A Multi-agent Approach to Computational Optimization of Metal Forming Processes

In the paper we present a new original approach to a complex multi-phase process optimization problem that relies on dividing the optimization task into partial tasks related to the implementation of individual phases. To implement this concept, we propose a multi-agent approach. Its practical realization is shown on the example of manufacturing process for auto body parts made of the Advanced High Strength Steels (AHSS). Although it is a rather simple process consisting of only two phases, we assumed, however, that the results obtained will allow to extend further research to more complex problems. We present the operating principles of a multi-agent model, the flow of the messages between agents, and the architecture of the system. To ensure the proper speed of the whole system a simple and flexible multi-agent framework called Eve was used to develop a prototype of the system. Research performed, as well as preliminary tests have shown that a multi-agent approach can be successfully applied to reduce complexity of the whole optimization processes. Due to splitting a single, complex optimization process into several, partially independent optimization processes, delegating them to autonomous agents, and application of a knowledge-based reasoning system, significant advantage could be observed over to the solutions described so far in the literature.