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Articles
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QICID: 27591
Title: Process Partitions from Time-Ordered Clusters
Copyright: ASQ
Author: Harnish, Peter; Nelson, Ben; Runger,George
Organization: Weyerhaeuser Company; Arizona State University
Subject: Change agent; Cluster analysis; Data collection; Data analysis; Segmentation problems; Constraints;
Series: Journal of Quality Technology, Vol. 41, No. 1, January 2009, pp. 3-17
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Abstract: [This abstract is based on the authors' abstract.]
Standard statistical methods based on global models may not be effective for the analysis of massive multivariate industrial data sets unless the data is partitioned into stable operating regions. Constrained clustering is proposed as a robust solution to detect change points and partition historical process data. The constraint is that only observations that are contiguous in time can be joined. A method is described for partitioning data sets into stable regions by modifying agglomerative clustering algorithms to take into account the time order within the data set. A stopping criterion is proposed to evaluate the number of change points generated.
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