Warranty forecasting of electronic boards using short-term field data

Vehbi Comert, Mustafa Altun, Mustafa Nadar, Ertunc Erturk

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The main goal of our study is precisely predicting the reliability performance of electronic boards throughout the warranty period by using short-term field return data. We have cooperated with one of the Europe's largest manufacturers and use their well-maintained data with over 1000 electronic board failures. Before using the field data for our model of warranty forecasting, we filter it to eliminate improper data, correlated to incomplete and poorly collected data. Our model is based on a two-parameter Weibull distribution, chosen from many other distribution options regarding optimum curve fitting. In the fitting process we use and compare 'Bayesian', 'rank regression', and 'maximum likelihood' fitting techniques. Our method has two steps. In the first step, we investigate how the Weibull parameter β changes by increasing the number of months of field data. For this purpose we use an electronic board with 36 months (full warranty period) of field return data. We develop a mathematical model of β as a function of the field data time interval and board dependent parameters. In the second step, we make a warranty forecasting of a new electronic board using its 3-month field data by using the mathematical model developed in the first step. The proposed method is evaluated by applying it to different electronic boards with 36 months (full warranty period) of field return data. The predicted results from our method and the direct results from the field return data matches well. This demonstrates the accuracy of our model.

Original languageEnglish
Title of host publicationRAMS 2015 - 61st Annual Reliability and Maintainability Symposium, Proceedings and Tutorials 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479967025
DOIs
Publication statusPublished - 8 May 2015
Event61st Annual Reliability and Maintainability Symposium, RAMS 2015 - Palm Harbor, United States
Duration: 26 Jan 201529 Jan 2015

Publication series

NameProceedings - Annual Reliability and Maintainability Symposium
Volume2015-May
ISSN (Print)0149-144X

Conference

Conference61st Annual Reliability and Maintainability Symposium, RAMS 2015
Country/TerritoryUnited States
CityPalm Harbor
Period26/01/1529/01/15

Bibliographical note

Publisher Copyright:
© 2015 IEEE.

Keywords

  • Electronics Reliability
  • Field Return Data
  • Warranty Forecasting
  • Weibull

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