The course introduces robustness and reliability assessments by probabilistic methods and the relation to sigma level or design for six sigma approaches. The application of robustness and reliability assessments will be demonstrated by using an application example of an optimized design.
Virtual product development is conducted using deterministic parameters, hence under idealized conditions. Particularly in the context of product optimization, the product performance under random influences (tolerances, external influences) must be warranted.
For a robustness or reliability analysis, input parameters are modelled as random variables. The result of a robustness assessment is a prognosis of the variation of the product performance. Moreover, a root cause analysis is possible by identifying the most relevant inputs influencing the scatter of the system response.
Strategies for finding optimal yet robust designs are discussed.
For the proof of safety requirements, optiSLang offers methods of reliability analysis, which compute the rare event of violating a –possibly non-linear– limit state.
- Basic knowledge about statistics
- Skills to conduct process integration and optimization in optiSLang
- Required prerequisites can be obtained by attending "Ansys optiSLang Getting Started".
Engineers who want to optimize a design and assure product quality under random influences.
Lectures and computer practical sessions to validate acquired knowledge.