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Activity Number:
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368
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Type:
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Contributed
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Date/Time:
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Tuesday, August 4, 2009 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Quality and Productivity
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| Abstract - #305304 |
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Title:
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Profile-Monitoring Analysis with Fixed and Random Effects Using Nonparametric and Semiparametric Methods
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Author(s):
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Abdel-Salam G. Abdel-Salam*+ and Jeffrey B. Birch
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Companies:
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Virginia Polytechnic Institute and State University and Virginia Polytechnic Institute and State University
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Address:
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400 Fairfax Rd., Apt. B-15 , Blacksburg, VA, 24060,
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Keywords:
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Profile Monitoring ; Semiparametric ; Model Robust Regression ; Nonparametric ; Model Misspecification ; T2 Control Chart
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Abstract:
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Profile monitoring is a relatively new technique in quality control best used where the process data follow a profile (or curve) at each time period. The majority of previous studies in profile monitoring focused on the parametric modeling of either linear or nonlinear profiles, with both fixed and random-effects, under the assumption of correct model specification. Our work considers those cases where the parametric model for the family of profiles is unknown or, at least uncertain. Consequently, we consider monitoring profiles via two methods, a nonparametric method and a semiparametric procedure that combines both parametric and nonparametric profile fits, a procedure we refer to as model robust profile monitoring (MRPM). We speculate that both methods will be robust to the common problem of model misspecification.
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