Evolutionary algorithms on diamond grinding of SiC. (19th January 2011)

• Record Type: Journal Article
• Authors: Lee, T.S.; Ting, T.O.; Rao, P.V.; Venkatesh, V.C.; , Y.J. Lin
• Is Part Of: International journal of precision technology. Volume 2:Number 1(2011)
• Page Start: 1
• Page End: 11
• Publication Date: 2011-01-19
• Subjects: ceramics grinding -- constrained optimisation -- particle swarm optimisation -- PSO -- differential evolution -- genetic algorithms -- GAs -- silicon carbide -- diamond grinding -- material removal rate -- MRR -- surface quality; Production engineering -- Periodicals; Mechanical engineering -- Periodicals; 670.5
• Languages: English
• ISSNs: 1755-2060

Abstract

Optimisation is needed in order to achieve better product quality, high productivity and low cost. Efficient grinding involves the optimal selection of operating parameters to maximise the material removal rate (MRR) while maintaining the required surface finish, and minimising surface damage. Three prominent evolutionary algorithms were used. They are particle Swarm optimisation (PSO), differential evolution (DE) and genetic algorithm (GA). Novel methodologies for tuning PSO and DE for optimising grinding process have been proposed. Validation of optimum MRR obtained from these algorithms has been done and the MRR values obtained from the proposed methodologies are encouraging.