Energy consumption scheduling in flow shop based on ultra-low idle state of numerical control machine tools

被引：0
|
作者：
Wang L.-M. [1 ,2 ]
Liu X.-Y. [1 ,2 ]
Li F.-Y. [1 ,2 ]
Li J.-F. [1 ,2 ]
Kong L. [1 ,2 ]
机构：
[1] School of Mechanical Engineering, Shandong University, Ji'nan
[2] Key Laboratory of High Efficiency and Clean Mechanical Manufacture of Ministry of Education, Shandong University, Ji'nan
来源：
Kongzhi yu Juece/Control and Decision | 2021年 / 36卷 / 01期
关键词：
Energy efficiency; Flow shop; Genetic algorithm; Hybrid algorithm; Manufacturing for environment; Shop schedule;
D O I：
10.13195/j.kzyjc.2019.0433
中图分类号：
学科分类号：
摘要：
In order to reduce the energy consumption of the flow shop, an ultra-low idle state of the numerical control (NC) machine tools is introduced. Compared with the research on converting the idle state into the shutdown state, the ultra-low idle state can reduce the idle power without stopping the machine and avoiding frequent stopping the numerical control machine tools. A hybrid genetic algorithm based on process translation is proposed to solve the ternary scheduling problem in the flow shop considering the processing state, standby state and ultra-low idle state. The hybrid genetic algorithm defines different process neighborhood movement operations, and realizes the transformation of the NC machine tool from the standby state to the ultra-low idle state or off state. The hybrid genetic algorithm forms an active energy saving scheduling strategy and improves the optimization ability of the genetic algorithm to solve the flow shop energy consumption scheduling problem considering the ultra-low idle state. The experimental results show that the ultra-low idle state can effectively reduce energy consumption of the flow shop by 10%. The performance of the hybrid genetic algorithm is better than that of the genetic algorithm in solving flow shop energy saving scheduling problems considering the ultra-low idle state. Copyright ©2021 Control and Decision.
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页码：143 / 151
页数：8
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