The Sequential Signed‐Rank Test Control Chart for Process Location

ABSTRACT This paper introduces a novel nonparametric control chart for monitoring process location using sequential sampling. The proposed chart employs the standardized sequential Wilcoxon signed‐rank statistic as its control statistic. Through an extensive simulation study, data‐driven approximate relationships between the chart parameters and their in‐control statistical performance measures are derived. These relationships are demonstrably accurate and facilitate the chart's design in practice. The statistical performance of the proposed chart is numerically compared with competing charts from the existing literature. Results show that the proposed chart significantly outperforms all competing signed‐rank statistic‐based charts in detecting a median shift of any size. Furthermore, it surpasses the SPRT sign chart for location, generally requiring fewer observations on average to detect location shifts of all sizes. A real‐world data example illustrates the practical application of the proposed chart.

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Publication Details

Journal
Quality and Reliability Engineering International
Published
2025-09-25
DOI
https://doi.org/10.1002/qre.70082
Citations
1
Primary Topic
Advanced Statistical Process Monitoring
Type
article
Field-Weighted Citation Impact
1.40
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article

The Sequential Signed‐Rank Test Control Chart for Process Location

Shashibhushan B. Mahadik, Michael B. C. Khoo, Ravindra E. Deore, Shubham R. Shinde
1 citations
Quality and Reliability Engineering International
Advanced Statistical Process Monitoring
1.40
article

The Sequential Signed‐Rank Test Control Chart for Process Location

Shashibhushan B. Mahadik, Michael B. C. Khoo, Ravindra E. Deore, Shubham R. Shinde
article en
1 citations

Abstract

ABSTRACT This paper introduces a novel nonparametric control chart for monitoring process location using sequential sampling. The proposed chart employs the standardized sequential Wilcoxon signed‐rank statistic as its control statistic. Through an extensive simulation study, data‐driven approximate relationships between the chart parameters and their in‐control statistical performance measures are derived. These relationships are demonstrably accurate and facilitate the chart's design in practice. The statistical performance of the proposed chart is numerically compared with competing charts from the existing literature. Results show that the proposed chart significantly outperforms all competing signed‐rank statistic‐based charts in detecting a median shift of any size. Furthermore, it surpasses the SPRT sign chart for location, generally requiring fewer observations on average to detect location shifts of all sizes. A real‐world data example illustrates the practical application of the proposed chart.

Quality and Reliability Engineering InternationalVol. 42(1)
Universiti Sains Malaysia (MY), Shivaji University (IN)
Openalex Percentile: Top 13%
Advanced Statistical Process Monitoring
1.40
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