• CN:11-2187/TH
  • ISSN:0577-6686

机械工程学报 ›› 2017, Vol. 53 ›› Issue (5): 24-33.doi: 10.3901/JME.2017.05.024

• 绿色制造技术 • 上一篇    下一篇

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面向低碳的切削参数与调度集成优化*

刘琼, 周迎冬, 张漪   

  1. 华中科技大学数字制造装备与技术国家重点实验室 武汉 430074
  • 出版日期:2017-03-05 发布日期:2017-03-05
  • 作者简介:

    刘琼(通信作者),女,1965出生,教授。主要研究方向为制造系统集成优化、低碳制造。

    E-mail: qiongliu@mail.hust.edu.cn

  • 基金资助:
    * 国家自然科学基金(51675206)、国家自然科学基金国际(地区)合作与交流(51561125002)和中央高校基本科研业务费专项资金(2016YXMS275)资助项目; 20160110收到初稿,20160911收到修改稿;

Integrated Optimization of Cutting Parameters and Scheduling for Reducing Carbon Emissions

LIU Qiong, ZHOU Yingdong, ZHANG Yi   

  1. State Key Laboratory of Digital Manufacturing Equipment & Technology, Huazhong University of Science and Technology, Wuhan 430074
  • Online:2017-03-05 Published:2017-03-05

摘要:

为更好地降低制造过程碳排放,克服以往研究将切削参数与调度分开优化而忽略了他们之间复杂关联关系的局限性,提出一个以制造过程碳排放和完工时间最小为优化目标的切削参数与调度集成优化模型,考虑切削参数对加工时间、刀具磨损、机床能耗的影响,继而影响到以完工时间和制造过程碳排放为优化目标的调度结果。针对集成优化模型中切削参数优化是连续优化问题而调度是离散优化问题的特点,改进了多目标万有引力搜索算法,在标准的万有引力搜索算法中加入交叉变异操作,使得切削参数在迭代的同时也能找出最优的调度排序。通过对实例结果的比较与分析,验证了所提集成优化模型在降低制造过程碳排放方面的有效性。

关键词: 调度, 切削参数优化, 万有引力搜索算法, 碳排放

Abstract:

In order to reduce carbon emissions in manufacturing processes and overcome the limitations of previous researches which dealt with cutting parameters optimization and scheduling optimization separately and ignored the complex relationship between cutting parameters and scheduling, an integrated optimization model of cutting parameters and scheduling is proposed to minimize the carbon emissions and completion time in the manufacturing process. The proposed model takes into account the impact of cutting parameters on makespan, cutting-tool wear and machine energy consumption, then further affects the result of low carbon orientated scheduling. Since the cutting parameters optimization is a continuous optimization problem but the scheduling optimization is a discrete optimization problem, an improved multi-objective gravitational search algorithm is designed to solve the integrated optimization problem. To optimize the cutting parameters and the scheduling at the same time, the proposed algorithm combines the crossover and mutation operators with the standard gravitation search algorithm. Finally, computational results verify the validity of the model.

Key words: cutting parameters optimization, gravitational search algorithm, scheduling, carbon emissions