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Dealing with the design complexity of cyber-physical products and smart interconnected systems of systems is driving the need for increased use of advanced digital modeling, simulation, and multi-disciplinary analysis and optimization (MDAO) augmented with AI/Machine Learning predictive analytics technologies.

Industry leaders use MDAO and process automation to enable design innovation, reduce overall product design costs, minimize rework and manufacturing defects, and optimize in-service operational performance and costs. Engineers can now define and apply multi-disciplinary MDAO and data analytics starting earlier in the conceptual design and development phase, as well as applied in manufacturing and in-service operations to enable combined physics and ML-based “hybrid digital twins.”

This webinar will review how a low code collaboration environment enables the capture, automation, and continuous refinement of best practices for performance simulation and collaborative design optimization.

Who Should Attend?

• VP Engineering and Engineering program management
• Physics-based simulation/analysis functions/CAE expert users who directly report to engineering management (e.g., R&D director)
• Predictive analytics / Machine-learning experts
• PLM/engineering process management
• CIOs/CTOs and IT management
• Product design and development staff
• Industry 4.0 experts involved in Digital Twins strategies for the monitoring of physical assets

Why Attend?

• Get the latest view of design innovation initiatives status from the viewpoint of industry professionals.
• Understand the speed of change in the industry in the use of CAE process automation & MDAO tools.
• Cut through the buzz around Cloud, MDAO and AI/ML adoption and receive actionable insights.
• Understand the disruptive paradigm of low-code collaborative engineering environments.
• Understand benefit of combining data science and Multiphysics simulation to produce more accurate Digital Twins.