Simulation-Driven Design for Advanced Manufacturing

Challenge:

Motorbike rear suspension pivot is redesigned for better performance, higher efficiency, and part consolidation.

Assess and benchmark designs for different manufacturing processes. 

Process:

• Identify performance requirements using kinematic motion simulation of assemblies
• Apply generative design while considering manufacturing design rules such as: casting, milling and multiple types of additive manufacturing
• Compare new designs for performance and manufacturing feasibility
• Derive geometry automatically to generate topology concept
• Validate performance and manufacturing feasibility

Result:

Best performing parts economically manufactured.

Drive Designs and Improve Manufacturing Decisions with Machine Learning

Leverage machine learning in your advanced manufacturing initiatives to improve the overall performance from design to production.

Machine learning is used by organizations to ensure that early design direction aligns with part yield, repeatability, cycle time, production planning goals and reduced costs.

Predict production performance based on specific conditions to avoid unplanned downtime on devices and enable predictive maintenance. Enable your organization to make real-time assessment and predictions with end-to-end analytic processes from data preparation over Predictive Analytics to the deployment of data models in valuable visualizations.

Visit our booth to learn more!