Model-Based Optimization of Nonconformance Management in Manufacturing Systems

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The overall objective of the research project is the development of a simulation model that derives recommendations for an effective and efficient integration of the failure management process into the production process. The present research proposal follows the hypothesis that these recommendations for action can be gained from a system-dynamic simulation model. Based on the results of the initial application period, the detailing of the simulation model, which ist o be connected to the production planning and controlling, is the core objective of the second period. In the first step the relevant interfaces and influencing variables of production planning and control must be identified. Based on this, a concept is being developed to expand and connect the production sub-model of the first application phase. More specifically, the model is to be enabled to display a process chain with any number of process steps. The expanded simulation model provides the necessary level of detail to be connected to production planning and control via the identified interfaces. With the aid of simulation analyzes of a real production chain, recommendations for the optimization of failure management are derived i.e. measures for better networking between the failure management strategy of a company and its production planning and control. This is done by a step by step consideration of individual company conditions. Companies can profit directly from the research results by carrying out a company-specific adaptation of the defined parameter set to their individual configuration of failure management and also by using the new model approach for displaying their production process in detail. Following this, a simulation model can be created that enables the derivation of individual strategies for the optimized use of failure management. In this case, the amount of work involved in the simulation consists primarily in the optimization of the parameter values.