应用数学规划模型求解过程能力指标S_(pk)置信区间

Q3 Engineering
Ching-Hsin Wang, M. Tseng, K. Tan, Kun-Tzu Yu
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引用次数: 12

摘要

通过将指标S_(pk)转化为μ_y = (μ - T)和σ_y =σ/d的函数,构造μ_y和σ_y联合置信区间的可行域,以S_(pk)(μ_y, σ_y)为目标函数,建立了确定S_(pk)置信区间的数学规划模型,克服了以往过程能力指标点估计和区间估计计算的不足。然后通过蒙特卡罗仿真对覆盖率进行了分析,验证了所提方法的准确性。我们的结果证明了所提出的评估模型使用石英晶体振荡器的有效性,石英晶体振荡器是通信设备中常用的无源元件。该方法消除了统计方法的复杂性,结果是对误差具有较强鲁棒性的最优值。该模型也可应用于其他复杂工艺评价指标,为制造商提供了一种高效、便捷的工艺能力评价方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of a Mathematical Programming Model to Solve the Confidence Interval of Process Capability Index S_(pk)
This study developed a mathematical programming model to determine confidence intervals of S_(pk) by converting index S_(pk) into a function of μ_y = (μ - T ) and σ_y =σ/d, constructing the feasible region of joint confidence interval with μ_y and σ_y, and then regarding S_(pk)(μ_y, σ_y) as an objective function, to overcome the shortage of point-estimate and interval-estimate calculations of the past process capability index. Then, Monte Carlo simulation was used to analyze the coverage rate in order to validate the accuracy of the proposed method. Our results demonstrate the efficacy of the proposed evaluation model using quartz crystal oscillators, a passive component commonly used in communication devices. The proposed method eliminates the complex complexity of statistical methods, and the results are optimal values largely robust to errors. The proposed model can also be applied to other complex process evaluation indices, thereby presenting manufacturers with an efficient and convenient method for the assessment of process capability.
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来源期刊
International Journal of Information and Management Sciences
International Journal of Information and Management Sciences Engineering-Industrial and Manufacturing Engineering
CiteScore
0.90
自引率
0.00%
发文量
0
期刊介绍: - Information Management - Management Sciences - Operation Research - Decision Theory - System Theory - Statistics - Business Administration - Finance - Numerical computations - Statistical simulations - Decision support system - Expert system - Knowledge-based systems - Artificial intelligence
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