An intelligent approach for multi-response optimisation of WEDM parameters
Bijaya Bijeta Nayak and
Siba Sankar Mahapatra
International Journal of Industrial and Systems Engineering, 2017, vol. 25, issue 2, 197-227
Abstract:
Usually, multi-criteria decision making methods are embedded with design of experiment (DOE) approach for handling the multi-response optimisation problems. However, uncertainties, impreciseness and arbitrary human judgement for weight assignment to criteria and alternatives result in inferior solutions. To overcome this limitation, an intelligent approach based on neuro-fuzzy system is proposed for converting multi-responses into single equivalent response. To illustrate the superiority of the proposed approach, a complex case study of taper cutting operation using wire electrical discharge machining (WEDM) process is considered. The effect of process parameters on equivalent response has been studied in detail and the relationship between the input parameters and responses are established by means of a nonlinear regression analysis resulting in a valid mathematical model. Finally, optimal parameter setting is obtained by recently proposed meta-heuristics like bat algorithm.
Keywords: multi-response performance characteristic index; MPCI; neuro-fuzzy systems; neural networks; fuzzy logic; taper cutting; angular error; bat algorithm; multi-response optimisation; WEDM; wire EDM; electrical discharge machining; electrico-discharge machining; process parameters; mathematical modelling; metaheuristics; multicriteria decision making; MCDM. (search for similar items in EconPapers)
Date: 2017
References: Add references at CitEc
Citations:
Downloads: (external link)
http://www.inderscience.com/link.php?id=81518 (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:ijisen:v:25:y:2017:i:2:p:197-227
Access Statistics for this article
More articles in International Journal of Industrial and Systems Engineering from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().