Tahir Munir, Xuelong Hu, Osmo Kauppila, Bjarne Bergquist, Effect of measurement uncertainty on combined quality control charts, Computers & Industrial Engineering, Volume 175, 2023, 108900, ISSN 0360-8352, https://doi.org/10.1016/j.cie.2022.108900
Effect of measurement uncertainty on combined quality control charts
|Author:||Munir, Tahir1; Hu, Xuelong2; Kauppila, Osmo3,4;|
1Department of Anaesthesiology, The Aga Khan University Karachi, Pakistan
2School of Management, Nanjing University of Posts and Telecommunications, Nanjing, China
3Industrial Engineering and Management, University of Oulu, Finland
4Quality Technology and Logistics, Luleå University of Technology, Luleå, Sweden
|Online Access:||PDF Full Text (PDF, 3.5 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2023050942369
|Publish Date:|| 2023-05-09
The accuracy of the measurement system is vital for reliable process monitoring using statistical process control charts. The applied chart’s effectiveness depends on the measurement system’s performance. Measurement uncertainty can lead to incorrect decisions like unnecessary stops or failure to intervene. In this paper, we investigated the effect of measurement errors on the performance of four well-established combined charts for monitoring the mean of normally distributed processes: Shewhart-CUSUM, Shewhart-Crosier’s CUSUM, Shewhart-EWMA and Shewhart-GWMA charts. To deal with measurement errors we considered the additive measurement error model. Detailed run length profiles of these charts are studied in terms of average run length (ARL), extra quadratic loss, relative ARL, and performance comparison index through Monte Carlo simulations under different sizes of measurement errors. It was found that measurement errors significantly reduce the power of the combined charts. Thus, multiple measurements scheme is incorporated as a remedy to this effect. The Shewhart-Crosier’s CUSUM performed best of four charts, while the Shewhart-EWMA chart did worst. To demonstrate the effect of measurement uncertainty and highlight implications further, a simulated dataset with a shift in the process mean is considered.
Computers & industrial engineering
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
222 Other engineering and technologies
This research was supported by these foundations: Foundation of Nanjing University of Posts and Telecommunications (No. NY222176), The Excellent Innovation Teams of Philosophy and Social Science in Jiangsu Province (No. 2017ZSTD022) and Key Research Base of Philosophy and Social Sciences in Jiangsu - Information Industry Integration Innovation and Emergency Management Research Center.
© 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).