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A review: use of evolutionary algorithm for optimisation of machining parameters
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SYSNO ASEP 0561211 Document Type J - Journal Article R&D Document Type Journal Article Subsidiary J Článek ve WOS Title A review: use of evolutionary algorithm for optimisation of machining parameters Author(s) Zolpakar, N.A. (MY)
Yasak, M.F. (MY)
Pathak, Sunil (FZU-D) ORCID, RIDNumber of authors 3 Source Title International Journal of Advanced Manufacturing Technology. - : Springer - ISSN 0268-3768
Roč. 115, č. 1-2 (2021), s. 31-47Number of pages 17 s. Language eng - English Country GB - United Kingdom Keywords machining process ; machining parameter ; optimisation ; evolutionary algorithm Subject RIV BH - Optics, Masers, Lasers OECD category Optics (including laser optics and quantum optics) Method of publishing Limited access Institutional support FZU-D - RVO:68378271 UT WOS 000646520800002 EID SCOPUS 85105382233 DOI https://doi.org/10.1007/s00170-021-07155-7 Annotation This pap. reviews studies to achieve the desired outputs min. surface roughness,highest material removal rate,lowest product. cost,and the shortest product. time of machining proc. and various optimisation attempts in terms of varying parameters that affect the outcomes.The review deliberates the optimis. methods employed and analyses the performance discussing the relevant param. that must have been considered by past researchers.Most studies have been focusing on optimising convent. machining proc. such as turning,milling,and drilling.Optimis. works have been performed parametrically,experimentally,and numerically,where discrete variations of the param. are investigated,while others are remained constant.Lately,evolutionary algorithm,statistical approaches such as genetic algorithm,particle swarm optimisation,and cuckoo search algorithm have been utilised in simultaneous optimis. of the param. of the desired outputs and its potential in optimising mach. proc. is recognisable.
Workplace Institute of Physics Contact Kristina Potocká, potocka@fzu.cz, Tel.: 220 318 579 Year of Publishing 2023 Electronic address https://doi.org/10.1007/s00170-021-07155-7
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