Multi-objective parameter optimization to support energy-efficient peck deep-hole drilling processes with twist drills

Abstract

Reducing energy consumption (EC) is an essential strategy for improving the sustainability of manufacturing industry. Machining processes have been widely applied in manufacturing industry, and current research has demonstrated that the machining parameter optimization is an effective energy-saving measure under the given processing conditions. Drilling is a typical machining process, and it is convenient to make deep holes through peck drilling with twist drills in practice. However, owing to the inefficiency of peck drilling with twist drills, many efforts have been devoted to improving the performance of peck deep-hole drilling process (PDDP). Correspondingly, the parameter optimization considering traditional performance indicators, such as processing time, tool wear, and drilling force, has been fully investigated. Nevertheless, the existing research rarely touches on the EC optimization or the improvement of EC-related environmental impacts. To bridge this gap, an approach based on the operating parameter optimization is proposed to fulfill the energy saving of PDDP, and the corresponding mathematical model considering EC and processing time simultaneously is established. To evaluate the EC of PDDP reliably, the Therblig-based energy supply models of machines are utilized. Further, a particle swarm optimization algorithm-based solution method is adopted, which can make a trade-off between two optimization objectives objectively and acquire the most suitable operating parameters. Moreover, experiments have been made to evaluate the energy-saving potential and the performance of the algorithm. Experimental results show that there could be significant potential for improving optimization objectives simultaneously through the operating parameter optimization, and the solution method is feasible.