CHANGE POINT DETECTION OF ROBUST INDIVIDUALS CONTROL CHART

Authors

  • Kooi Huat Ng Universiti Tunku Abdul Rahman
  • Habshah Midi Universiti Putra Malaysia
  • Kok Haur Ng University of Malaya

DOI:

https://doi.org/10.23055/ijietap.2017.24.5.2947

Keywords:

Industrial engineering, Production, Manufacturing engineering, Quality management

Abstract

Crucial part in the inference of industrial process change point detection is that once a suspected change point is detected, statistical test needs to be carried out to ensure the significance of the change. Conventional test statistics such as Maximum-Type testing method is very sensitive to outliers as the formulation of estimator is lack of robustness. In addition, oftentimes, evidence of larger shifts could be mistakenly downweighted or rejected stemming from these outliers and also due to the designated score function. The proposed robust individuals control chart adopting the HMT testing method is based on a well-motivated Huber score function, which appears to provide protection against this complication. Extensive numerical simulation studies were carried out to assess the performance of the proposed procedure with its counterparts.  Taking a real data set from industry, we illustrate the usefulness and applicability of the proposed chart in practice.

Author Biographies

Kooi Huat Ng, Universiti Tunku Abdul Rahman

Lee Kong Chian Faculty of Engineering and Science, Department of Mathematical and Actuarial Sciences, Universiti Tunku Abdul Rahman.

Position: Assistant Professor

Habshah Midi, Universiti Putra Malaysia

Department of Mathematics, Faculty of Science,
Universiti Putra Malaysia.

Position: Professor

Kok Haur Ng, University of Malaya

Institute of Mathematical Sciences, Faculty of Science,
University of Malaya.

Position: Senior Lecturer

Published

2018-01-11

How to Cite

Ng, K. H., Midi, H., & Ng, K. H. (2018). CHANGE POINT DETECTION OF ROBUST INDIVIDUALS CONTROL CHART. International Journal of Industrial Engineering: Theory, Applications and Practice, 24(5). https://doi.org/10.23055/ijietap.2017.24.5.2947

Issue

Section

Quality, Reliability, Maintenance Engineering

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