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