Load and energy management for factories through multi-stage production planning and optimization

The production phase has a major influence on the embodied energy of many products and, thus, their overall environmental performance. As a result, manufacturing enterprises are prompted to raise their energy efficiency and flexibility to improve their products' sustainability. The simultaneous integration of renewable energy sources and decentral storages is a feasible option in this but also require consistent solutions for appropriately planning and controlling the operation of the entire factory system. This paper proposes an iterative multi-stage heuristic optimization for intelligent load and energy management. A load profile of the production plan, based on the minimized overall makespan, is checked against the available energy supply to identify demands and opportunities to shift single jobs based on calculated buffer times. Whenever infeasibility is determined, the process returns to the previous production planning stage for further alterations. This cycle is initiated regularly (e.g. weekly) or following certain events (e.g. long-lasting machine failure) and terminates once all restrictions are observed or if a termination threshold (e.g. calculation time) is reached. The experimental setup used for developing and validating this approach to energy-aware factory operation makes use of a probabilistic material flow simulation model. It provides information on tasks to be scheduled and executes production plans to evaluate the performance of the proposed solution. This new approach to energy-aware factory operation also provides opportunity to integrate additional ecologic criteria to improve the sustainability of manufactured products. (C) 2019 The Authors. Published by Elsevier B.V.