Research and engineering questions In the automotive industry, the reliability of products is often defined by a so-called B10-value. That means, that at a defined point in time, the maximal failure probability is 10 %. Due to the fact that the B10-value correlates to the required service, it is quite challenging to proof a service life expectation, for example 250.000 km for a passenger car, in a quite short time frame for testing activities within a product development project. During the development of products, the proof of product reliability is therefore a challenging activity. Basic planning actions have to be executed in an early design stage of the product. First of all, two possible ways for the proof of reliability are available: testing without failures and testing with failures. Within the framework of this work, the focus will be on testing without failures, also called reliability demonstration testing (rdt). Methodology At the planning phase, many questions have to be analysed to perform a reliability proof: - What is an appropriate reliability target for the product? - Decision for testing to failures or testing without failures – differences and characteristics. - What could be a useful product level for testing – system test vs. component test. - What is the probability of a successful reliability proof? - Which number of specimen and testing duration is necessary? - How to handle the unlike event of product failures while performing a rdt? - Which uncertainties have to be regarded and how to consider in the evaluation phase. The usage of statistical methods is shown to derive answers to the raised questions. Results In addition to a procedural flow of test planning, correlations between reliability requirements and various test parameters such as test duration and sample size are shown. The test quality is evaluated by the confidence level, whose dependencies are also determined. Especially uncertainties and their consequences are part of this study. One example is the estimation of the shape parameter of a Weibull distributed failure characteristic in the planning phase. Possible sources for the estimation and the consequences of uncertainties of the estimation are analyzed. After performing a rdt, the impact of uncertainties on the results are under consideration. The effects of uncertainties of the planning phase, e.g. uncertainties of the estimation of the Weibull shape parameter, to the demonstrated reliability and the confidence level are shown. Finally, case studies give an impression of the importance of the uncertainties as well as comparisons between testing to failures and testing without failures. Some hints for the practical implementation close the whole topic. Limitations of this study For targeted test planning, it must already be possible to make assumptions or estimates about the failure behavior. In the context of the investigation, the often used Weibull distribution is used to describe the product failure behavior. The procedure is transferable to other failure characteristics, which can be modeled with another type of distribution. What does the paper offer that is new in the field in comparison to other works of the author? The underlying theory is used from a practical application perspective. The statistical basics are limited to the necessary minimum, the practical challenges are in focus. At the same time, the elaboration allows in an understandable way which statistical requirements exist for a test planning and how an iterative planning process can take place. Conclusion Important elementary methodical basics for a reliability proof are shown in an understandable way. In addition, limits of what is reasonable are described.
Prof. Dr.-Ing. Tobias Leopold, Professor, Esslingen University of Applied Sciences