机器人
计算机科学
背景(考古学)
汽车工业
能源消耗
整数规划
帕累托原理
约束(计算机辅助设计)
工业机器人
能量(信号处理)
数学优化
模拟
实时计算
工业工程
人工智能
算法
统计
数学
工程类
机械工程
古生物学
生态学
生物
航空航天工程
作者
Amir Nourmohammadi,Masood Fathi,Taha Arbaoui,Ilhem Slama
标识
DOI:10.1016/j.procs.2024.01.126
摘要
The recent Industry 4.0 trend, followed by the technological advancement of collaborative robots, has convinced many industries to shift towards semi-automated assembly lines with human-robot collaboration (HRC). In the HRC environment, robot agility can support human skill upon efficiently balancing tasks among the stations and operators. On the other hand, the robot energy consumption in today's energy crisis area demands that tasks be performed with as little energy utilization as possible by robots. In this context, the cycle time (CT) and total energy cost (TEC) of robots are among two conflicting objectives. Thus, this study balances HRC lines where a trade-off between CT and TEC of robots is sought. A mixed-integer linear programming model is proposed to formulate the problem. In addition, a multi-objective optimization approach based on ε-constraint is developed to address a case study from the automotive industry and a set of generated test problems. The computational results show that promising Pareto solutions in terms of CT and TEC can be obtained using the proposed approach.
科研通智能强力驱动
Strongly Powered by AbleSci AI