An adaptive EWMA scheme‐based CUSUM accumulation error for efficient monitoring of process location

• Published in: Quality and reliability engineering international Vol. 33; no. 8; pp. 2463 - 2482
• Main Authors: Zaman, Babar, Lee, Muhammad Hisyam, Riaz, Muhammad, Abujiya, Mu'azu Ramat
• Format: Journal Article
• Language: English
• Published: Bognor Regis Wiley Subscription Services, Inc 01-12-2017
• Subjects: Accumulation; Adaptive control; adaptive EWMA; average run length; Control charts; Environmental monitoring; Error detection; Handling; Huber function; Process controls; Product quality; Quality assurance; Quality control; Statistical methods; Tukey bisquare function
• ISSN: 0748-8017; 1099-1638
• DOI: 10.1002/qre.2203

The examination of product characteristics using a statistical tool is an important step in a manufacturing environment to ensure product quality. Several methods are employed for maintaining product quality assurance. Quality control charts, which utilize statistical methods, are normally used to detect special causes. Shewhart control charts are popular; their only limitation is that they are effective in handling only large shifts. For handling small shifts, the cumulative sum (CUSUM) and the exponential weighted moving average (EWMA) are more practical. For handling both small and large shifts, adaptive control charts are used. In this study, we proposed a new adaptive EWMA scheme. This scheme is based on CUSUM accumulation error for detection of wide range of shifts in the process location. The CUSUM features in the proposed scheme help with identification of prior shifts. The proposed scheme uses Huber and Tukey bisquare functions for an efficient shift detection. We have used average run length (ARL) as performance indicator for comparison, and our proposed scheme outperformed some of the existing schemes. An example that uses real‐life data is also provided to demonstrate the implementation of the proposed scheme.