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This paper deals with the conception and modelling of overlapping business processes which base upon software agents. The regarded processes arise in connection with the research project CoagenS, in which learnable production networks of series fabrication will be conceived and realized. The R&D project CoagenS is supported by the BMBF1 within its programme: “Research for the production of tomorrow.” By the use of a software agent the in-house purchase processing of the Supply Chain Management is arranged more efficiently. The benefit of software agents results from its special flexibility and the capability to learn, which allows solving a problem without a central coordinator. By means of attributes such as autonomy, reactivity, sociability, and productivity software agents dispose of the possibility to plan and to track a multitude of complex functions independently.

Control strategies - the long term rules used in production planing and control - for highly integrated and flexible manufacturing systems in most cases are specialized in specific and usually constant production programs. Therefore, changes in the production program require adaptations in those single or combined control strategies. To keep the system optimal, there is a need for more than just analytical mathematical methods, whose limits are quickly crossed because of their complex correlations. An effective device for the development of optimal control strategies connected with an advantageous system structure is the focused Experiment Planning. It combines static analysis and calculations with dynamic simulations in order to develop alternatives for improvement of control strategies and the system structure in a repetitive process.