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Multi-objective optimization for optimum tolerance synthesis with process and machine selection using a genetic algorithm

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Abstract

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 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.

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Authors and Affiliations

  1. Raja College of Engineering and Technology, Madurai, Tamilnadu, 625 020, India

    K. Geetha

  2. National Engineering College, K.R. Nagar, Kovilpatti, 628 503, Tamilnadu, India

    D. Ravindran

  3. Sree Sowdambika College of Engineering, Chettikurichi, 626 134, Aruppukottai, Tamilnadu, India

    M. Siva Kumar

  4. Curtin University, GPO Box U 1987, Perth, WA, 6845, Australia

    M. N. Islam

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  1. K. Geetha
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  2. D. Ravindran
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  3. M. Siva Kumar
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  4. M. N. Islam
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Correspondence to K. Geetha.

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Geetha, K., Ravindran, D., Kumar, M.S. et al. Multi-objective optimization for optimum tolerance synthesis with process and machine selection using a genetic algorithm. Int J Adv Manuf Technol 67, 2439–2457 (2013). https://doi.org/10.1007/s00170-012-4662-6

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  • DOI: https://doi.org/10.1007/s00170-012-4662-6

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