An energy-responsive optimization method for machine tool selection and operation sequence in flexible machining job shops

The environmental burden caused by energy consumption during the use phase of machine tool systems is widely acknowledged and hence ways must be found to use energy more efficiently. There is potentially a significant amount of energy savings that could be realized by selecting alternative machine tools and reducing the idle energy consumption through better scheduling. This paper proposes an energy-saving optimization method that considers machine tool selection and operation sequence for flexible job shops. The former seeks to reduce the energy consumption for machining operations, and the latter aims to reduce the idle energy consumption of machine tools. A mathematical model is formulated using mixed integer programming and the energy consumption objective is combined with a classical objective, the makespan. A Nested Partitions algorithm, which has proved to be robust for NP-hard problems, is utilized to solve the model. The proposed method is evaluated in a test case by two scenarios with different energy optimization schemes as well as the classical makespan objective. The results show that the proposed method is effective at realizing energy-savings for a flexible machining job shop.