Abstract
When a control chart signals that an assignable cause is present, process engineers are required to identify a time point of process changes and then search for the assignable cause of the process disturbance. In the statistical process control literature, there is a research area called change point detection. As one of change point detection problems, it has been considered how to identify the time of a step-change in the process fraction nonconforming using the maximum likelihood theory. However, the process fraction nonconforming may be changed multiple times until a chart signals. Such a multiple change-points model for the process fraction nonconforming has not been considered yet. In this study, we consider a multiple change-points model of the process fraction nonconforming under a p chart. Then, a method of tracking the transition of process fraction nonconforming is proposed using the maximum likelihood theory and information criterion.
Original language | English |
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Pages (from-to) | 130-134 |
Number of pages | 5 |
Journal | IFAC-PapersOnLine |
Volume | 52 |
Issue number | 13 |
DOIs | |
Publication status | Published - Sept 2019 |
Event | 9th IFAC Conference on Manufacturing Modelling, Management and Control, MIM 2019 - Berlin, Germany Duration: Aug 28 2019 → Aug 30 2019 |
Keywords
- Akaike information criterion (AIC)
- Change point detection
- Control chart
- Dynamic programming
- Maximum likelihood
- P chart
- Proportion of nonconforming items
- Quality control
- Statistical inference
ASJC Scopus subject areas
- Control and Systems Engineering