基于局部搜索NSGA-Ⅱ算法的机械产品分组选择装配方法

doi:10.3969/j.issn.1004-132X.2022.09.015

中国机械工程 ›› 2022, Vol. 33 ›› Issue (09): 1127-1133.DOI: 10.3969/j.issn.1004-132X.2022.09.015

基于局部搜索NSGA-Ⅱ算法的机械产品分组选择装配方法

李好¹, 徐志玲¹, 徐勇², 赵有为³

1. 中国计量大学质量与安全工程学院, 杭州, 310018;
2. 台州方圆质检有限公司, 台州, 318000;
3. 浙江天马轴承集团有限公司, 湖州, 313200

收稿日期:2021-07-30 出版日期:2022-05-10 发布日期:2022-05-17
通讯作者: 徐志玲(通信作者),女,1966年生,教授。研究方向为质量控制。E-mail:xuzhiling@cjlu.edu.cn。
作者简介:李好,男,1996年生,硕士研究生。研究方向为装配质量与质量控制。E-mail:leeee_lip@163.com。
基金资助:
浙江省公益技术研究计划(LGG20FD30006)

Grouping Selective Assembly Method for Mechanical Products Based on Local Search Strategy for NSGA-Ⅱ

LI Hao¹, XU Zhiling¹, XU Yong², ZHAO Youwei³

1. College of Quality & Safety Engineering, China Jiliang University, Hangzhou, 310018;
2. Taizhou Fangyuan Quality Inspection Co., Ltd., Taizhou, Zhejiang, 318000;
3. Zhejiang Tianma Bearing Group Co., Ltd., Huzhou, Zhejiang, 313200

Received:2021-07-30 Online:2022-05-10 Published:2022-05-17

摘要/Abstract

摘要： 针对批量机械产品多目标要求下的分组选择装配问题，提出一种基于局部搜索的第二代非支配排序遗传算法(NSGA-Ⅱ)的分组选择装配方法。以装配精度和装配成功率为优化目标，构建基于质量损失函数和尺寸偏差的综合选择装配模型。采用浮点数和整数相结合的编码方式来描述分组选择装配方案，为获得分组选择装配方案中每个产品的封闭环实际尺寸，设计了一种解码方式。为了提高算法局部搜索能力，利用NSGA-Ⅱ混合模拟退火算法对分组选择装配问题进行求解，将成绩标量函数作为个体评价规则，实现了多目标要求下选择装配分组方案的优化。以某深沟球轴承的装配为例，验证了该方法的可行性和有效性。

关键词: 选择装配, 装配质量, 分组方案, 多目标优化

Abstract: Aiming at the grouping selective assembly problems under multi-objective requirements for mass-produced mechanical products, a method was proposed based on local search strategy for non-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ). Taking the assembly precision and assembly yield as optimization objectives, a comprehensive selective assembly model was established based on quality loss function and dimensional deviation. A combination of floating-point coding and integer coding was used to describe grouping selective assembly scheme. A decoding method was designed to obtain the actual size of the closed loop of each products in grouping selective assembly scheme. The achievement scalarizing function was taken as evaluation rule of the individuals, and the grouping selective assembly problem was solved by NSGA-Ⅱ hybrid simulated annealing algorithm, which improved the local search ability and realized the optimization of multi-objective assembly. The assembly of a deep groove ball bearing was used to verify the feasibility and effectiveness of the method herein.

Key words: selective assembly, assembly quality, grouping scheme, multi-objective optimization

中图分类号:

TP391.9

李好, 徐志玲, 徐勇, 赵有为. 基于局部搜索NSGA-Ⅱ算法的机械产品分组选择装配方法[J]. 中国机械工程, 2022, 33(09): 1127-1133.

LI Hao, XU Zhiling, XU Yong, ZHAO Youwei. Grouping Selective Assembly Method for Mechanical Products Based on Local Search Strategy for NSGA-Ⅱ[J]. China Mechanical Engineering, 2022, 33(09): 1127-1133.

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基于局部搜索NSGA-Ⅱ算法的机械产品分组选择装配方法

Grouping Selective Assembly Method for Mechanical Products Based on Local Search Strategy for NSGA-Ⅱ

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