新型双采样c图的表征与优化设计

Manuel J. Campuzano, A. Carrión, Jaime Mosquera
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引用次数: 1

摘要

本文提出了一种新的c控制图双采样方案(DS-c),旨在提高c控制图的性能或降低检测成本。推导了精确评估ARL和ASN所需的数学表达式。在此基础上,利用双目标遗传算法对DS-c方案进行优化设计。这种优化的目的是同时最小化错误概率类型II和ASN,保证错误概率类型i的期望水平。对c图的双重抽样(DS),固定参数(FP),变简单大小(VSS)和指数加权移动平均(EWMA)方案进行了性能比较。结果表明,与VSS和EWMA相比,DS-c方案的实施显著降低了失控ARL, ASN相对FP更低,ARL曲线更好。[收稿日期:2018年2月4日;录用日期:2019年2月1日]
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Characterisation and optimal design of a new double sampling c chart
This paper proposes a new double sampling scheme for c control chart (DS-c), which was designed to improve the performance of c chart or to reduce the inspection cost. The mathematical expression required to do an exact evaluation of ARL and ASN is deduced. Further, a bi-objective genetic algorithm is implemented to obtain the optimal design of the DS-c scheme. This optimisation is aimed to simultaneously minimising the error probability type II and the ASN, guaranteeing a desired level for the error probability type I. A performance comparison between the double sampling (DS), fixed parameters (FP), variable simple size (VSS) and exponential weighted moving average (EWMA) schemes for the c chart is carried out. The comparison shows that with the implementation of DS-c scheme is obtained a significant reduction of the out of control ARL with a lower ASN respect to FP and a better ARL profile than VSS and EWMA. [Received: 4 February 2018; Accepted: 1 February 2019]
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