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Synthetic-X control charts optimized for in-control and out-of-control regions

机译:针对控制内和失控区域进行了优化的Synthetic-X控制图

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摘要

There are real industrial cases where small shifts in the quality of a productive process do not need to be detected, but, at the same time, it is necessary to maintain the performance of the control chart to detect large shifts which are considered important. In this paper the optimization, zero- and steady-state cases, of the synthetic-X control chart is studied (standard, side-sensitive, group runs and side-sensitive group runs versions) with the aim of not detecting shifts in a region of admissible shifts (in-control region) and, at the same time, being able to detect shifts considered important (out-of-control region). Genetic algorithms have been employed to solve this optimization problem and user-friendly software has been developed with the objective of helping users to select the best synthetic-X chart for the process. On the other hand, a comparison is made with the optimized EWMA chart for this in-control and out-of-control optimization problem.
机译:在实际的工业案例中,不需要检测生产过程质量的微小变化,但是同时,必须保持控制图的性能以检测被认为重要的较大变化。在本文中,研究了综合X控制图的最佳状态(零状态和稳态)(标准,侧向敏感,组运行和侧向敏感组运行版本),目的是不检测区域中的偏移允许的班次(控制范围内),同时能够检测到重要的班次(控制范围外)。遗传算法已被用来解决此优化问题,并且开发了用户友好的软件,其目的是帮助用户为该过程选择最佳的合成X图表。另一方面,针对此控制内和控制外优化问题,与优化的EWMA图进行了比较。

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