A Novel Clustering Approach for Estimating the Time of Step Changes in Shewhart Control Charts
Although control charts are very common to monitoring process changes, they usually do not indicate the real time of the changes. Identifying the real time of the process changes is known as change-point estimation problem. There are a number of change point models in the literature however most of...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Iran University of Science & Technology
2008-12-01
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| Series: | International Journal of Industrial Engineering and Production Research |
| Subjects: | |
| Online Access: | http://ijiepr.iust.ac.ir/browse.php?a_code=A-10-1-5&slc_lang=en&sid=1 |
| Summary: | Although control charts are very common to monitoring process changes, they usually do not indicate the real time of the changes. Identifying the real time of the process changes is known as change-point estimation problem. There are a number of change point models in the literature however most of the existing approaches are dedicated to normal processes. In this paper we propose a novel approach based on clustering techniques to estimate Shewhart control chart change-point when a sustained shift is occurrs in the process mean. For this purpose we devise a new clustering mechanism, a new similarity measure and a new objective function. The proposed approach is not only capable of detecting process change-points, but also automatically estimates the true values of the out-of-control parameters of the process. We also compare the performance of the proposed approach with existing methods. |
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| ISSN: | 2008-4889 2345-363X |