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Handbook for Robustness Validation of Semiconductor Devices in Automotive Applications
- Ground Vehicle Standard
Published February 21, 2014 by SAE International in United States
Downloadable datasets availableAnnotation ability available
This document will primarily address intrinsic reliability of electronic components for use in automotive electronics. Where practical, methods of extrinsic reliability detection and prevention will also be addressed. The current handbook primarily focuses on integrated circuit subjects, but can easily be adapted for use in discrete or passive device qualification with the generation of a list of failure mechanisms relevant to those components. Semiconductor device qualification is the main scope of the current handbook.
Other procedures addressing extrinsic defects are particularly mentioned in the monitoring chapter. Striving for the target of Zero Defects in component manufacturing and product use it is strongly recommended to apply this handbook. If it gets adopted as a standard, the term “shall” will represent a binding requirement.
This document does not relieve the supplier of the responsibility to assure that a product meets the complete set of its requirements.
Error and issue corrections with latest state of art updates.
|Ground Vehicle Standard||Handbook for Robustness Validation of Automotive Electrical/Electronic Modules|
|Technical Paper||A Function Failure Approach to Fault Tree Analysis for Automotive Systems|
|Journal Article||A Tool for Ensuring Consistent Occurrence Ranking in FMEAs|
Data Sets - Support Documents
|TABLE 3.1||ILLUSTRATES THE MEANING OF ROBUSTNESS VALIDATION BY CONTRASTING POSITIVE (IS) AND NEGATIVE (IS NOT) STATEMENTS|
|TABLE 4.2||EXAMPLES OF PARAMETERS OF A TWO-DIMENSIONAL ROBUSTNESS DIAGRAM|
|[Unnamed Dataset 3]|
|[Unnamed Dataset 4]|
|TABLE 9.1||REQUIRED SAMPLE SIZE FOR DIFFER ENT FAILURE TARGETS ASSUMING 90% CL|
|TABLE 15.1||EXAMPLE OF OEM VEHICLE MISSION PROFILE PARAMETERS – (HIGH-LEVEL)|
|[Unnamed Dataset 7]|
|[Unnamed Dataset 8]|
|[Unnamed Dataset 9]|
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