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

Anuj Dixit, Supriyo Roy and Kaushik Kumar

International Journal of Process Management and Benchmarking, 2016, vol. 6, issue 4, 544-560

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. (search for similar items in EconPapers)
Date: 2016
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=79677 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijpmbe:v:6:y:2016:i:4:p:544-560

Access Statistics for this article

More articles in International Journal of Process Management and Benchmarking from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().