lasers. There is going to be a lower threshold, but man it's expensive to get into-


Stephen LaMarca: We're talking about edge technology, so it's always going to be expensive.


Benjamin Moses: Yep, then the realization of benefits. So if I buy a piece of equipment, being able to get to a more profitable state. One of the benefits of ... If I do grow something and then additively manufacture it, what is the benefit to the end user? So that whole ecosystem of, hey these things could be better need to be realized sooner, either before you start cutting chips, before you start melting parts, before you start thinking about designs. So, that whole ecosystem needs to improve on.


Benjamin Moses: Then later in the abstract it talks about a significant impact on these areas may be achieved through the reduction in the cost of systems utilization, material cost which is still-


Stephen LaMarca: Oh yeah.


Benjamin Moses: I wouldn't say it's outrageous, but it's not the best. Facilitating the production of large products. Yeah, we've seen that there are size limitations of additives still. There also is a need for standardized model for cost categorization and product quality and reliability testing. I think that cost categorization is pretty solid, so being able to understand how much a part will cost, especially when we look at metals. I think we're getting there, but if you look at the full processing of from the concept to getting on a part, getting a part and final assembly, that whole rationalization of how much it costs versus traditional manufacturing. I think it's got aways to go.


Benjamin Moses: So the article is pretty good. It's a fairly long read. It's like 50 some pages, but it goes into some ... It's a good airplane read. I highly recommend it. It does get into a little bit of some mathematical equations when he talks about change agents and things like that.


Stephen LaMarca: Awesome.


Benjamin Moses: But I highly recommend just taking a glimpse of this because it does highlight some of the things that need to be improved in additive. That's where I think additive has some negative light to that where there's still too much hype behind it. Working with a company that presented the pros and cons of additive manufacturing at a summit awhile ago.


Stephen LaMarca: Well, in 2013, there was still a lot of hype to additives.


Benjamin Moses: There's still a lot of hype. I'd say there's still enough hype that companies are making bad business decisions on additive manufacturing.


Stephen LaMarca: Right now, still?


Benjamin Moses: I think so, yeah.


Stephen LaMarca: Okay.


Benjamin Moses: Some of it could be carried around.


Stephen LaMarca: They're probably just not enough in the know.


Benjamin Moses: The guys that presented in January at one of our committee meetings talked about several companies that have shut down because of their exploration of additive manufacturing. So some of that is carried over from a couple of years ago where they just haven't been able to get new business, but in the end it's a bad business decision. I definitely recommend this read if you're exploring, getting into additive as part of your core business. Now if you're doing it as sport tooling and things like that, prototyping, that's a more cap X exercise. But if you want to make it part of your core business, this is a strong lead.


Stephen LaMarca: Does this paper, it sounds like, does this go into the standards behind additive at all? 2013, that was still before standards really started getting-


Benjamin Moses: There's still the growth of standards within additive. I think it does mention the need. It does mention the need for standards in terms of reliability testing and then the standard for reliability or quality testing, but it doesn't highlight the issues that have become more prevalent. In the past couple of years, we've seen a huge growth that has gone into production testing. So being able to consistently test the same part over and over again is a big problem now.


Stephen LaMarca: Right.


Benjamin Moses: They're CTing every single part that gets made, which is expensive and ... well you could say it's automated somehow. There's still some level of interpretation that goes on that there are not strong standards on.


Stephen LaMarca: I would imagine it's not the easiest or it's probably pretty difficult to batch test additively produced parts unless you're making multiple parts in one brand.


Benjamin Moses: Yeah.


Stephen LaMarca: Interesting.


Benjamin Moses: So there's still questions about should I hit the parts, do I need to stress relieve. There's still some very fundamental questions on the value of some of these things. I was at America Makes TRX meeting a week or two ago in Texas, and they talked about some of the foundational issues that are still prevalent, which is interesting because I feel like castings, the casting industry has kind of solved some of these issues or either accepted that we're just going to do this as part of our norm. I feel like additive still has a lot to learn from the casting industry.


Stephen LaMarca: Let me ask you a more basic question, because you just mentioned hipping and stress relief. Does cryogenic treatment of a part, does that fall under stress relief because you're trying to align the molecules of a part in a more friendly stable manner after production?


Benjamin Moses: That's a good question. I would say conceptually yes, but in writings and actual application, no. I feel like cryogenics is its own material subset, so usually in most of the literature when you say heat treating, it's an elevated temperature cycle.


Stephen LaMarca: Yeah.


Benjamin Moses: Cryogenics being negative temperature is not grouped in the same category as that.


Stephen LaMarca: Interesting. Okay.


Benjamin Moses: I do like me some cryogenically treated roters though.


Stephen LaMarca: Or shotgun barrels. All right-


Benjamin Moses: What's that last article you got there Steve?


Stephen LaMarca: The last one I've got is a fun one. It is metrology used in the motorcycle industry. So when you look at the timeline 20 years ago, and I would say for myself not even 10 years ago, a brand, an Austrian motorcycle brand KTM was relatively unheard of.


Benjamin Moses: Yeah, they're known for their off road stuff.


Stephen LaMarca: A lot of stuff is new to me even still today, but I feel like if you said, KTM makes a car today, it'd be like who is KTM?


Benjamin Moses: And they have a car.


Stephen LaMarca: They're Austrian. They're like, Austria makes ... I know Austria makes the glock. They make a car? I hope it's as reliable as a glock. But KTM is a European brand that makes pretty affordable motorcycles for ... considering that they are a European motorcycle brand. They're up there in terms of price with the equally innovative or seemingly really innovative Japanese motorcycles, but KTM really came out of nowhere.


Benjamin Moses: Okay.


Stephen LaMarca: In an industry where there's a lot of established brands and a lot of innovative established brands, like your Honda, your Yamaha, Kawasaki, Suzuki. The ones that get to outside of Japan, Dukati, Triumph, BMW. Those are the innovative brands that a lot of people think of and they've been around for a long time, and nobody has really heard of KTM. From a marketing standpoint, it was genius for them to come out with, I guess 10 years ago, the KTM crossbow which was a street legal go kart.


Benjamin Moses: Open air cockpit.


Stephen LaMarca: Yeah, that thing is still really awesome, even though it's kind of phased out. Not phased out, but nobody really talks about it anymore. But it's still awesome.


Benjamin Moses: Ariel Atom has the same problem.


Stephen LaMarca: People think about the Ariel Atom. The other thing that kind of eclipsed the Ariel Atom is the-


Benjamin Moses: BAC Mono.


Stephen LaMarca: The BAC Mono is my dream car.


Benjamin Moses: That thing looks really good.


Stephen LaMarca: I love that you can't put anybody else in it and there's no storage space.


Benjamin Moses: I love how when I go to the website and I'm like, how much does this cost? Oh my gosh.


Stephen LaMarca: It really is like a four wheeled motorcycle because it's got the sequential gear box. It doesn't have some automatic or manual. It's a sequential gear box.


Benjamin Moses: It's so expensive though.


Stephen LaMarca: It's a four wheeled motorcycle. It is really expensive for what it is, but their rationale is it spoke to you. It only seats one person and it can only fit one person because we have to size you up before we make it. Everything is made out of carbon fiber.


Benjamin Moses: Sure.


Stephen LaMarca: Performance wise, even though it's only a naturally aspirated 2.5 liter four cylinder ... I don't know if it's 2.5.


Benjamin Moses: Sure.


Stephen LaMarca: Naturally aspirated four cylinder, it still goes. It has its zero to 60 time equal to a McLaren P1, which is a million dollar plus super car. So when you think about that, $100 thousand for the BAC Mono is a deal. Anyway, we have totally digressed.


Benjamin Moses: Back to inspection.


Stephen LaMarca: Back to motorcycle metrology. KTM, in this kind of piece that's just on KTM, they're like so how did you guys blow up, how did you guys seemingly come out of nowhere in an industry that is dominated by so many other established brands? It's saturated by a lot of other brands that are both innovative and have been around forever. Not you Harley Davidson. How did you do it? They were like, we didn't really do anything special. We use really high end metrology inspection equipment to have world dominating quality assurance.


Benjamin Moses: That's awesome.


Stephen LaMarca: A customer will never see a poorly produced part on anything that we make.


Benjamin Moses: That's cool.


Stephen LaMarca: So, if anything ... The point that they are trying to convey, that I am trying to convey here is they're not the most innovative.


Benjamin Moses: Sure.


Stephen LaMarca: And they own that. What they are though is they will ensure that nothing bad leaves their factory, which is really cool. They're really uptight about their quality assurance, which is awesome.


Benjamin Moses: Sure. So maybe another way to phrase it there, innovative in a metrology.


Stephen LaMarca: Yeah, they are.


Benjamin Moses: That's cool. I like that.


Stephen LaMarca: It is really cool.


Benjamin Moses: Depends on what you do.


Stephen LaMarca: Yeah. So we can find links to all of these articles that Ben and I talk about in the description that will pair along with this podcast. You can reach out to Ben on-


Benjamin Moses: Before you get that far.


Stephen LaMarca: Okay.


Benjamin Moses: Episode is sponsored by the MT360 conference.


Stephen LaMarca: Oh, of course.


Benjamin Moses: So if you want to understand the latest transform of technology getting into manufacturing, check out MT360 conference.com. Also, if you want to hear from Steve on a regular basis, we've created the MT360 tech report.


Stephen LaMarca: That's right.


Benjamin Moses: That gets published every week. You can also sign up for that at MT360confernece.com/blog.


Stephen LaMarca: That's a good little snippet of tech trends that I am pushing out with my own-


Benjamin Moses: Barrings.


Stephen LaMarca: With my own spin on what you're going to be reading. It's not full access to tech trends. It's a nice little snippet, what I would like to think as the best of, but the other good thing is it's free.


Benjamin Moses: It's free, and you get to see Steve's face at the bottom of the email letter.


Stephen LaMarca: And I get to quote somebody fun every week.


Benjamin Moses: So where can they find more information on Steve?


Stephen LaMarca: They can see all those links in the description because I don't have the websites off the top of my head. They can reach out to you on Twitter and LinkedIn.


Benjamin Moses: Just LinkedIn.


Stephen LaMarca: Just LinkedIn.


Benjamin Moses: For Gods sakes.


Stephen LaMarca: Why do I always think you have a Twitter?


Benjamin Moses: I do, but it's personal and I use it to follow my daughter's teachers at school.


Stephen LaMarca: Well, I know this about your LinkedIn. On your LinkedIn, on weekly basis, you do repost, retweet if you will, my weekly test bed updates.


Benjamin Moses: That's correct.


Stephen LaMarca: So you can also find my blog and my test bed updates at [inaudible 00:42:41] Steve.blogspot.com.


Benjamin Moses: That's enough. All right, bye everybody.


Stephen LaMarca: Goodbye.


Benjamin Moses: That was good.