Optimization for cutting force and material removal rate in milling thin-walled parts

被引：0
|
作者：
Qu, Sheng [1 ,2 ]
Zhang, Mingqin [1 ]
机构：
[1] Shandong Jianzhu Univ, Sch Mech Engn, Jinan 250101, Peoples R China
[2] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
来源：
PROCEEDINGS OF THE 2016 4TH INTERNATIONAL CONFERENCE ON ADVANCED MATERIALS AND INFORMATION TECHNOLOGY PROCESSING (AMITP 2016) | 2016年 / 60卷
关键词：
Thin-walled parts; Machining parameters; Optimization; NSGA-II; GENETIC ALGORITHM; NEURAL-NETWORK; PREDICTION; PARAMETERS;
D O I：
暂无
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
Conservative milling parameters are usually adopted in actual milling. This paper presents an optimization procedure to determine the optimum combinations of machining parameters for minimal cutting force and maximal machining efficiency. The regression model for cutting force is developed as objective function according to experimental results. The objectives under investigation in this study are cutting force and material removal rate subjected to constraints conditions. A non-dominated sorting genetic algorithm (NSGA-II) is then adopted to solve this multi-objective optimization problem. The optimized combinations of machining parameters are achieved by the Pareto optimal solutions.
引用
收藏
页码：461 / 465
页数：5
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