Application of a Fuzzy Inference System for the Optimization of Material Removal Rate and Multiple Surface Roughness Characteristics in the Machining of GFRP Polyester Composites

• Autorzy: Singh A. , Datta S. , Mahapatra S. S.

Identyfikatory

DOI

10.7494/dmms.2013.7.1.19

• Języki publikacji: EN

Abstrakty

EN

This paper presents a multi-objective extended optimization methodology applied in the machining of a randomly oriented GFRP rod. Design of Experiment (DOE) has been selected based on a L9 orthogonal array design with varying process control parameters like: spindle speed, feed rate and depth of cut. Multiple surface roughness parameters of the machined FRP product along with the Material Removal Rate (MRR) of the machining process have been optimized simultaneously. The Fuzzy Inference System (FIS) has been proposed for providing feasible means for the meaningful aggregation of multiple objective unctions into an equivalent single performance index (MPCI). This Multi-Performance Characteristic Index (MPCI) has been optimized using the Taguchi method. The approach adapted here is capable of overcoming limitations/assumptions of existing optimization methodologies available in the literature.

Słowa kluczowe

EN

GFRP; DoE; Fuzzy Inference System (FIS); Taguchi method

• Wydawca: AGH University of Science and Technology Press
• Czasopismo: Decision Making in Manufacturing and Services
• Rocznik: 2013
• Tom: Vol. 7, no. 1-2
• Strony: 19--42
• Opis fizyczny: Bibliogr. 36 poz., tab., rys., wykr.

Twórcy

autor

Singh A.

• Department of Mechanical Engineering National Institute of Technology, Rourkela-769008

autor

Datta S.

• Department of Mechanical Engineering National Institute of Technology, Rourkela-769008

autor

Mahapatra S. S.

• Department of Mechanical Engineering National Institute of Technology, Rourkela-769008

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