Podcast: Why AI is a must-have for manufacturers, plus practical use cases

Andrew Halonen is the president of Amatrium and the AmatriumGPT tool. Andrew has worked for 25 years in a variety of industries, including machine design, automotive castings, engineering, forging, and lightweight materials. Andrew earned a Bachelor of Science in Mechanical Engineering degree from Michigan Technological University, and he interned at Ford Motor Company before working for eight years at the 3M Company. Andrew recently spoke with Robert Brooks, editor in chief of American Machinist and Foundry Management & Technology, about new and inventive ways artificial intelligence is changing the manufacturing industry.

Below is an excerpt from the podcast:

RB: There's a distinction to be made between machine learning and other applications of artificial intelligence. The other application, of course, is what's referred to as large language models. And this is the basis of the well-recognized ChatGPT. Am I right to assume you are restarting a discussion here about the use of artificial intelligence in manufacturing?

AH: Let me say this. There's a lot of confusion around AI and business. Some people are tracking every detail, but most people that I reach out to in manufacturing aren't sure what to think of it. Is it a gimmick? Is it useful? Is it scary? Is it going to take my job? I even hear people say, “What is your AI strategy?” And I say, “The better question to ask is what problem are you aiming to solve.” Let's think of what the best tool is, and maybe AI is one of them. I'll even mention it to some of my clients, and they say, “If I hear the word AI from anybody else, I'm going to…” and then it's not very pleasant.

So, AI is very polarizing. Which is why we even removed it from our promotions. We don't talk about it. If you go to Amatrium.com, you don't see the word. You have to dig for it. Instead, we focus on the value which is largely around time savings. So again, we started in machine learning, and we learned a hard lesson. We scanned in a lot of high-quality data on aluminum castings, which is the world we know the best, and reached out to the die casters saying, “I have this prediction tool. You can put in your alloy, your temper, and it's going to push out properties.” Well naturally, they said, “Oh, that sounds fun. Let's go try it.” And they went, tried it with the alloys they were producing that day, and guess what? It didn't match. And now they won't return my phone calls. And that's why I say it's a painful lesson.

So why didn't that match? Well, if you step back and think about a metal casting foundry, when metal solidifies, what drove solidification? The geometry, the die life, the lubrications, the people that charge materials, there's all these things that are really pertinent to that process. So, on the machine learning side, we learned the lesson that the data that matters is your data, Mr. Customer, not a random scan of data. And so that's also a lesson in the large language models, right? When ChatGPT came out, people instantly had this phrase called hallucinations, which I call a used car salesman. It sounds elegant, eloquent, but it's wrong. And so why is that? Why is it wrong? Because they scanned the whole world, and then they tried to script an answer on, you know, extrudability of 7000 series alloys. So, with AmatriumGPT, how we solve that, we say, “Here. Load the data, your data. You trust it. You understand where it came from, and it's pertinent to your business.” And now when you ask a question, you get a great answer.

RB: Many manufacturing organizations already have members-only libraries. Would that be an appropriate or useful tool for AmatriumGPT?

AH: It's an exceptional tool for AmatriumGPT. Whether you're in powder, metallurgy, plastics, welding, or just about anything, you have members. The members help pay for research. You're doing research very pertinent to your business, your market, and over the years, you accumulate thousands of files. We were talking to organizations with 15,000 files. You have members from all these different countries, languages, all that. These tools are exceptional with search and discovery. You search on a topic like ‘what is the benefit of strontium and 356 aluminum?’ You get paragraph answers, in-line citations, and the citations come from the library. A lot of these libraries are sitting dormant because the search is so horrible. Now it's awesome and it's easy, and that's where you're going to go to for information.

And on top of that, you can put in sponsor ads to help pay the bills, and the sponsor ads, part of the SEO from those ads, they can get insight on what questions people are asking and help tailor their own strategies. So, it's an exceptional opportunity to really keep the member dues coming and even bring in non-dues revenue. So, one of our customers who's about to launch, they have some content that they don't want to give away for free. So, let's say you do a one-hour webinar, and you grab the transcript of that webinar. That's about 35 pages of content. That's in the background to provide great answers, but if somebody clicks on that citation, they'll get a little preview. And if they say I want to download this like they can for the free stuff, it will go to a URL to sell that. So that's another way membership groups can get revenue.

RB: I've browsed your website, which is www.Amatrium.com. And you have a lot there. Our listeners should go there and check it out. But one example that you have discussed with me involves Waupaca Foundry. For listeners who don't know, this is the largest ferrous metal foundry in the U.S., a very important, significant supplier to the transportation markets, passenger cars, commercial vehicles. And they are using the AmatriumGPT tool to research their technical records, which are extensive because the company has been in business for a century or more, and they're using it to create marketing reports. Apparently, it has other applications too. Would you describe what's going on there at Waupaca for our listeners?

AH: Absolutely. So, Waupaca is a technology company delivering a high-tech product for critical applications. The chemistry of the brake rotor is critical to the ability to stop your car on a dime or to stop the 80,000 lb. semi on the freeway. The challenge with marketing is they have to communicate this technology and the processing and so on to engineers in a way that's quick to consume, easy reading, and very informative. And engineers don't like fluff. So you have to include that whole technical story into a very readable piece. Well, of course the challenge is that marketers, for the most part, are not engineers. And then engineers don't have that marketing sense.

So that's where these tools like AmatriumGPT make up for the deficiencies. You can combine the technical information, the promotional, the case studies, sustainability, all these messages into one, list the documents, and then generate great content for your target audience. And this content comes out in like 10 seconds. Now Sarah is spending time on strategy and execution, not just writers block. How do I write this? What should it say? You know, going back and forth to engineers. I think when you see the content come out from your data, you're going to go to the engineer and say, “What do you think of this?” Pretty soon they're going to say, “You know what? I trust you. You don't need to keep coming to me.”

About the Podcast
Great Question: A Manufacturing Podcast offers news and information for the people who make, store and move things and those who manage and maintain the facilities where that work gets done. Manufacturers from chemical producers to automakers to machine shops can listen for critical insights into the technologies, economic conditions and best practices that can influence how to best run facilities to reach operational excellence.