1. Reliability Prediction of Electronic Boards by Analyzing Field Return Data Authors: Vehbi Cömert (Presenter) Mustafa Altun Hadi Yadavari Ertunç Ertürk

2. Performing a reliability analysis using a real field return data Motivation: Modeling hazard rate curve and making accurate reliability prediction 2

3. 3 Introduction Field Return Data Electronics Reliability Filtering Field return data may have obvious and hidden errors. Surveying accuracy of the field return data to find errors Based on beta parameter of Weibull distirubtion Modeling of hazard rate curve Reliability prediction with filtered field return data Investigation of distributions that fits to data. Change of hazard rate shape with respect to ‘Time to Failure’ Two phase hazard rate curve

4. Field Return Data The field return data,that we use, belongs to Arçelik (Beko), one of the biggest white apliance company in Europe It is a warranty data and includes - 1 million sales - 3000 warranty claims - We have first 54 months of the data Warranty involves 36 months. 4

5. Electronics Reliability Good reliability Expected long life Usually catastrophic failures Decreasing or constant hazard rate Hard to see wear out signs 5

6. 6 Filtering Eliminating errors in field return data Step 1 : Eliminating Obvious Errors Step 2 : Eliminating Hidden Errors Stage 1: Forward analysis Stage 2: Backward analysis Stage 3: 6-month analysis

7. Errors in field return data Obvious error : The errors that can be seen easily by checking claims Hidden error : The errors that cannot be seen at first glance What can be a hidden error? 7 Assembly dateReturn Date 11 November 201112 July 2016 Missing Claims

8. Filtering Process To ensure the accuracy of the analysis, errors must be eliminated !!! Step 1 : Obvious errors must be filtered by checking hand 8 Records with; Unknown assembly date Unknown return date Zero time to failure Negative time to failure Unreasonable time to failure

9. Filtering Process 9

10. Step -2 stage1 : Forward Analysis 10 161218243036424854 problematic Assembly date/Month Weibull Fitting

11. Filtering Process Step-2 stage-2: Backward analysis 11 161218243036424854 Lack of return data toward end of the time Assembly date/Month

12. Filtering Process Step-2 stage-3: 6 - month periods analysis 12 061218243036424854 problematic Assembly date/Month

13. Filtering Process 13 problematic First three intervals (1-18 months) should be filtered.

14. 14 Modeling of hazard rate curve To obtain an accurate hazard rate curve Searching points where the hazard rate tendency changes Forward and Backward analysis

15. Modeling of Hazard Rate Curve 15

16. Modeling of Hazard Rate Curve Method to find change point via Reliasoft Weibull++ -Analyzing filtered field return data in terms of time to failure (TTF) - Using ‘’best fit’’ option in Weibull++ and fitting with respect to different time intervals. - Trying to find the point where the best fitting distribution changes by showing different hazard rate trend 16

17. Forward analysis Modeling of Hazard Rate Curve 17 1 2 3 4 5 6 7 8 …………………………… M f ……………………………………………..…………………………..36 Time to Failure/month includes field returns that can have all TTF values between 1 and M f Results : At end of each interval analysis, decreasing hazard rate trend was observed for this filtered data. Weibull++ offered most commonly Weibull distribution in addition to Lognormal and Gamma distributions What is the hazard rate trend? Most likelihood distribution

18. Modeling of Hazard Rate Curve 18 1 2 3 4 5 6 7 8 …………………………… M b …………………………………….……………33 34 35 36 includes field returns that can have all TTF values between M b and 36 month

19. Modeling of Hazard Rate Curve 19 M < 14 Weibull Distribuiton M > 14 Exponential Distribution

20. Modeling of Hazard Rate Curve 20

21. Conclusion This study will be used by Arçelik Usefull for high volume sales This methods can be generalized for all field return datas 21 FILTERING A systematic approach is offered for elimination errors in field return data To determine hidden errors. 1) Forward Analysis 2) Backward Analysis 3) 6-month Analysis 18 months at begining of the data seem as problematic MODELING OF HAZARD RATE CURVE We look for change of hazard rate tendency 1) Forward Analysis 2) Backward Analysis In the forward analysis we didn’t see a change in the hazard rate shape But in the backward analysis, exponential distribution fits best between 14 and 36 months

22. THANK YOU 22