Increasing energy efficiency in production environments through an optimized, hybrid simulation-based planning of production and its periphery

This research aims to develop a novel planning tool able to increase both the energy efficiency and general performance of production systems using a hybrid-simulation based, multi-criteria optimization, with this particular paper focusing on the optimization method. Lacking necessary planning tools for an energy aware production planning and control, companies are unable harness the associated optimization potential. State-of-the-art tools are not able to sufficiently consider interactions between the discrete system behavior of material flow and the continuous thermal-physical behavior of equipment. This paper presents a planning method addressing this deficiency. The developed genetic-algorithm based optimization module optimally fits the requirements.