- Develop a robust cantilevered conical joint design, while minimizing cost and time in order to meet functional targets.
- Using Abaqus for CATIA (AFC) for structural analysis and Isight for process automation and optimization, the engineering team at Ford is able to develop an automated Design of Experiments process to eliminate design inefficiencies and allow them to complete their analysis in four days rather than an estimated 70 days.
- Utilizing AFC and Isight, the Ford engineering team was able to achieve their project goals in a fraction of the time it would have otherwise taken. Their initial time investment in completely automating the testing process will save them countless weeks of development time in the future.
Modern Methods for Optimal Engineering
Developing high-quality bolted joints is an integral part of vehicle chassis design. While less understood than the design of connecting members, such as a toe-link that connects the sub frame to the knuckle, robust joints are critical to improving handling and longevity of vehicle performance. Joints that are loose tend to exacerbate quality issues such as alignment, and ultimately the durability of the joined components. A properly designed joint is more efficient and can support larger loads with smaller size fasteners without loosening.
Engineers at Ford Motor Company were tasked to deliver a robust cantilevered conical joint design for the rear suspension system of a midsize passenger car (see Figure 1). To minimize time and cost while meeting functional targets, the team developed an automated Design of Experiments (DOE) process using Abaqus for CATIA (AFC) for structural analysis and Isight for process automation and optimization.
“Our team chose AFC in order to deploy standard stress modeling and simulation practices in the form of templates to a broader group of engineers within the design organization,” says Satyendra Savanur, chassis CAE engineer at Ford. ”Linking Isight with AFC enabled us to develop a powerful and automated design analysis methodology. We used response surface model, one of the approximation models, for finding optimal parameters to size the joint.”
It is estimated it would have taken approximately 70 days to complete all 35 runs, while maintaining other day-to-day work; we completed this task in about four days.
|Just how did Isight effect unprecedented design efficiency at Ford?
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