Multi-objective optimization for optimum tolerance synthesis with process and machine selection using a genetic algorithm
|dc.contributor.author||Siva Kumar, M.|
|dc.contributor.author||Islam, Mohammad Nazrul|
|dc.identifier.citation||Geetha, 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.publisher||Springer U K|
|dc.subject||and manufacturing processes|
|dc.subject||tolerance cost models|
|dc.title||Multi-objective optimization for optimum tolerance synthesis with process and machine selection using a genetic algorithm|
|dcterms.source.title||International Journal of Advanced Manufacturing Technology|
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