DocumentCode :
2209192
Title :
Refrigerator failure early prediction based on warranty data
Author :
Liu, Ke
fYear :
2002
fDate :
2002
Firstpage :
195
Lastpage :
199
Abstract :
This paper provides a method to predict the failure characteristics of refrigerator components based on the early warranty return data from the field (suspended data). The predication will be used to support the management decision of actions. Very commonly, the company doesn´t (or has no capability to) record each unit purchase date by the end customers (not by OEM), but does record all units´ manufacture dates and returned units´ purchase dates for the warranty claims purpose. This makes it difficult for the analyst to estimate how many units are currently used in the field, which is required in order to do a suspended data analysis. This paper chooses a ´sample population´ from warranty claim database and uses Weibull distribution to describe the time duration between the manufacture dates and end customer purchase dates for the units in the sample population. Then, assuming this time duration distribution representing the time duration distribution of the ´objective population´, and using integration function described in this paper, how many units of objective population are currently used in the field can be estimated. This makes the reliability prediction possible (by processing the field suspended data). An example is used to demonstrate the method
Keywords :
Weibull distribution; failure analysis; refrigerators; reliability; Weibull distribution; censored data; field failure analysis; refrigerator failure early prediction; reliability prediction; returned units´ purchase dates; suspended data analysis; time duration distribution; unit manufacture dates; unit purchase date; warranty analysis; warranty claims; Absorption; Costs; Data analysis; Databases; Failure analysis; Pulp manufacturing; Refrigeration; Virtual manufacturing; Warranties; Weibull distribution;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Reliability and Maintainability Symposium, 2002. Proceedings. Annual
Conference_Location :
Seattle, WA
ISSN :
0149-144X
Print_ISBN :
0-7803-7348-0
Type :
conf
DOI :
10.1109/RAMS.2002.981641
Filename :
981641
Link To Document :
بازگشت