Comprehensive Energy Saving Optimization of Processing Parameters and Job Shop Dynamic Scheduling Considering Disturbance Events

doi:10.3901/JME.2022.19.242

Abstract

Abstract: As energy consumption and environmental problems continue to intensify, efficient and energy saving production in machining job shops has attracted more and more attention from the manufacturing industry. In traditional dynamic scheduling optimization, the processing parameters of each operation are fixed, and the relationship between processing parameters and job shop scheduling is not considered, which limits the potential of scheduling optimization. In order to better realize the energy saving and efficiency increase of the flexible job shop, and quickly and effectively deal with the sudden disturbance events, a comprehensive optimization method of processing parameters and job shop dynamic scheduling considering disturbance events is proposed. Firstly, the energy consumption characteristics of the flexible job shop under new job arrival and machine tool breakdown are explained in detail, and the comprehensive optimization model of processing parameters and dynamic scheduling is established with the objectives of total energy consumption and maximum completion time. Then, the dynamic decision-making mechanism for disturbance events is designed, and the improved adaptive geometry estimation based multi-objective evolutionary algorithm (AGE-MOEA) is proposed. Finally, the effectiveness of the proposed method is verified by case analysis and algorithm comparison.

Key words: energy saving, disturbance event, processing parameter, dynamic scheduling, flexible job shop

CLC Number:

TH162

Lü Yan, XU Zhengjun, LI Congbo, LI Lingling, YANG Miao. Comprehensive Energy Saving Optimization of Processing Parameters and Job Shop Dynamic Scheduling Considering Disturbance Events[J]. Journal of Mechanical Engineering, 2022, 58(19): 242-255.

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