Work

Run Sum Hotelling's T2${T}^2$ Chart for Autocorrelated Processes

Year: 2025

Type: article

Abstract: ABSTRACT Autocorrelation has recently gained significant attention as many industrial outcomes are autocorrelated. This work presents a multivariate run sum (MRS) chart for monitoring autocorrelated processes by utilizing a first‐order vector autoregressive (VAR(1)) model with an s ‐skip sampling strategy. To evaluate the performance of the proposed chart, the average run length (ARL) measure is used. Comparative analyses reveal that the proposed MRS chart significantly outperforms the basic charts for autocorrelated processes. The s ‐skip sampling strategy is incorporated into the MRS chart for autocorrelated processes to reduce the impact of autocorrelation. An illustrative example is included to demonstrate the practical implementation of the proposed chart, highlighting its advantages in real‐world applications and emphasizing its potential to improve process monitoring across various industrial settings.

Source: Quality and Reliability Engineering International

DOI: 10.1002/qre.3775

Authors: Sajal Saha, Michael B. C. Khoo, Oluwagbenga Tobi Babatunde, Sin Yin Teh, Wei Lin Teoh

Institutions: Universiti Sains Malaysia, International University of Business Agriculture and Technology, University of Nigeria, Heriot-Watt University Malaysia

Language: English

Topic: Advanced Statistical Process Monitoring

Subfield: Statistics, Probability and Uncertainty

Field: Decision Sciences

Domain: Social Sciences

Open Access status: hybrid

Estimated APC paid: $4,550

OpenAlex ID: W4409262335

FWCI: 2.466

Cites: 38

Cited by: 4

Related to: 10