Dynamic Bottleneck Forecasting in Flexible Manufacturing Systems

Speaker: Ferdinand Klenner, BMW

In the context of Industry 4.0, flexible manufacturing systems are the conceptual basis for highly flexible and efficient high-volume manufacturing. But the inherent complexity of these systems and the lack of transparency impede the further increase of their efficiency. If the number of machine breakdowns exceeds the resources of operators and maintenance, it is necessary to guide the employees to the most critical machines. Based on the approach of the Theory of Constraints, the most critical machine is called bottleneck and restricts the throughput of the entire system to any given time. Thus, an effective decision support system for production employees needs a real-time identification of momentary bottlenecks. Furthermore, a bottleneck prediction can support the employees to plan actions in advance and prevent uncoordinated firefighting. Hereby, production data, modern IT-infra- structure, and data mining applications enable the development of real-time identification and prediction of bottlenecks in such complex, flexible manufacturing systems.

Ferdinand Klenner, BMW

Project Leader Predictive Analytics and Optimization Flexible Manufacturing Systems

Ferdinand Klenner, born in 1986, studied mechanical engineering and business administration at the RWTH University of Aachen. Since 2013, he works as project leader in the predevelopment of the production de- partment for the BMW Group in Munich, where he is responsible for the analysis and optimization of flexible manufacturing systems using advanced data analytics.