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Nonparametric progressive sign chart for monitoring process location based on individual data
Quality Technology and Quantitative Management ( IF 2.8 ) Pub Date : 2020-10-15 , DOI: 10.1080/16843703.2020.1827726
Zameer Abbas 1 , Hafiz Zafar Nazir 2 , Muhammad Abid 3 , Noureen Akhtar 2 , Muhammad Riaz 4
Affiliation  

ABSTRACT

Statistical process control (SPC) plays a vital role in the maintenances and improvements of quality outputs in manufacturing, industrial and service production processes. Control chart is an important SPC tool, used to detect noises and to improve process performance. When the underlying process distribution lacks the assumption of normality, nonparametric (NP) control charts become essential and particularly are useful because their in-control (IC) run length properties remain the same for every continuous distribution. This article develops the NP progressive mean sign (NPPM-SN) chart for monitoring the process target through 100% inspection by taking individual measurements from the process. The performance of the proposed NPPM-SN chart is examined under zero-state and steady-state scenarios. The IC and out-of-control run length properties of the proposed control chart are evaluated using Monte Carlo simulation. The proposed NPPM-SN chart is compared with traditional exponentially weighted moving average (EWMA), nonparametric EWMA sign (NPEWMA-SN) and traditional progressive mean (PM) control charts based on individual measurements using average run length and some other characteristics of the run-length distribution. The proposed NPPM-SN chart is found more robust (for all distributions) and efficient (for skewed distributions) as compared to its competitors. Along with a real-life example related to high voltage power supply, a simulated data example is also presented for the implementation of the proposed NPPM-SN chart.



中文翻译:

非参数渐进式符号图,用于基于单个数据监视过程位置

摘要

统计过程控制(SPC)在维护,改进制造,工业和服务生产过程中的质量输出中起着至关重要的作用。控制图是重要的SPC工具,用于检测噪声和改善过程性能。当基础过程分布缺乏正态性假设时,非参数(NP)控制图将变得至关重要,因为它们的控制中(IC)运行长度属性对于每个连续分布都保持不变,因此特别有用。本文开发了NP逐步平均符号(NPPM-SN)图表,通过对过程进行单独测量来通过100%检查来监视过程目标。建议的NPPM-SN图表的性能在零状态和稳态情况下进行了检查。使用蒙特卡洛仿真评估了建议控制图的IC和失控运行长度属性。拟议的NPPM-SN图表与传统的指数加权移动平均值(EWMA),非参数EWMA符号(NPEWMA-SN)和传统的渐进平均值(PM)控制图进行了比较,这些图表是根据使用平均运行长度和运行其他特征的单独测量得出的长度分布。与竞争对手相比,建议的NPPM-SN图表更健壮(针对所有发行版)和有效(针对偏斜的发行版)。连同与高压电源相关的实际示例,还提供了一个模拟数据示例,用于实现建议的NPPM-SN图。拟议的NPPM-SN图表与传统的指数加权移动平均值(EWMA),非参数EWMA符号(NPEWMA-SN)和传统的渐进平均值(PM)控制图进行了比较,这些图表是根据使用平均运行长度和运行其他特征的单独测量得出的长度分布。与竞争对手相比,建议的NPPM-SN图表更健壮(针对所有发行版)和有效(针对偏斜的发行版)。连同与高压电源有关的实际示例,还提供了一个模拟数据示例,用于实现所提出的NPPM-SN图。拟议的NPPM-SN图表与传统的指数加权移动平均值(EWMA),非参数EWMA符号(NPEWMA-SN)和传统的渐进平均值(PM)控制图进行了比较,这些图表是根据使用平均运行长度和运行其他特征的单独测量得出的长度分布。与竞争对手相比,建议的NPPM-SN图表更健壮(针对所有发行版)和有效(针对偏斜的发行版)。连同与高压电源有关的实际示例,还提供了一个模拟数据示例,用于实现所提出的NPPM-SN图。非参数EWMA符号(NPEWMA-SN)和传统的渐进均值(PM)控制图基于使用平均游程长度和游程长度分布的某些其他特征的单个测量结果。与竞争对手相比,建议的NPPM-SN图表更加健壮(针对所有发行版)和有效(针对偏斜的发行版)。连同与高压电源有关的实际示例,还提供了一个模拟数据示例,用于实现所提出的NPPM-SN图。非参数EWMA符号(NPEWMA-SN)和传统的渐进均值(PM)控制图基于使用平均游程长度和游程长度分布的某些其他特征的单个测量结果。与竞争对手相比,建议的NPPM-SN图表更健壮(针对所有发行版)和有效(针对偏斜的发行版)。连同与高压电源有关的实际示例,还提供了一个模拟数据示例,用于实现所提出的NPPM-SN图。

更新日期:2020-10-15
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