首页|基于模拟退火算法的人机协同装配线平衡问题研究

基于模拟退火算法的人机协同装配线平衡问题研究

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作为一种新兴的智能制造趋势，将协作机器人引入装配线，与工人以人机协同方式进行装配，正受到越来越多的重视和实践。人机协同装配线的特点在于工人和机器人可以在同一工位中独立执行、并行执行或协作执行装配任务，从而提高传统装配线的生产效率。以最小化节拍时间为优化目标，对人机协同装配线平衡问题开展研究。首先，设计节拍时间下限、上限和初始解的加强策略，并基于已有的人机协同装配线平衡问题模型，构建一个新的增强的混合整数规划模型;其次，设计一类改进的模拟退火算法，使用多种工位完工时间评估方法，实现对问题的高效求解;此外，通过大量的计算实验，验证所提模型和算法的有效性和适用性;最后，对相关参数开展敏感性分析，为制造企业引入协作机器人开展人机协同装配提供管理启示和实践参考。
Research on the human-robot collaborative assembly line balancing problem based on simulated annealing algorithm
As an emerging trend of intelligent manufacturing,collaborative robots are recently introduced and implemented in the assembly line systems with human-robot collaborative approach,which has received increasing attention and practice.In such system,workers and robots can perform tasks separately,simultaneously,or collaboratively at each station,which can significantly improve the efficiency of the production line.This study addresses an assembly line balancing problem with human-robot collaboration(ALBP-HRC)to minimize the cycle time.We first propose multiple enhancement strategies,including lower bound,upper bound and initial solution.Meanwhile,based on the existing ALBP-HRC model,we formulate an enhanced mixed integer programming model.Secondly,we present an improved simulated annealing algorithm,using multiple completion time estimation procedures for stations to solve the problem efficiently.Moreover,extensive experiments are conducted,and the results verify the effectiveness and applicability of the methods.Finally,we investigate sensitivity analysis on different parameters,revealing the managerial insights and practical references for enterprises implementing human-robot collaborative assembly line.

collaborative robotshuman-robot collaborationassembly line balancingenhancement strategiesenhanced mixed integer programmingsimulated annealing algorithm

毛照昉、王威、方侃、黄典

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天津大学管理与经济学部,天津 300072

天津大学新媒体与传播学院,天津 300072

协作机器人 人机协同 装配线平衡问题 加强策略 增强的混合整数规划模型 模拟退火算法

国家自然科学基金项目国家自然科学基金项目国家自然科学基金项目科技部创新方法专项项目天津市哲学社会科学规划项目

9216720672361137004722310052020IM030300TJGL21-016

2024

10.13195/j.kzyjc.2023.1068

控制与决策
东北大学

控制与决策

CSTPCD北大核心
影响因子：1.227
ISSN：1001-0920
年,卷(期)：2024.39(10)