Abstract
: Received March 16 2013 Received in revised format May 9 2013 Accepted May 30 2013 Available online June 3 2013 This study presents optimization of performance characteristics in unidirectional glass fiber reinforced plastic composites using Taguchi method and Grey relational analysis. Performance characteristics such as surface roughness and material removal rate are optimized during rough cutting operation. Process parameters including tool nose radius, tool rake angle, feed rate, cutting speed, cutting environment and depth of cut are investigated using mixed L18 orthogonal array. Grey relation analysis is used to optimize the parameters and Principal Component Analysis is used to find the relative significance of performance characteristics. Depth of cut is the factor, which has great influence on surface roughness and material removal rate, followed by feed rate. The percentage contribution of depth of cut is 54.399% and feed rate is 5.355%.
Highlights
Environmental FRPs are an important class of materials in advanced structural applications due to their light weight, high modulus and specific strength
This paper investigates optimization problem of the cutting parameters in turning of unidirectional glass fiber reinforced plastic (UD-GFRP) composite rods
The work material used for the present investigation is unidirectional glass fiber reinforced plastic (UD-GFRP) composite rods
Summary
Environmental FRPs are an important class of materials in advanced structural applications due to their light weight, high modulus and specific strength. Grey relational analysis was used to optimize the multi performance characteristics to minimize the cutting force and surface roughness and maximize the tool life criteria. The major characteristics indexes for performance selected to evaluate the processes were tool life and metal removal rate and the corresponding cutting parameters were type of milling, spindle speed, feed per tooth and radial depth of cut and axial depth of cut. The principal component analysis was applied to evaluate the weighting values corresponding to various performance characteristics so that their relative importance could be properly and objectively described. The process parameters considered were electrolyte concentration, feed rate and applied voltage and were optimized with considerations of multiple performance characteristics including material removal rate, over cut, cylindricity error and surface roughness. Principal component analysis is used to find the weight corresponding to different performance characteristics
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