Title: Strategic process optimisation for tribological behaviour of silica gel reinforced aluminium composite material by neuro-grey modelling

Authors: Anuj Dixit; Supriyo Roy; Kaushik Kumar

Addresses: Department of Mechanical Engineering, Birla Institute of Technology, Mesra, Ranchi, 835215, India ' Department of Management, Birla Institute of Technology, Mesra, Ranchi, 835215, India ' Department of Mechanical Engineering, Birla Institute of Technology, Mesra, Ranchi, 835215, India

Abstract: Rotating and reciprocating parts requires low friction and high wear resistance for better life. Material like aluminium and its alloys, used largely in manufacturing/automotive sector, has the disadvantage of poor mechanical and tribological properties. In order to enhance the same the usage of aluminium-silicon composites are being rapid increased. In this work, silica gel reinforced aluminium composite was prepared to examine the tribological behavior. Plan of experiment was developed on the basis of three levels and three factors with Taguchi method initially. Proposed multi-objective optimisation problem was solved by neuro-grey modelling by using design including multiple attributes characterisation. The combined approach of ANN and GRA successfully overcomes the limitations of each other and provides with better solution. Experimental results show the efficacy of using such heuristics to highlight tribological properties of composite materials and any decision maker may opt for such strategy to make their operations more efficient.

Keywords: composite materials; operations strategy; tribological behaviour; process optimisation; heuristics; neuro-grey modelling; silica gel reinforced composites; tribology; aluminium composites; friction; wear resistance; Taguchi methods; multi-objective optimisation; ANNs; artificial neural networks; GRA; grey relational analysis.

DOI: 10.1504/IJPMB.2016.079677

International Journal of Process Management and Benchmarking, 2016 Vol.6 No.4, pp.544 - 560

Available online: 24 Sep 2016 *

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