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Simultaneous optimal design of parameters and tolerance of bearing locations for high-speed machine tools using a genetic algorithm and Monte Carlo simulation method

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Abstract

In designing a high-speed motorized spindle-bearing system, bearing locations and tolerances must be designed optimally based on the concepts of motorized spindle shaft and bearings, and the number of bearings has been determined. Under certain constraints, a mathematical model of the optimization problem is developed to minimize total costs, which consist of the tolerance cost and expected value of the quality-loss cost. Therefore, we propose an optimization method that integrates the genetic algorithm and Monte Carlo Simulation to search simultaneously for the optimal values of nominal values and tolerance of location of bearings. To verify the effectiveness of the proposed method, this study investigates a real design example of bearing location for a high-speed motorized spindle-bearing system. Weights-related sensitivity analyses are also performed. The results of sensitivity study confirm that a higher tolerance cost results in a greater optimal tolerance design value that will be required.

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  1. Department of Industrial Engineering and Systems Management, Feng Chia University, 100, Wenhwa Rd., Seatwen, Taichung, Taiwan, 40724

    Chi-Wei Lin

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  1. Chi-Wei Lin
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Correspondence to Chi-Wei Lin.

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Lin, CW. Simultaneous optimal design of parameters and tolerance of bearing locations for high-speed machine tools using a genetic algorithm and Monte Carlo simulation method. Int. J. Precis. Eng. Manuf. 13, 1983–1988 (2012). https://doi.org/10.1007/s12541-012-0261-6

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  • DOI: https://doi.org/10.1007/s12541-012-0261-6

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