Phase‐II Monitoring the Ratio of Population Means of a Bivariate Normal Distribution Based on Subgroup Samples

ABSTRACT In various industrial contexts, there is a need for online monitoring of quality characteristics represented as the ratio of two normal random variables. This includes scenarios such as maintaining the correct proportion between ingredients or elements in a product, assessing product performance before and after specific operations like chemical reactions, and monitoring chemical or physical properties computed as ratios. This paper introduces two new Phase II Shewhart monitoring schemes for monitoring the ratio of population means of bivariate normal distributions when parameters are known and unknown, respectively. Notably, the size of each sample unit can vary across different subgroups, enhancing the adaptability of the chart implementation in diverse manufacturing settings. We use the average run length (ARL) for evaluating the Phase II performance of the proposed monitoring schemes. Simulation results are provided to demonstrate the statistical performance of the investigated monitoring schemes under the known and unknown parameter cases. Two real‐data examples are presented for illustration.

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Publication Details

Journal
Quality and Reliability Engineering International
Published
2026-09-29
DOI
https://doi.org/10.1002/qre.70400
Primary Topic
Advanced Statistical Process Monitoring
Type
article
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article

Phase‐II Monitoring the Ratio of Population Means of a Bivariate Normal Distribution Based on Subgroup Samples

Amitava Mukherjee, FuPeng Xie, Anan Tang, Philippe Castagliola et al.
Quality and Reliability Engineering International
Advanced Statistical Process Monitoring
article

Phase‐II Monitoring the Ratio of Population Means of a Bivariate Normal Distribution Based on Subgroup Samples

Amitava Mukherjee, FuPeng Xie, Anan Tang, Philippe Castagliola, Xiaohan Zhang
article en

Abstract

ABSTRACT In various industrial contexts, there is a need for online monitoring of quality characteristics represented as the ratio of two normal random variables. This includes scenarios such as maintaining the correct proportion between ingredients or elements in a product, assessing product performance before and after specific operations like chemical reactions, and monitoring chemical or physical properties computed as ratios. This paper introduces two new Phase II Shewhart monitoring schemes for monitoring the ratio of population means of bivariate normal distributions when parameters are known and unknown, respectively. Notably, the size of each sample unit can vary across different subgroups, enhancing the adaptability of the chart implementation in diverse manufacturing settings. We use the average run length (ARL) for evaluating the Phase II performance of the proposed monitoring schemes. Simulation results are provided to demonstrate the statistical performance of the investigated monitoring schemes under the known and unknown parameter cases. Two real‐data examples are presented for illustration.

Quality and Reliability Engineering International
Centre National de la Recherche Scientifique (FR), Nanjing Institute of Technology (CN), Xavier School of Management (IN), Nanjing University of Posts and Telecommunications (CN), Laboratoire des Sciences du Numérique de Nantes (FR), Nantes Université (FR)
Openalex Percentile: Top 9%
Advanced Statistical Process Monitoring
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Phase‐II Monitoring the Ratio of Population Means of a Bivariate Normal Distribution Based on Subgroup Samples — Amitava Mukherjee, FuPeng Xie, et al. · Quality and Reliability Engineering International (2026) | TGRS Research Map | TGRS