Abstract

A control chart has become a choice of quality practitioners for monitoring the output of industrial and production processes. It is a common practice to develop control charts under normality assumption or known distribution of the quality characteristic(s). These control charts are known as parametric charts. These charts may provide misleading results when the normality assumption of the process distribution is doubtful or unknown. In such situations, the nonparametric (NP) charts serve as an effective alternative for efficient monitoring of the process parameter(s). In this study, we have proposed a new NP double progressive mean chart based on sign statistic for detecting small shifts in the process location. The run-length (RL) properties of the proposed chart have been computed and compared with the existing competitor charts. We have used the most popular performance measure namely average RL (ARL) as an evaluation criterion. The comparisons revealed that the proposed chart performs better than its existing competitor’s charts. We have also considered a real-life data set related to a piston ring manufacturing process for the practical implementation of the proposed and existing charts.

摘要

控制图已成为质量从业者监控工业和生产过程输出的选择。在正态假设或已知的质量特性分布下开发控制图是一种常见的做法。这些控制图称为参数图。当过程分布的正态性假设可疑或未知时，这些图表可能会提供误导性结果。在这种情况下，非参数 (NP) 图可以作为有效监控过程参数的有效替代方案。在本研究中，我们提出了一种基于符号统计的新 NP 双渐进均值图，用于检测过程位置中的小变化。所提出的图表的游程 (RL) 属性已被计算并与现有的竞争对手图表进行了比较。我们使用最流行的性能指标，即平均 RL (ARL) 作为评估标准。比较表明，提议的图表比现有竞争对手的图表表现更好。我们还考虑了与活塞环制造过程相关的现实数据集，以实际实施拟议的和现有的图表。