Development of a Repetitive Control Chart for Monitoring Processes with Dagum-Distributed Data

This paper presents a repetitive control chart designed for monitoring processes where the quality characteristic follows a Dagum distribution a flexible, skewed distribution often used in income, finance, and reliability data. Traditional control charts assume normality, resulting in poor performance with heavy-tailed or skewed distributions. To address this, we introduce a repetitive control chart based on quantiles of the Dagum distribution. The approach includes deriving control limits, implementing an optimised repetitive sampling scheme, and evaluating performance using ARL. Simulation studies demonstrate that the proposed chart outperforms existing charts in detecting small to moderate shifts in data distributed according to a Dagum distribution.

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Publication Details

Journal
SCOPUA Journal of Applied Statistical Research
Published
2025-08-16
DOI
https://doi.org/10.64060/jasr.v1.i2.6
Primary Topic
Advanced Statistical Process Monitoring
Type
article
Field-Weighted Citation Impact
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article

Development of a Repetitive Control Chart for Monitoring Processes with Dagum-Distributed Data

M. Palanivel, G. V. Sriramachandran, R Nagaraju
SCOPUA Journal of Applied Statistical Research
Advanced Statistical Process Monitoring
article

Development of a Repetitive Control Chart for Monitoring Processes with Dagum-Distributed Data

M. Palanivel, G. V. Sriramachandran, R Nagaraju
article en

Abstract

This paper presents a repetitive control chart designed for monitoring processes where the quality characteristic follows a Dagum distribution a flexible, skewed distribution often used in income, finance, and reliability data. Traditional control charts assume normality, resulting in poor performance with heavy-tailed or skewed distributions. To address this, we introduce a repetitive control chart based on quantiles of the Dagum distribution. The approach includes deriving control limits, implementing an optimised repetitive sampling scheme, and evaluating performance using ARL. Simulation studies demonstrate that the proposed chart outperforms existing charts in detecting small to moderate shifts in data distributed according to a Dagum distribution.

SCOPUA Journal of Applied Statistical ResearchVol. 1(2)
Government Medical College (IN), Government Medical College (IN)
Openalex Percentile: Top 79%
Advanced Statistical Process Monitoring
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