Metal Forming
Assembly Line
In-process, real-time monitoring of forming forces in rotary draw bending process
Monitoring forming forces in metal forming processes is essential for analyzing process behaviors, mechanisms, and defect detection. This is particularly relevant in aluminum tube bending processes, where the dimensional quality of the formed product is sensitive to multiple upstream and in-process variables. This research presents a method for real-time, in-process monitoring of forming forces in rotary draw bending (RDB). By developing a set of innovative forming tools (clamp die, bend die, pressure die, etc.) with directional force sensors embedded, key forming forces are measured. Through a series of experiments, the measurement method was validated by analyzing both measured forces and calculated moments, demonstrating high measurement consistency. The systematic examination of measurement variations provided insights into the reliability and robustness of the method. Moreover, comparison with FE results supported the accuracy of the measurements. Additionally, laser-based measurements showed a good correlation between the measured springback angle and the calculated moment during bending. These findings lay the groundwork for the industrial implementation of in-process force measurements in RDB, advancing the production of tube components.
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 improveÂment.” While they’d previously been gathering data from the machine for predictive-maintenance use, the old process was neither efficient nor of adeÂquate 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 anaÂlyzing 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.”