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Growing Science » International Journal of Industrial Engineering Computations » Machining performance of aluminium matrix composite and use of WPCA based Taguchi technique for multiple response optimization

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International Journal of Industrial Engineering Computations

ISSN 1923-2934 (Online) - ISSN 1923-2926 (Print)
Quarterly Publication
Volume 9 Issue 4 pp. 551-564 , 2018

Machining performance of aluminium matrix composite and use of WPCA based Taguchi technique for multiple response optimization Pages 551-564 Right click to download the paper Download PDF

Authors: Diptikanta Das, Purna Chandra Mishra, Saranjit Singh, Anil Kumar Chaubey, Bharat Chandra Routara

DOI: 10.5267/j.ijiec.2017.10.001

Keywords: Aluminium matrix composite, Turning, Weighted principal component analysis, Taguchi

Abstract: Silicon carbide (SiC) particulate impregnated Al 7075 matrix composite was fabricated by stir casting method and then heat treated to T6 condition. It was then machined with multiple layer of TiN coated tungsten carbide (WC) inserts in dry environment and pollution free Spray Impingement Cooling (SIC) environment to compare the machining performance. SIC environment presented better machining performance with respect to cutting tool temperature (T), average roughness of the machined surface (Ra) and tool flank wear (VBc). Quadratic response surface models were developed by computing the experimental data. Weighted Principal Component Analysis (WPCA) based Taguchi technique was adopted to optimize the multiple responses simultaneously, which resulted 40 m/min of cutting speed (V), 0.05 mm/rev of feed (f) and 0.2 mm of cutting depth (d) was the optimal combination of process parameters.

How to cite this paper
Das, D., Mishra, P., Singh, S., Chaubey, A & Routara, B. (2018). Machining performance of aluminium matrix composite and use of WPCA based Taguchi technique for multiple response optimization.International Journal of Industrial Engineering Computations , 9(4), 551-564.

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Journal: International Journal of Industrial Engineering Computations | Year: 2018 | Volume: 9 | Issue: 4 | Views: 2025 | Reviews: 0

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