Failure Rates from Data of Field Returns - How to Prove High Reliability for Electric Components?
- 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.
| Author: | Sven-Joachim KimmerleORCID, Karl Dvorsky, Hans-Dieter Liess |
|---|---|
| URN: | urn:nbn:de:bvb:861-opus4-29421 |
| Parent Title (English): | MATHMOD 2025 (11th Vienna International Conference on Mathematical Modelling) |
| Document Type: | conferenceposter |
| Language: | English |
| Publication Year: | 2025 |
| Contributing Corporation: | TH Rosenheim; Physical Software Solutions; UniBw München |
| Conference: | 11th Vienna International Conference on Mathematical Modelling (Vienna) |
| Release Date: | 2025/02/25 |
| Tag: | automotive vehicle electrical systems; autonomous driving/intelligent autonomous vehicles; field data; modelling uncertainties and stochastic systems; reliability |
| GND Keyword: | Reliabilität; Statistik; Bordnetz |
| Page Number: | 1 |
| faculties / departments: | Fakultät für Angewandte Natur- und Geisteswissenschaften |
| Dewey Decimal Classification: | 5 Naturwissenschaften und Mathematik / 51 Mathematik |
| Licence (German): |  Creative Commons - CC BY-NC-ND - Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International |
