A mixed HWMA-CUSUM mean chart with an application to manufacturing process

Muhammad Abid; Sun Mei; Hafiz Zafar Nazir; Muhammad Riaz; Shahid Hussain

doi:10.1002/qre.2752

A mixed HWMA-CUSUM mean chart with an application to manufacturing process

Muhammad Abid^*
, Sun Mei
, Hafiz Zafar Nazir
, Muhammad Riaz
, Shahid Hussain

^*Corresponding author for this work

Department of Mathematics

Research output: Contribution to journal › Article › peer-review

44 Scopus citations

Abstract

Memory-type control charts play a significant role to identify slight changes in the parameters of the production process. In this article, we have proposed a new cumulative sum chart that utilizes the statistic of the homogeneously weighted moving average chart. The performance of the proposed chart is studied using Monte Carlo simulations. The proposed chart is compared with some existing charts under different run length profiles. The run length profile comparisons reveal that the proposed chart performs superior as compared to the existing control charts. A real-life application using a manufacturing process dataset is also part of this study.

Original language	English
Pages (from-to)	618-631
Number of pages	14
Journal	Quality and Reliability Engineering International
Volume	37
Issue number	2
DOIs	https://doi.org/10.1002/qre.2752
State	Published - Mar 2021

Bibliographical note

Publisher Copyright:
© 2020 John Wiley & Sons Ltd.

Keywords

CUSUM
HWMA
average run length
manufacturing processes
mixed control chart
run length profiles

ASJC Scopus subject areas

Safety, Risk, Reliability and Quality
Management Science and Operations Research

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1002/qre.2752

Cite this

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title = "A mixed HWMA-CUSUM mean chart with an application to manufacturing process",

abstract = "Memory-type control charts play a significant role to identify slight changes in the parameters of the production process. In this article, we have proposed a new cumulative sum chart that utilizes the statistic of the homogeneously weighted moving average chart. The performance of the proposed chart is studied using Monte Carlo simulations. The proposed chart is compared with some existing charts under different run length profiles. The run length profile comparisons reveal that the proposed chart performs superior as compared to the existing control charts. A real-life application using a manufacturing process dataset is also part of this study.",

keywords = "CUSUM, HWMA, average run length, manufacturing processes, mixed control chart, run length profiles",

author = "Muhammad Abid and Sun Mei and Nazir, \{Hafiz Zafar\} and Muhammad Riaz and Shahid Hussain",

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AU - Abid, Muhammad

AU - Mei, Sun

AU - Nazir, Hafiz Zafar

AU - Riaz, Muhammad

AU - Hussain, Shahid

PY - 2021/3

Y1 - 2021/3

N2 - Memory-type control charts play a significant role to identify slight changes in the parameters of the production process. In this article, we have proposed a new cumulative sum chart that utilizes the statistic of the homogeneously weighted moving average chart. The performance of the proposed chart is studied using Monte Carlo simulations. The proposed chart is compared with some existing charts under different run length profiles. The run length profile comparisons reveal that the proposed chart performs superior as compared to the existing control charts. A real-life application using a manufacturing process dataset is also part of this study.

AB - Memory-type control charts play a significant role to identify slight changes in the parameters of the production process. In this article, we have proposed a new cumulative sum chart that utilizes the statistic of the homogeneously weighted moving average chart. The performance of the proposed chart is studied using Monte Carlo simulations. The proposed chart is compared with some existing charts under different run length profiles. The run length profile comparisons reveal that the proposed chart performs superior as compared to the existing control charts. A real-life application using a manufacturing process dataset is also part of this study.

KW - CUSUM

KW - HWMA

KW - average run length

KW - manufacturing processes

KW - mixed control chart

KW - run length profiles

UR - https://www.scopus.com/pages/publications/85090944534

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JO - Quality and Reliability Engineering International

JF - Quality and Reliability Engineering International

IS - 2

ER -

A mixed HWMA-CUSUM mean chart with an application to manufacturing process

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

UN SDGs

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