Optimum tolerance synthesis of simple assemblies with nominal dimension selection using genetic algorithm
dc.contributor.author | Kumar, D. | |
dc.contributor.author | Ravindran, D. | |
dc.contributor.author | Kumar, M. | |
dc.contributor.author | Islam, Mohammad Nazrul | |
dc.date.accessioned | 2017-01-30T14:37:52Z | |
dc.date.available | 2017-01-30T14:37:52Z | |
dc.date.created | 2016-02-17T19:30:19Z | |
dc.date.issued | 2015 | |
dc.identifier.citation | Kumar, D. and Ravindran, D. and Kumar, M. and Islam, M.N. 2015. Optimum tolerance synthesis of simple assemblies with nominal dimension selection using genetic algorithm. Journal of Mechanical Engineering Science. 230 (19): pp. 3488–3508. | |
dc.identifier.uri | http://hdl.handle.net/20.500.11937/39872 | |
dc.identifier.doi | 10.1177/0954406215613366 | |
dc.description.abstract |
Optimum tolerance allocation plays a vital role in minimization of the direct manufacturing cost, and it is sensitive to tolerances related to variations in manufacturing processes. However, optimal adjustment of both nominal dimensions and selection of tolerances may further reduce assembly manufacturing cost and wastage of materials during processing. Most studies in existing literature focus on optimum tolerance allocation for the assemblies without considering nominal dimension selection. The method proposed in this work uses genetic algorithm techniques to allocate tolerances to assembly components, thereby minimizing costs. The component alternate nominal dimensions are predicted based on critical dimensions and its tolerances. The effectiveness of the developed algorithms demonstrated using randomly generated problems as well as sample problems taken from the literature. Test results are compared with those obtained using the Lagrange multiplier method. It is shown that by adjusting the nominal dimensions, the proposed method yields considerable savings in manufacturing costs. | |
dc.title | Optimum tolerance synthesis of simple assemblies with nominal dimension selection using genetic algorithm | |
dc.type | Journal Article | |
dcterms.source.volume | xx | |
dcterms.source.startPage | xx | |
dcterms.source.endPage | xx | |
dcterms.source.issn | 0022-2542 | |
dcterms.source.title | Journal of Mechanical Engineering Science | |
curtin.department | Department of Mechanical Engineering | |
curtin.accessStatus | Fulltext not available |
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