Issue link: https://iconnect007.uberflip.com/i/1520213
18 SMT007 MAGAZINE I MAY 2024 then it becomes very hard to change people's behavior. Specific to changeover, if my facility special- izes in small volume, high mix, would that give me more opportunity to realize change- over efficiencies, rather than a facility doing long run, high volume jobs? Are there more opportunities to apply these tools on the floor than just changeover or operator response time to a machine alert? Luis Vidal: Smaller and midsize players gain a lot when they increase OE from 50 to 65%. In higher volume players, the line revenue might be $20–25 million a year, on average. Even small changes in OE can make a difference from a growth standpoint. In very large organizations, change can be a challenge. ings are political, and there are many decision-makers. If you want to recom- mend a change to optimize, you might need to supply 10 examples of why it's not working. Our system gives people the ammunition they need to go into a very complex organizational environment and say, "Hey, this doesn't work. Here's the reason why. Let's go fix this." e data will set you free. Vora: To Luis's point, we sometimes have dif- ficulty convincing our customers to make changes. I might say, "Why is this so expen- sive? Make this change, and I can reduce your price." But he doesn't until he sees his product on the line. Instead, I can show him a video and show him how long it takes compared to this other board, which was designed correctly. I can show why it moves so much more effi- ciently through our system. I think there is a case to be made. Holden: e main impact is wherever operator behaviors matter. ere are other processes, like material prep. If something is slow, it's usu- ally because the material wasn't ready, or it was prepped the wrong way. It's very rare that it's because something broke somewhere. ere's another video of a downtime event that's just over an hour long. In it, you can see this yellow stock light blinking. ere's nobody there; somebody should go check it. en, you can see when they responded to the light. ey're arriving but they don't take any action to respond to the light. If they see it, why are they just waiting? Turns out this operator has run out of material. She's ordered it from the warehouse and is waiting for the warehouse to bring it over. In the video, we see the deliv- ery. en there's some chatting and now she's doing the change. ere was an hour of time spent here. Because of the video, it only took us five minutes to figure out what happened, and we didn't have to watch the whole hour. We can also see that it wasn't necessarily the opera- tor's fault. e question is really, "Why wasn't it ready?" Even in our focused manufacturing space, AI providers are churning. A couple have radically pivoted, and others are gone. Where do you see this going? Luis Vidal