AI-Based Design of Industrial Components for Next-Gen Industry
Speaker: David Howard – Brisbane, QLD, AustraliaTopic(s): Artificial Intelligence, Machine Learning, Computer Vision, Natural language processing , Graphics and Computer-Aided Design
Abstract
Generative machine learning is poised to revolutionise the design of a range of sectors where rational design has long been the de facto approach: where design is practically a time consuming and frustrating process guided by heuristics and intuition. In this talk we focus on industrial design, which is an ideal candidate for generative design approaches and is crying out for modern design solutions as industry aims to find low-emission, high-performance solutions. We walk through a generative machine learning framework that optimises diverse, bespoke devices for modern industries including membrane filtration and flow chemistry. The approach combines techniques from high-throughput drug discovery, physics modelling, 3D printing, and Bayesian optimisation. We show the critical role of computational modelling and experimental assessment in creating high-throughput and physically-performant devices. In the case of flow chemistry, we show how this approach yields the discovery of never-before-seen bespoke devices whose performance exceeds the state of the art by 45%. These findings highlight the power of autonomous generative design to improve the operational performance of complex functional structures, with potential wide-ranging industrial applications. From closing the reality gap to describing and searching huge multi-dimensional spaces, this presentation covers the what, the why, and the how, of using computational design and artificial intelligence for real world optimisation problems.
About this Lecture
Number of Slides: 40 - 100Duration: 40 - 120 minutes
Languages Available: English
Last Updated:
Request this Lecture
To request this particular lecture, please complete this online form.
Request a Tour
To request a tour with this speaker, please complete this online form.
All requests will be sent to ACM headquarters for review.