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Abstract Details

Activity Number: 239
Type: Contributed
Date/Time: Monday, July 30, 2012 : 2:00 PM to 3:50 PM
Sponsor: Quality and Productivity Section
Abstract - #306384
Title: Spatial Control Charts for the Mean
Author(s): Scott Grimshaw*+ and Natalie J. Blades
Companies: Brigham Young University and Brigham Young University
Address: Statistics Department, Provo, UT, 84602, United States
Keywords: spatial covariance models ; multivariate control charts ; optimal allocation of sample resources

New ultrasonic technology to measure thickness of bottles is nondestructive and provides the opportunity to obtain measurements at any location. Increasing the number of measurements may increase the sensitivity of control charts to detection of flaws in local regions; however, the correlation between spatially-close measurements may introduce redundancy and inefficiency in the test. This presentation treats the bottle measurements as spatial data and investigates the properties of control charts where the spatial measurements are assembled into a vector and multivariate charts are constructed where the covariance matrix is derived from the semivariogram.

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