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Company:

PROTON

Products:

Adams
FEA, AFEA and TFEA
MSC Nastran
Patran

Industries:

Automotive

Overview:
PROTON develops mechanical and structural components, sub systems and complete vehicle systems.
Challenge:
In developing complex mechanical and structural automotive components, going through multiple build-and-test hardware prototype cycles to verify performance, stress and fatigue life is just too timeconsuming and expensive. This issue can be addressed by evaluating and refining designs with analysis tools up front in development, reducing test cycles later in the development process. PROTON’s pioneering spirit naturally has led Mr ismail to not just stop at traditional methodologies in computer-aided engineering for design analysis. As the risk of failure in any design was becoming more and more significant and he was constantly looking at areas to assess risk parameters and minimize any risk factors, he needed to turn to industry-leading simulation analysis tools that would be able to provide him with the necessary accurate foundation to progress his methodology. Mr. Ismail realized that conventional virtual development approaches are no longer sufficient to meet the increasing standards of accuracy required at PROTON. Conventional approaches do not take into consideration the variations that affect finite element analyses. Mr. Ismail needed proven tools that produced the most accurate results, allowing him to capture the potential failures and provide the nature of failures so that these can be mitigated in the process. With resource efficiency on his mind, Ms Ismail also needed to manage test accuracy while reducing the dependency on running too many variations.
Solution:
With MSC, Mr. Ismail was able to conduct multi- run design improvement studies which can be used to assess design sensitivity to product and environment variability, discover unknown design variable interactions, and provide a global view of the overall design space.
Benefits:
  • Visible quantification of design risk or reliability
  • Identifies areas of high risk in a design
  • Provides the ability to modify design variables relative to reliability
  • Provides a means to compare differing designs

 
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