We were honored to have Narayana Venugopal from Ford Motor Company present and share his presentation at the 2022 SIMULIA Great Lakes Regional User Meeting, June 8, 2022.
Abstract: Ford Motor Company is conducting fundamental operational changes via Ford+ initiative, with focus on modernization and simplification, while leveraging our strengths. A two-prong approach for our team is to drive our ICE (internal combustion engine) success, while in parallel thinking like a start-up, to develop a leading-edge technology company we call Ford Model e. Flexible Vehicle Architectures are at the foundation of Ford+ plan. The success of these Architectures is dependent on our “Hardware at the speed of software” approach, which we are executing via the Design Framework vision. Our success will be dependent on the development of analytical methods and tools replace hardware tests and automating the workflow of these methods to expedite the validation. AI and machine learning technologies will play a key role in our quest to expedite our decision-making. There is a dire need for software suppliers to recognize this opportunity and provide tools allowing seamless transition for our engineers to the deep learning environment of every aspect of our business, including simulation. Ultimately, such toolsets, when coupled with correlated analytical design methods, will drive significant product development efficiency gains benefiting our customers, our company, and our employees. The presentation will lay out our vision, progress to date with some examples and additional enablers needed.
Biography: As the global Underbody Systems CAE Manager at Ford, Narayana VENUGOPAL is responsible for chassis, transmission, and driveline CAE. The team footprint spans the U.S., Mexico, Germany, England and India with expertise in FEA, CFD, hydraulics, MBD and VSA and a focus on CAE for metals and plastics. Narayana has been with Ford for 28 years, 30 years in the automotive industry and 3 years in Aerospace, having worked in Japan, Mexico and India. He is a strong believer in automation, AI and ML applied to engineering processes. Narayana holds a Masters degree in Mechanical Engineering and is pursuing a Master degree in in Computer Science with a specialization in Machine Learning.
RUM2022 RUM2022-GreatLakes
