A pressing case for predictive analytics at MacLean-Fogg
Metform chose to focus specifically on the AMP50XL’s drive train because “that was the area where we saw the biggest opportunity for improvement.” While they’d previously been gathering data from the machine for predictive-maintenance use, the old process was neither efficient nor of adequate detail, they realized. “From a data collection standpoint, there was a lot of spreadsheets, a lot of handwritten notes, a lot of tribal knowledge,” Delk said. “We wanted to make sure we could gather that information and put it into context as we were analyzing the equipment.”
“We’re able to monitor the machine health, see in real time how the machine is doing and see a signal of a problem before it becomes a major problem. We have a long way to go in terms of learning how to better use the system and gain further confidence in the system, but at this point, I’m really pleased with the progress we made. I’m anxious to expand this to the other nine Hatebur presses.”
Metal Forming Division: long live the loop
“For us in the Metal Forming Division, accuracy and early error detection are particularly important.”
A critical factor is the high production speed of the roll forming lines, which can process up to 120 meters of sheet metal per minute. The later a defect is detected, the more material and time is lost.
“The goal of digitalized roll forming is to replace the previous process monitoring, such as checking the dimensions afterwards, with automatic inline measurement to allow us to move from process monitoring to digital process control.” If this goal is achieved, we could be looking at up to four times the accuracy in production.