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dc.contributor.authorGeetha, K.
dc.contributor.authorRavindran, D.
dc.contributor.authorSiva Kumar, M.
dc.contributor.authorIslam, Mohammad Nazrul
dc.identifier.citationGeetha, K. and Ravindran, D. and Siva Kumar, M. and Islam, M.N. 2012. Multi-objective optimization for optimum tolerance synthesis with process and machine selection using a genetic algorithm. International Journal of Advanced Manufacturing Technology. 67 (9-12): pp. 2439-2457.

This paper presents a new approach to the tolerance synthesis of the component parts of assemblies by simultaneously optimizing three manufacturing parameters: manufacturing cost, including tolerance cost and quality loss cost; machining time; and machine overhead/idle time cost. A methodology has been developed using the Genetic Algorithm (GA) technique to solve this multi-objective optimization problem. The effectiveness of the proposed methodology has been demonstrated by solving a wheel mounting assembly problem consisting of five components, two subassemblies, two critical dimensions, two functional tolerances, and eight operations. Significant cost saving can be achieved by employing this methodology.

dc.publisherSpringer U K
dc.subjectand manufacturing processes
dc.subjecttolerance cost models
dc.subjectoptimization techniques
dc.subjecttolerance synthesis
dc.titleMulti-objective optimization for optimum tolerance synthesis with process and machine selection using a genetic algorithm
dc.typeJournal Article
dcterms.source.titleInternational Journal of Advanced Manufacturing Technology

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curtin.accessStatusOpen access

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