NDLI: Multivariate outlier modeling for capturing customer returns

Content Provider	IEEE Xplore Digital Library
Author	Tikkanen, J. Sumikawa, N. Wang, L.-C. Abadir, M.S.
Copyright Year	2014
Description	Author affiliation: UC-Santa Barbara, Santa Barbara, CA, USA (Tikkanen, J.; Wang, L.-C.) \|\| Freescale Semicond., USA (Sumikawa, N.; Abadir, M.S.)
Abstract	Univariate outlier analysis has become a popular approach for improving quality. When a customer return occurs, multivariate outlier analysis extends the univariate analysis to develop a test model for preventing similar returns from happening. In this context, this work investigates the following question: How simple multivariate outlier modeling can be? The interest for answering this question are twofold: (1) to facilitate implementation of a test model in test application and (2) to ensure robustness of the methodology. In this work, we explain that based on a Gaussian assumption, a simpler covariance-based outlier analysis approach can be sufficient over a more complex density-based approach such as one-class SVM. We show that correlation among tests can be a good metric to rank potential outlier models. Based on these observations a simple outlier analysis methodology is developed and applied to effectively analyze customer returns from two automotive product lines.
Starting Page	164
Ending Page	169
File Size	2955165
Page Count	6
File Format	PDF
ISBN	9781479953240
DOI	10.1109/IOLTS.2014.6873663
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-07-07
Publisher Place	Spain
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Correlation Support vector machines Gaussian distribution Analytical models Semiconductor device modeling Automotive engineering Testing
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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