Optimization Formulation Based on Limited Data and RSM: An Approximation

被引:0
|
作者
Gadallah, Mohamed H. [1 ]
机构
[1] Cairo Univ, Inst Stat Studies & Res, Dept Operat Res, Cairo 12613, Egypt
关键词
Limited Data; RSM; Multi-objective optimization; Approximations;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
In this study, response surface models (RSMs) based on limited data are developed. Experimental cutting force data for the flat end milling process are employed to build these models. Four RSM models are developed in terms of process variables. The first model is used to build the mean cutting force. Similarly, the second, third and fourth models are used to build models for the variance, skewness and curtosis coefficients of the cutting forces. A bi-objective optimization procedure is developed and solved to generate a set of optimal process settings. An approximation scheme resulted in 6 possible objective combinations. The Pareto set of solutions (or part of) are generated for the six possible combinations. The merit of this study lies in the fact that response surfaces are built from limited data, often experienced in reality.
引用
收藏
页码:572 / 577
页数:6
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