Simulation based evaluation of machining processes (GRK2193)

The turbulences of modern markets with dynamic and intensive changes in the demands require factories and products to efficiently adapt with high frequency. The key factors for success are the time frame, which is necessary for the adaptation, and the efficiency and effectiveness of the adaptation process. The main research of the interdisciplinary Research Training Group “Adaption Intelligence of Factories in a Dynamic and Complex Environment” (GRK2193) therefore focusses on the development of methods for an integrated support of the adaptation process of factories. In order to investigate this comprehensive topic, different faculties (Architecture and Civil Engineering, Mechanical Engineering, Logistics, Business, Economics and Social Sciences, Computer Science, Electrical Engineering and Information Technology) are combined in this Research Training Group.

In order to support an efficient adaptation process for factory planning, a detailed and flexible data base containing, e.g., information about process time and energy consumption of the machining processes, is necessary. The information can be used for a suitable selection of machine tools which takes the required quality of the machined workpiece into account.

For the machining of new products and components, however, this information is generally not available. For this purpose, simulation systems are suited to analyse the virtual machining and to evaluate the process on different machine tools and with different process parameter values (fig.).

Fig.: Simulation system for analysing NC machining processes

In this project, an efficient simulation system for the analysis of milling processes is qualified for the application in the factory adaption planning process. For this purpose, the parameters relevant to the planning process (e.g. quality of the machined components, process time, process reliability and energy efficiency) are first identified and modelled using the simulation system. In combination with a model for the simulation of factory systems, it is possible to carry out multi-level optimisations taking into account multiple targets and considering the interaction of several, partly different processes. In this way, the simulated results flow into the adaptation planning process of a virtual model factory to support the decision-making processes.

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