SLOA294A June   2020  – April 2024 TPS3851-Q1 , TPS7A16A-Q1

 

  1.   1
  2.   Abstract
  3.   Trademarks
  4. 1 Introduction
  5. 2 Types of Faults and Quantitative Random Hardware Failure Metrics
  6. 3 Random Failures Over a Product Lifetime and Estimation of BFR
  7. 4 BFR Estimation Techniques
  8. 5 Siemens SN 29500 FIT model
  9. 6 IEC TR 62380
  10. 7 Recommended Assumptions for BFR Calculations
  11. 8 Special Considerations for Transient Faults
  12. 9 BFR Differences (Due to Package) Between IEC TR 62380 and SN 29500
  13. 10Effect of Power-on Hours on BFR
  14. 11What Can You Expect for TI Products
  15. 12Summary
  16. 13References
  17. 14Revision History

7 Recommended Assumptions for BFR Calculations

  • Choose only one technique and use that technique consistently. The technique can be any of the following:
    • Empirical
    • Based on field data
      • State the model (Weibull or exponential) used for failure rate derived from field data
    • Based on reliability guide. (TI products use BFRs derived from reliability guides.)
  • Assume a usage profile. Here are a couple of examples:
    • Industrial: always on 24/7 year-round until a scheduled preventive maintenance cycle
    • Automotive motor control: two to four starts per day, approximately 4 hours per day of use, as in IEC TR 62380
  • Select (and state) the confidence interval (75%, 80%, 90%) for the underlying statistics used in the estimation
  • Clearly document any scaling factors or derates that have gone into the BFR estimation
  • Account for non-operating time and solder-joint-based failures

As long as all semiconductor suppliers use the same BFR estimation assumptions – or at minimum explicitly state the assumptions – it is possible to compare the BFRs of comparable semiconductor components from two different manufacturers.