机械加工
研磨
约束(计算机辅助设计)
遗传算法
机床
过程(计算)
选择(遗传算法)
职位(财务)
计算机科学
砂轮
工程类
数学优化
机械工程
数学
人工智能
机器学习
财务
经济
操作系统
作者
Nanyan Shen,Yang Wu,Jing Li,Tianqiang He,Yushun Lu,Yingjie Xu
标识
DOI:10.1080/00207543.2022.2045378
摘要
The complexity of composite grinding movement, the variety of machining features and available grinding wheels, and the changing working conditions pose a challenge to the rapid programming of safe and efficient composite grinding procedure. The procedure optimisation plays an important role in solving this difficult problem. Therefore, a procedure optimisation method is proposed for composite grinding based on a Digital Twin (DT) system, which takes procedure time as optimisation objective to achieve high efficiency and ensures process rationality and safety by constructing corresponding constraint conditions. Moreover, the actual working conditions mapped into the DT system, such as workpiece parameters, machining requirements, grinding wheel parameters and status, machine tool motion position, and so on, are obtained to update the parameters involved in the optimisation model. And thus, the proposed method has the ability to timely find the optimal procedure under changing working conditions. In addition, a combination algorithm based on genetic algorithm (GA) and dynamic programming is proposed, which greatly reduces the search space of GA and realises the two-class co-optimisation of grinding wheel selection and procedure. Finally, the case study verifies the effectiveness of the proposed method to reduce procedure time and the dynamic response ability to changing working conditions.
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