面向绿色制造的轴承生产车间多目标调度优化

Multiobjective scheduling optimization of bearing production workshop for green manufacturing

针对高性能轴承零部件的加工过程,以最大完工时间、机器加工碳排放量和磨削液使用量为目标函数,对轴承零部件加工的绿色车间调度问题进行研究.将轴承零部件的加工过程细化为启动、装夹、加工、卸夹、待机和关闭共6个流程,建立多目标绿色调度数学模型;提出了改进的多目标遗传算法进行求解,采用融合工序选择和机器选择的分段式编码方式,并在交叉、变异等步骤进行改进,提高算法收敛性;最后以某轴承公司的轴承零部件加工过程为例进行案例分析与对比试验,并通过大规模数据测试与分析.结果表明,所提模型可以得到更低的完工时间、碳排放量和磨削液使用量,从而验证了所提模型的科学性和有效性.

Aiming at the machining process of high-performance bearing parts,the green shop scheduling problem of bearing parts processing was studied herein,with the maximum completion time,minimum machine carbon emission,and minimum grinding fluid usage as the optimization objectives.The manufacturing process is divided into six technological processes:startup,clamping,machining,unloading,standby,and shutdown.The multiobjective green shop scheduling mathematical model is established.Then,an improved multiobjective genetic algorithm is proposed,adopting a segmented coding method that integrates the process and machine selections and improves the steps of crossover and mutation,all of which improve the algorithm s convergence.Finally,the bearing parts processing of a bearing company is taken as a case study,and large-scale data tests and analyses are constructed.The result shows that the proposed model can obtain lower completion time,carbon emission,and grinding fluid consumption,which verifies the scientificity and effectiveness of the proposed model.