Automatic Optimization Techniques Applied to a Large Range of Industrial Test Cases

TL;DR: Ten industrial partners have been selected to cover the different area of the mechanical forging industry and provide different examples of the forming simulation tools and an optimization module, fully embedded within the Forge2009 IHM, makes possible to cover all the defined examples.

Abstract: The use of material processing numerical simulation has spread widely in recent years in the engineering industry. It allows a strategy of trial and error to improve virtual processes without incurring material costs or interrupting production and therefore save a lot of money. On the other hand, it requires user time to analyze the results, adjust the operating conditions and restart the simulation. Automatic optimization seems the perfect complement to simulation. Evolutionary Algorithm coupled with metamodelling makes it possible to obtain industrially relevant results on a very large range of applications within a few tens of simulations and without any specific automatic optimization technique knowledge. In the frame of the LOGIC ANR French project, ten industrial partners have been selected to cover the different area of the mechanical forging industry and provide different examples of the forming simulation tools. An optimization module, fully embedded within the Forge2009 IHM, makes possible to cover all the defined examples, and the use of new multicore hardware to compute several simulations at the same time reduces the needed time dramatically. The presented examples demonstrate the method versatility. They include billet shape optimization of a common rail and the cogging of a bar.