TY - JOUR
T1 - Effect of measurement errors on dual CUSUM mean charts
AU - Munir, Tahir
AU - Qin, Hong
AU - Cheema, Salman A.
AU - He, Zhen
N1 - Publisher Copyright:
© 2025
PY - 2025/9
Y1 - 2025/9
N2 - The accuracy of a measurement system is crucial for ensuring reliable process monitoring with statistical process control charts. This study examines the influence of measurement errors on the performance of four dual CUSUM control charts in detecting shifts in the mean of normally and non-normal distributed processes. These charts are called the dual CUSUM (DC), dual Crosier's CUSUM (DCC), EWMA-dual DC (EDC), and EWMA-dual DCC (EDCC) charts, incorporate an additive measurement error model. Through extensive Monte-Carlo simulations are applied to assess their performance in terms of various metrics, such as average run length (ARL), extra quadratic loss (EQL), integrated relative ARL (IRARL), and performance comparison index (PCI). The results indicate that the presence of measurement errors can significantly diminish the charts' effectiveness, which can be mitigated by utilizing a multiple measurements scheme. Among the four charts examined, the EDCC chart shows the most favorable performance, while the DC chart shows the least favorable. To illustrate the impact of measurement uncertainty and demonstrate the charts' implications, a simulated as well as real-life datasets with a shift in the process mean is employed.
AB - The accuracy of a measurement system is crucial for ensuring reliable process monitoring with statistical process control charts. This study examines the influence of measurement errors on the performance of four dual CUSUM control charts in detecting shifts in the mean of normally and non-normal distributed processes. These charts are called the dual CUSUM (DC), dual Crosier's CUSUM (DCC), EWMA-dual DC (EDC), and EWMA-dual DCC (EDCC) charts, incorporate an additive measurement error model. Through extensive Monte-Carlo simulations are applied to assess their performance in terms of various metrics, such as average run length (ARL), extra quadratic loss (EQL), integrated relative ARL (IRARL), and performance comparison index (PCI). The results indicate that the presence of measurement errors can significantly diminish the charts' effectiveness, which can be mitigated by utilizing a multiple measurements scheme. Among the four charts examined, the EDCC chart shows the most favorable performance, while the DC chart shows the least favorable. To illustrate the impact of measurement uncertainty and demonstrate the charts' implications, a simulated as well as real-life datasets with a shift in the process mean is employed.
KW - Dual dual CUSUM chart
KW - Measurement error
KW - Monte Carlo simulation
KW - Multiple measurements
KW - Reliability monitoring
KW - Statistical process control
UR - https://www.scopus.com/pages/publications/105013492374
U2 - 10.1016/j.rineng.2025.106201
DO - 10.1016/j.rineng.2025.106201
M3 - Article
AN - SCOPUS:105013492374
SN - 2590-1230
VL - 27
JO - Results in Engineering
JF - Results in Engineering
M1 - 106201
ER -