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  • ISSN：0577-6686
机械工程学报

机械工程学报 ›› 2016, Vol. 52 ›› Issue (19): 168-179.doi: 10.3901/JME.2016.19.168

• 数字化设计与制造 • 上一篇    下一篇

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一种面向机械车间柔性工艺路线的加工任务节能调度方法*

何彦1, 王乐祥1, 李育锋1, 王禹林2   

  1. 1. 重庆大学机械传动国家重点实验室 重庆 400030；
    2. 南京理工大学机械工程学院 南京 210094
  • 出版日期:2016-10-05 发布日期:2016-10-05
  • 作者简介:

    作者简介：何彦(通信作者)，女，1981年出生，博士，教授，博士研究生导师。主要研究方向为绿色制造，制造系统工程，现代工艺及装备。

    E-mail：heyan@cqu.edu.cn

    E-mail：wanglexiang@cqu.edu.cn

    E-mail：liyufengcqu@cqu.edu.cn

    E-mail：wyl_sjtu@126.com

  • 基金资助:
    * 国家自然科学基金(51575072）、重庆市基础与前沿研究计划(cstc2015jcyjBX0088，cstc2013jcyjA70014)、江苏省“六大人才高峰”(2014-; ZBZZ-006)和南京理工大学“卓越计划”“紫金之星”(2015-zijin-07)资助项目; 20151018收到初稿，20160627收到修改稿;

A Scheduling Method for Reducing Energy Consumption of Machining Job Shops Considering the Flexible Process Plan

HE Yan1, WANG Lexiang1, LI Yufeng1, WANG Yulin2   

  1. 1. State Key Laboratory of Mechanical Transmission， Chongqing University， Chongqing 400030
    , 2. School of Mechanical Engineering， Nanjing University of Science and Technology， Nanjing 210094
  • Online:2016-10-05 Published:2016-10-05

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摘要：

大量研究表明机械车间消耗了大量能量，因此降低机械车间的能耗是实现可持续制造的策略之一。现有机械车间节能调度研究主要针对给定的或者具有部分柔性的工艺路线，缺乏对机械车间任务工艺路线多柔性的节能调度研究。针对机械车间任务柔性工艺路线对机械车间调度能耗的影响特性，提出一种面向机械车间柔性工艺路线的节能调度方法。首先，分析了面向机械车间柔性工艺路线的加工任务调度的能耗特性;基于此，构建了节能调度模型，该模型是以任务加工总能耗、加工完成时间、机床负载为目标。进一步提出了一种改进的Q学习算法对该模型进行求解获得其Pareto解。最后通过案例验证了提出模型的节能效果及算法的可行性。

关键词: Pareto多目标优化, 改进Q学习算法, 能耗, 柔性工艺路线

Abstract:

：Numerous studies indicated that amount of energy is consumed by machining job shops. Hence reducing the energy consumption of machining job shops is one of the strategies for sustainable manufacturing. The existing researches of scheduling method considering energy consumption for machining job shops focus on constant or partly flexible process plan, and the study considering multi flexibilities of process plan is scarce. A scheduling method for reducing energy consumption of machining job shops considering the flexible process plan is proposed which considers the influence that flexible process plan have on energy consumption. Based on the analysis of energy consumption characteristics of flexible process plan-oriented task scheduling, a mathematical model of task scheduling problem is formulated. The optimal objects of the model include total energy consumption of task, makespan and workload of machine. The Q-learning algorithm is improved to find the Pareto optimal solution of the multi-objective mathematical model. Finally, the experimental results indicate that the proposed model has energy saving potential and improved Q-learning algorithm is feasible.

Key words: energy consumption, improved Q-learning algorithm, pareto multi-object optimization, flexible process plan

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