An adaptive simulation-based optimisation approach for the scheduling and control of dynamic manufacturing systems - Phase 2

• Applicant: Professor Dr.-Ing. Michael Freitag
• Subject Area: Production Systems, Operations Management, Quality Management and Factory Planning
• Term: from 2016 to 2021
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 288035798

In order to assure a high performance of dynamic manufacturing systems, the currently processed project AdaptiveSBO develops a data-driven adaptive simulation-based optimisation (SBO) method that derives optimised machine assignment and dispatching rules according to the current state of a manufacturing in real-time. The approach couples an SBO method deriving optimised rules for shop floor control with a framework for the data exchange between the SBO method and the manufacturing system. In this way, the optimisation always considers the current state of the system. Until now, the approach assumes an ensured availability of raw material and does not consider possible lacks. Moreover, the current approach only takes into account maintenance indirectly by performing reactive maintenance when a machine breakdown occurs. In order to reflect the current state of a production system in a more detailed and realistic way, these aspects will be taken into account in the proposed continuation of this project. In this way, the approach will on the one hand be able to derive well-founded solutions in the unwanted case of a lack of raw material and will, on the other hand, achieve less machine downtimes and therefore save costs. The main goal of the proposed project continuation is the development of a data-driven adaptive SBO method for integrated inventory, production and maintenance control.In order to achieve the main goal of the project, the already developed SBO method has to be extended in several ways. On the one hand, the method has to be expanded to derive priorities for maintenance jobs as well as production jobs depending on the current raw material inventory levels. On the other hand, the developed data exchange framework has to be extended to include all relevant data for the bidirectional data exchange between the new adaptive SBO method and the shop floor.While the German research group develops an SBO approach for integrated production and maintenance control, the Brazilian research group develops in parallel an SBO approach for integrated production and inventory control. Subsequently, the two approaches are merged to achieve the main goal of the project. For the examination of a realistic production scenario, the approach is applied to the job shop of a Brazilian producer of mechanical parts. Based on this scenario a test bench platform is developed, which is used for the evaluation of the developed method. The results will be published as a benchmark for future research in this field.

• DFG Programme: Research Grants
• International Connection: Brazil
• Cooperation Partner: Professor Dr.-Ing. Enzo M. Frazzon