TY - GEN
T1 - Multi-Condition Methodology for Stress Determination in the Reliability Assessment of Electrical Components
AU - Aksu, Osman
AU - Youn, Jeongik
AU - Schmid, Michael
AU - Bierwirth, Florian
AU - Radosavac, Misel
AU - Herzog, Hans Georg
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - This paper presents an extended methodology for calculating Failure In Time (FIT) rates for automotive electronics, building upon Siemens Norm 29500. Many calculations rely on a single operating point, typically a worst-case scenario or an average value. For convex stress functions, a purely worst-case assumption can significantly overestimate the FIT rate, while using an average may lead to underestimation. The proposed approach incorporates multiple distinct operating conditions, each weighted by its respective share of operating time. A method for identifying and consolidating these different operating ranges based on analog sensor data is introduced. Mathematical analyses show that the resulting FIT rate can be lower than that obtained by a single worst-case value or higher than a simple average assumption, thus aligning more closely with real operating profiles. This provides significant potential for optimizing costs and development times without compromising the required safety standard.
AB - This paper presents an extended methodology for calculating Failure In Time (FIT) rates for automotive electronics, building upon Siemens Norm 29500. Many calculations rely on a single operating point, typically a worst-case scenario or an average value. For convex stress functions, a purely worst-case assumption can significantly overestimate the FIT rate, while using an average may lead to underestimation. The proposed approach incorporates multiple distinct operating conditions, each weighted by its respective share of operating time. A method for identifying and consolidating these different operating ranges based on analog sensor data is introduced. Mathematical analyses show that the resulting FIT rate can be lower than that obtained by a single worst-case value or higher than a simple average assumption, thus aligning more closely with real operating profiles. This provides significant potential for optimizing costs and development times without compromising the required safety standard.
KW - automotive electronics
KW - FIT rate calculation
KW - fleet data integration
KW - multi-condition modeling
KW - reliability analysis
KW - sensor signal clustering
KW - Siemens Norm 29500
UR - https://www.scopus.com/pages/publications/105015500746
U2 - 10.1109/ZINC65316.2025.11103549
DO - 10.1109/ZINC65316.2025.11103549
M3 - Conference contribution
AN - SCOPUS:105015500746
T3 - 2025 IEEE Zooming Innovation in Consumer Technologies Conference, ZINC 2025
SP - 64
EP - 69
BT - 2025 IEEE Zooming Innovation in Consumer Technologies Conference, ZINC 2025
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2025 IEEE Zooming Innovation in Consumer Technologies Conference, ZINC 2025
Y2 - 28 May 2025 through 29 May 2025
ER -