Article ID: | iaor201113468 |
Volume: | 192 |
Issue: | 1 |
Start Page Number: | 3 |
End Page Number: | 19 |
Publication Date: | Jan 2012 |
Journal: | Annals of Operations Research |
Authors: | Tsung Fugee, Zou Changliang, Ning Xianghui |
Keywords: | service, datamining, statistics: multivariate, control |
In many applications of manufacturing and service industries, the quality of a process is characterized by the functional relationship between a response variable and one or more explanatory variables. Profile monitoring is for checking the stability of this relationship over time. In some situations, multiple profiles are required in order to model the quality of a product or process effectively. General multivariate linear profile monitoring is particularly useful in practice due to its simplicity and flexibility. However, in such situations, the existing parametric profile monitoring methods suffer from a drawback in that when the profile parameter dimensionality is large, the detection ability of the procedures commonly used