Taguchi Optimization for Tool Wear Using Fuzzy Deduction

doi:10.1080/09720510.2011.10701590

CNU IR > College of Sustainable Environment and Recreation > Dept. of Applied Geoinformatics > Periodical Articles > Item 310902800/26973

Please use this identifier to cite or link to this item: https://ir.cnu.edu.tw/handle/310902800/26973

Title:	Taguchi Optimization for Tool Wear Using Fuzzy Deduction
Authors:	Lan, Tian-Syung Hsu, Kuei-Shu
Contributors:	應用空間資訊系
Keywords:	computer numerical control Taguchi method fuzzy deduction optimization tool wear
Date:	2011-09
Issue Date:	2013-10-14 14:57:43 (UTC+8)
Publisher:	Taylor & Francis
Abstract:	In this paper, four parameters (cutting depth, feed rate, speed, tool nose runoff) with three levels (low, medium, high) are considered to optimize the tool wear for CNC (computer numerical control) finish turning based on L 9(34) orthogonal array. Additionally, twenty- seven fuzzy control rules using trapezoid membership function with respective to seventeen linguistic grades for tool wear are constructed. Considering thirty input and eighty output intervals, the defuzzification using center of gravity is moreover completed. Through the Taguchi experiment, the optimum fuzzy deduction parameters can then be received. The confirmation experiment for optimum deduction parameters is furthermore performed on an ECOCA-3807 CNC lathe. It is shown that the tool wear ratio from the fuzzy deduction optimization parameters is significantly advanced comparing to that from the benchmark. This paper not only proposes a parametric deduction optimization scheme using orthogonal array, but also contributes the satisfactory fuzzy approach to the tool wear for CNC turning with profound insight.
Relation:	Journal of Statistics & Management Systems , 14(5), pp.885-898
Appears in Collections:	[Dept. of Applied Geoinformatics] Periodical Articles

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