ASME TEC TALK: Transforming Design and Manufacturing with AI and Machine Learning

May 12, 2021

Janis Terpenny
The next TEC Talk, a monthly one-hour webinar series exclusively for ASME members, will be presented on Thursday, May 27, at 12:00pm EST by ASME’s Materials Division.

Conrad Tucker
From design to manufacturing, artificial intelligence (AI) and machine learning (ML) provide tremendous possibilities for improving efficiency, profitability, and safety while accelerating the pace of engineering discovery. In manufacturing, AI and ML provide the ability of machines to learn and perform tasks. They can make sense of large sets of data to detect patterns, organize information, identify relationships, make predictions, detect anomalies, support robotics, and automate processes. In design, a key transformation and opportunity is the ability for human designers to work in collaboration with AI/ML to conduct design activities.  Co-design or co-creation assists human designers in efficiently generating and exploring candidate solutions to challenging engineering problems that often resist other solution strategies.

Paul Witherell
This webinar will first provide a background on the AI/ML tools and algorithms that are being leveraged by today's engineering designers. We will then hear from experts in the field on how these co-design strategies can be applied in design, manufacturing, and additive manufacturing. This will lead into a discussion on the future directions and opportunities as well as federal government investments in the area, including additive/smart manufacturing, healthcare devices, photonics, energy production, and light-matter interactions, such as in quantum hardware. The panelists will take questions from the audience to conclude the event.

Mark Fuge
The speakers for this webinar include Dr. Paul W. Witherell, mechanical engineer in the Life Cycle Engineering (LCE) Group of the Systems Integration Division (SID) of the Engineering Laboratory (EL) at the National Instituteof Standards and Technology (NIST); Conrad Tucker, Arthur Hamerschlag Career Development Professor of Mechanical Engineering with courtesy faculty appointments in machine learning, robotics, andbiomedicalengineering at Carnegie Mellon University; Janis Terpenny, professor in Industrial and Systems Engineering and on leave as the dean and Wayne T. Davis Dean’s Chair of the Tickle College of Engineering at the University ofTennessee, Knoxville; and Mark Fuge, assistant professor of mechanical engineering at the University of Maryland, College Park, where he is also an affiliate faculty in the Institute for Systems Research and a member of the Maryland Robotics Center and Human-Computer Interaction Lab.

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