A phase-II change-point-based distribution-free scheme for monitoring of three process aspects

Abstract

In recent years, more attention has been paid to joint monitoring of two-aspects, namely, location and scale parameters, of a continuous process when their in-control (IC) standard values are unknown. However, barring a few, most literature ignores the third aspect of the process, namely the shape parameter. This paper proposes a new distribution-free change point formulation-based scheme for monitoring three aspects of a process simultaneously. No prior knowledge about the process distribution or its parameters, except for continuousness, is required. We discuss the in-control robustness of the proposed scheme, assuming that an independently and identically distributed Phase-I sample of size greater or equal to five from an unknown population is available. Simulation studies based on Monte-Carlo reveal some advantages of the proposed scheme over its competitors. An illustration with the arrival delay data of a Railway Network is presented, and some concluding remarks with future research directions are offered.

Keywords:

• Change-point detection
• distribution-free
• linear rank statistic
• statistical process control
• tri-aspect

Acknowledgments

The authors are grateful to the editor, the associate editor, and anonymous referees for many constructive comments and suggestions, which improved the quality of this paper greatly.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Correction Statement

This article has been corrected with minor changes. These changes do not impact the academic content of the article.

Additional information

Funding

This work was supported by the National Key R&D Program of China [2022YFA1003801; 2021YFA1000101; 2021YFA1000102], National Natural Science Foundation of China [12201382;12071144; 71931004], Basic Research Project of Shanghai Science and Technology Commission [22JC1400800], Shanghai Pilot Program for Basic Research [TQ20240201].