TY  - CPAPER
U1  - Konferenzposter
A1  - Kimmerle, Sven-Joachim
A1  - Dvorsky, Karl
A1  - Liess, Hans-Dieter
IN  - TH Rosenheim; Physical Software Solutions; UniBw München
T1  - Failure Rates from Data of Field Returns - How to Prove High Reliability for Electric Components?
T2  - MATHMOD 2025 (11th Vienna International Conference on Mathematical Modelling)
N2  - To determine failure rates is a challenge, if there are only a few failures and a low failure rate should be checked. As an application example, we are interested in failure rates of electrical automotive components for automated/autonomous driving. Basically, three methods are common: (i) exploitation of field data, (ii) standardized handbooks with failure rates, e.g. the FIDES guide, and (iii) laboratory long term exposure tests. We discuss shortly the (dis)advantages of each method and focus on the statistics behind method (i). Moreover, our poster sketches how this can be applied to data as available in industry.
AB  - To determine failure rates is a challenge, if there are only a few failures and a low failure rate should be checked. As an application example, we are interested in failure rates of electrical automotive components for automated/autonomous driving. Basically, three methods are common: (i) exploitation of field data, (ii) standardized handbooks with failure rates, e.g. the FIDES guide, and (iii) laboratory long term exposure tests. We discuss shortly the (dis)advantages of each method and focus on the statistics behind method (i). Moreover, our poster sketches how this can be applied to data as available in industry.
KW  - Reliabilität
KW  - Statistik
KW  - Bordnetz
KW  - modelling uncertainties and stochastic systems
KW  - automotive vehicle electrical systems
KW  - reliability
KW  - autonomous driving/intelligent autonomous vehicles
KW  - field data
Y1  - 2025
U6  - https://nbn-resolving.org/urn:nbn:de:bvb:861-opus4-29421
UN  - https://nbn-resolving.org/urn:nbn:de:bvb:861-opus4-29421
SP  - 1
ER  -