Multi-objective optimisation of CNC milling process using Grey-Taguchi method in machining of GFRP composites. Issue 2 (5th August 2014)

• Record Type: Journal Article
• Authors: Naresh, N.; Jenarthanan, M.P.; Hari Prakash, R.
• Is Part Of: Multidiscipline modeling in materials and structures. Volume 10:Issue 2(2014)
• Page Start: 265
• Page End: 275
• Publication Date: 2014-08-05
• Subjects: Materials -- Mathematical models -- Periodicals; Engineering -- Mathematical models -- Periodicals; 620.11015118
• DOI: 10.1108/MMMS-06-2013-0042
• Languages: English
• ISSNs: 1573-6105

Abstract

<abstract> <title> <x content-type="archive" xml:space="preserve">Abstract</x> </title> <sec> <title content-type="abstract-heading">Purpose</title> <p> – In milling process the surface roughness and delamination are the most important performance characteristics, which are influenced by many factors like fibre orientation angle, helix angle, feed rate and spindle speed. The selection of these parameters at optimum level plays a vital role in getting minimum surface roughness and delamination factor. The purpose of this paper is to present multi-objective optimisation of Computer Numerical Control milling parameters using Grey-Taguchi method to get minimum surface roughness and delamination factor in machining of glass fibre reinforced plastics (GFRP) composites used in automotive, aircraft and manufacture of space ships. </p> </sec> <sec> <title content-type="abstract-heading">Design/methodology/approach</title> <p> – The experiments are designed and conducted based on Taguchi's L<sub>27</sub> orthogonal array by taking fibre orientation angle, helix angle, feed rate and spindle speed at three levels and responses are surface roughness and delamination factor. Taguchi's signal-to-noise (S/N) ratio are determined based on their performance characteristics. A Grey relation grade is obtained by using S/N ratio. Based on Grey relational grade value, optimum levels of parameters have been identified by using response table and response graph. </p> </sec> <sec> <title content-type="abstract-heading">Findings</title> <p> – Optimum levels of parameters for GFRP composites have been identified by using response table and response graph and the significant contributions of controlling parameters are estimated using analysis of variance. </p> </sec> <sec> <title content-type="abstract-heading">Originality/value</title> <p> – The combined effect of fibre orientation angle and helix angle during milling of GFRP composites using Grey relational analysis has not been previously attempted for analysis.</p> </sec> </abstract>