Monitoring of Multiple Binary Data Streams using a Hierarchical Model Structure. (20th July 2015)

• Record Type: Journal Article
• Authors: Das, Devashish; Chen, Yong; Zhou, Shiyu; Sievenpiper, Crispian
• Is Part Of: Quality and reliability engineering international. Volume 32:Number 4(2016:Jun.)
• Page Start: 1307
• Page End: 1319
• Publication Date: 2015-07-20
• Subjects: attribute control chart -- multi‐stream process monitoring -- over‐dispersed binary data monitoring; Reliability (Engineering) -- Periodicals; Quality control -- Periodicals; High technology -- Periodicals; 620.00452
• DOI: 10.1002/qre.1831
• Languages: English
• ISSNs: 0748-8017

Abstract

Abstract : Multiple streams of binary data occur commonly in practice. In this paper, we propose a hierarchical statistical model to describe multi‐stream binary data that demonstrate over‐dispersion. In such a model, a group of binary streams in a multi‐stream dataset is modeled by a beta‐binominal hierarchical mixture distribution. Using this hierarchical model structure, a cumulative sum (CUSUM) chart based on the log‐likelihood ratio is developed to monitor all the data streams simultaneously. The performance of the CUSUM chart is investigated and compared to conventional monitoring schemes through numerical studies and a real‐world dataset. It is shown that the CUSUM method using the hierarchical model is effective and advantageous over the conventional methods. Copyright © 2015 John Wiley & Sons, Ltd.