机械加工
叠加原理
数学优化
粒子群优化
计算机科学
算法
工程类
机械工程
数学
数学分析
标识
DOI:10.1080/00207543.2020.1767313
摘要
Milling is one of the most frequently used machining operations in manufacturing industry. In order to remove cutting stocks economically and effectively, it is typically necessary to employ a multi-pass milling plan. Nevertheless, an optimisation practice is desirable in order to decide the most appropriate cutting plan (cutting speeds and feed rates) in each cutting pass to minimise the total machining time. In this study, optimisation of cutting conditions in multi-pass milling is achieved by utilising an improved version of a recently developed swarm intelligence based metaheuristic algorithm, which is known as a weighted superposition attraction algorithm. All of the cutting constraints are successfully satisfied and the results obtained from the proposed optimisation algorithm are compared with other optimisation approaches. The proposed optimisation algorithm is able to provide the best solutions for all test cases with reasonable computational time.
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