Aug 2026· Quality and Reliability Engineering International· 0 citations· 8 references
Abstract
Explanatory variables affect the characteristics of processes in most monitoring applications, and the failure to consider them may give misleading signals and performance in detection. Control charts based on regression help to overcome this problem by observing regression‐adjusted residuals, but most of the current schemes depend on a set of given parameters and assume that shift magnitudes are known. The paper suggests a Regression‐based Adaptive CUSUM (RA‐ACUSUM) control chart whose reference parameter is dynamically changed in accordance with the observed residual deviations. Results of the simulation, which has been calibrated to a typical in‐control average run length, indicate that the proposed chart performs better in small to moderate shifts with stable in‐control behavior compared to the benchmark regression‐based CUSUM charts and EWMA charts. The practical usefulness of the proposed method is demonstrated by an application to the agricultural production monitoring.
The original Shewhart p- and c-charts monitor binomial and Poisson attribute data using normal-approximation control limits, which may be unreliable for small or moderate samples, low defect levels, or sparse nonconformities. This study proposes Improved Square Root Transformation-based modified exponentially weighted...
S. Phantu, Y. Areepong, S. Sukparungsee· WSEAS transactions on system...· 0 citations
This study proposes a multivariate functional CUSUM (MFCUSUM) control chart for Phase II monitoring of high-dimensional multivariate functional data. The proposed framework combines B-spline smoothing, multivariate functional principal component analysis (MFPCA), whitening transformation, and CUSUM accumulation, with c...
Ayu Afrinah, M. Mashuri, M. Ahsan· IEEE Access· 0 citations
This study introduces a Bayesian Variable Sample Size (VSS) Re‐weighted Adaptive Exponentially Weighted Moving Average (VRAEWMA) control chart that incorporates a sigmoid adjustment function for efficient detection of process mean shifts. By integrating Bayesian inference with the adaptive VRAEWMA framework, the prop...
Hassan M. Aljohani, Imad Khan, M. A. Elwahab et al.· Quality and Reliability Engi...· 0 citations
Numerous attribute control charts have been developed to monitor process means; however, most rely on the assumption of statistical independence, rendering them inadequate for modern industrial environments where process variables exhibit significant autocorrelation. This study proposes a novel attribute control char...
Luh Juni Asrini, Kung-Jeng Wang· Quality and Reliability Engi...· 0 citations
The shifted (or two‐parameter) exponential distribution is a well‐known flexible probability model for skewed data, such as failure times or survival times due to its two‐parameter representation. Control charts for monitoring a process that is modeled according to a shifted exponential distribution have been studied...
D. Antzoulakos, K. G. Fountoukidis, A. Rakitzis· Quality and Reliability Engi...· 0 citations
