On the power and robustness of phase I nonparametric Shewhart-type charts using sequential normal scores

Control charts play a crucial role in industry, facilitating retrospective analysis of process data during its initial phase (Phase I) and monitoring its behavior over time once a chart is set (Phase II). This study introduces four novel Phase I nonparametric control charts based on combined forms of sequential normal scores. An adequate combination of characteristics from these statistics helps address early-stage data analysis challenges, including potential contamination and lack of normality. Their performance, evaluated by empirical alarm probability, was compared, and the preferred option was later tested against parametric approaches and available nonparametric alternatives across various practical scenarios. Previous Phase I charts have demonstrated difficulties handling specific out-of-control patterns and sample size restrictions. The results of this research indicate that the SNSmax statistic exhibits superior detection power compared to existing nonparametric methods, particularly when dealing with skewed distributions. Furthermore, it demonstrates robustness against isolated and certain types of sustained changes. This positions the SNSmax statistic as a reliable and powerful tool for quality assurance practitioners dealing with the assessment of independent batches of observations. [GRAPHICS]