SFFS309A April   2022  – May 2022 TPS3704 , TPS3704-Q1

 

  1.   Trademarks
  2. 1Introduction
  3. 2Hardware Component Failure Modes Effects and Diagnostics Analysis (FMEDA)
    1. 2.1 Random Fault Estimation
      1. 2.1.1 Fault Rate Estimation Theory for Packaging
      2. 2.1.2 Fault Estimation Theory for Silicon Permanent Faults
      3. 2.1.3 Fault Estimation Theory for Silicon Transient Faults
      4. 2.1.4 The Classification of Failure Categories and Calculation
    2. 2.2 Using the FMEDA Spreadsheet Tool
      1. 2.2.1 Mission Profile Tailoring Tab
        1. 2.2.1.1 Confidence Level
        2. 2.2.1.2 Geographical Location
        3. 2.2.1.3 Life Cycle
        4. 2.2.1.4 Use Case Thermal Management Control (Theta-Ja) and Use Case Power
        5. 2.2.1.5 Safe vs Non-Safe (Safe Fail Fraction) for Each Component Type
        6. 2.2.1.6 Analog FIT Distribution Method
        7. 2.2.1.7 Operational Profile
      2. 2.2.2 Pin Level Tailoring Tab
      3. 2.2.3 Function and Diag Tailoring Tab
      4. 2.2.4 Diagnostic Coverage Tab
      5. 2.2.5 Customer Defined Diagnostics Tab
      6. 2.2.6 Totals - ISO26262 Tab
      7. 2.2.7 Details - ISO26262 Tab
      8. 2.2.8 Totals - IEC61508 Tab
      9. 2.2.9 Details - IEC61508 Tab
    3. 2.3 Example Calculation of Metrics
      1. 2.3.1 Assumptions of Use for Calculation of Safety Metrics
      2. 2.3.2 Summary of ISO 26262 Safety Metrics at Device Level
      3. 2.3.3 Summary of IEC 61508 Safety Metrics at Device Level
  4. 3Revision History

2.2 Using the FMEDA Spreadsheet Tool

A FMEDA is a common functional safety analysis technique used to determine the effectiveness of a functional safety architecture. For failure modes of the design blocks identified, a probability of occurrence is quantified. For diagnostics implemented, the effectiveness of the diagnostic is quantified. The quantification of these values enables the calculation of safety metrics per targeted functional safety standards such as the IEC 61508 safe failure fraction or the ISO 26262 single point fault metric, which estimates the effectiveness of the implemented safety architecture.

TI has created a FMEDA for this device that allows the user to tailor the metrics to their specific use case based on which features or design blocks are being used as part of the safety function. This tool additionally allows the user to modify the environmental factors, device power consumption, and other factors that affect the raw (base) FIT rates. Finally, this tool allows the user to customize the diagnostics that are applied that can detect faults within the device itself. All of the green cells in the spreadsheet can be modified by the user. All other cells have been populated by TI based on the specifics of the device or are calculated based on the user selections. This Excel workbook is locked to protect the user from incorrectly modifying the calculations. The sections below go into detail on how to use these tailoring options. Any tab not mentioned below is informational.

See Section 2.3.1 for the default values of these fields in this device's FMEDA.