DocumentCode
3434952
Title
Notice of Retraction
Reliability assessment of products based on performance degradation data with outliers paper
Author
Jun Lu ; Baowei Song ; Zhaoyong Mao ; Chunyang Cheng
Author_Institution
Inst. of Underwater Vehicle Coll. of Marine, Northwestern Polytech. Univ., Xi´an, China
fYear
2013
fDate
15-18 July 2013
Firstpage
75
Lastpage
77
Abstract
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
Performance degradation data can provide useful information for reliability assessment. Especially for high reliability and long life products, the overall effect is good using of performance degradation data. However, there are some outliers in the testing process of product performance because of the influence of random error, which makes the assessment be not robust. In this case, this paper uses fuzzy clustering least squares method to evaluate the parameters, which impair the influence of outliers and improve the stability. Finally, an actual example is presented to show that the method is correct and effective.
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
Performance degradation data can provide useful information for reliability assessment. Especially for high reliability and long life products, the overall effect is good using of performance degradation data. However, there are some outliers in the testing process of product performance because of the influence of random error, which makes the assessment be not robust. In this case, this paper uses fuzzy clustering least squares method to evaluate the parameters, which impair the influence of outliers and improve the stability. Finally, an actual example is presented to show that the method is correct and effective.
Keywords
fuzzy set theory; least squares approximations; performance evaluation; product quality; reliability; fuzzy clustering least squares method; outliers paper; product performance degradation data; product reliability assessment; Degradation; Estimation; Least squares approximations; Reliability theory; Time measurement; Transistors; fuzzy clustering; least-squares estimation; outliers; performance degradation; reliability;
fLanguage
English
Publisher
ieee
Conference_Titel
Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE), 2013 International Conference on
Conference_Location
Chengdu
Print_ISBN
978-1-4799-1014-4
Type
conf
DOI
10.1109/QR2MSE.2013.6625538
Filename
6625538
Link To Document