Ansys optiSLang Product Quality (Robust Design Optimization) - (Available as Self-paced Learning)
The course gives a short introduction to probabilistic theory and provides the background of the terms robustness and reliability. 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) has to be warranted to fulfill the requirements.
For a robustness analysis, input parameters are modelled as random variables. The result of a robustness assessment is a prognosis of the variation of the product performance in connection with the prognosis quality of the simulated system response. Moreover, the most relevant inputs influencing the scatter of the system response can be identified.
For the proof of quality or safety requirements, optiSLang offers methods of reliability analysis, which compute the rare event of exceeding a –possibly non-linear– limit state.
Following completion of this course, you will be able to:
- Introduction to Robust Design Optimization
- Conduct a variance-based robustness evaluation
- Understand the concepts of a probability-based robustness evaluation
- Basic knowledge about statistics and optiSLang is required which can be obtained by attending "Ansys optiSLang Getting Started".
Target Audience: Engineers and Designers that want to calibrate they simulation to a measurement or a desired system behavior.
Teaching Method: Lectures and computer practical sessions to validate acquired knowledge.
Self-paced Learning: Complete a class on your own schedule at your own pace. Scope is equivalent to Instructor led classes. Includes video lecture, workshops and input files. All our Self-Paced video courses are only available with an Ansys Learning Hub subscription. Register for a subscription using the tab below or contact firstname.lastname@example.org for more information.
Learning Options: Training materials for this course are available with an Ansys Learning Hub Subscription. If there is no active public schedule available, private training can be arranged. Please contact us.
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