Fuzzy Parametric Deduction for Material Removal Rate Optimization | Science Publications

Journal of Mathematics and Statistics

Tian-Syung Lan¹ 

关键词: Computer Numerical Control (CNC);    Taguchi method;    fuzzy deduction optimization;    Material Removal Rate (MRR);    CNC turning;    deduction parameters;    fuzzy linguistic;    fuzzy control rules;    control factors;    design parameters;    process parameters;   

DOI  :  10.3844/jmssp.2011.51.56

学科分类：社会科学、人文和艺术（综合）

来源: Science Publications

【 摘 要 】

Problem statement: A general optimization scheme without equipment operations for CNC(computer numerical control) finish turning is deemed to be necessarily developed. Approach: In thisstudy, four parameters (cutting depth, feed rate, speed, tool nose runoff) with three levels (low,medium, high) were considered to optimize the Material Removal Rate (MRR) based on L⁹(3⁴)orthogonal array. Twenty-seven fuzzy control rules using trapezoid membership function withrespective to seventeen linguistic grades for material removal rate were additionally constructed.Considering thirty input and eighty output intervals, the defuzzification using center of gravity wasmoreover completed. Through the Taguchi experiment, the optimum fuzzy deduction parameters couldthen be received. Results: The confirmation experiment for optimum deduction parameters wasfurthermore computed within the parameter ranges on an ECOCA-3807 CNC lathe. It is shown that thematerial removal rate from the fuzzy deduction optimization parameters was significantly advancedcomparing to that from the benchmark. Conclusions: This study not only proposed a parametricdeduction optimization scheme using orthogonal array, but also contributed the satisfactory fuzzyapproach to the material removal rates for CNC turning with profound insight.

【 授权许可】

Unknown