AI and knowledge-based design optimisation in high value manufacturing industries

Design traditionally follows an iterative process of applying a set of widely used tools and methodologies across all sectors. It is heavily reliant upon the designers personal knowledge, experiences, and information available such as design tools, industrial sectors, manufacturing processes, standards, patents, legislation, suppliers etc. However, the main drawbacks of the current design process are that it is often inherently slow, with the final design outcome being inconsistent and heavily influenced by the designers/engineers’ background and preferences, hence many designs are typically far from optimal. In contrast, designs from the natural world that have evolved (iterated) over millions of years have repeatedly been shown to be both multidisciplinary and optimal. This has led to the growing field of Biomimicry, where mankind adopts nature’s design rules to similar problems. The Biomimicry approach combined with the artificial Intelligence (A.I.) offers a huge opportunity for the design community to step towards optimised designs.

This research will investigate the feasibility of how A.I., through Biomimicry and algorithm-driven design can improve and optimise the design process in high value manufacturing industries. The work will define how A.I. will learn and how it will interrogate and make use of available information in order to create truly optimised solutions in a cyber-physical environment. This project will build on existing scholarly research and would aim to attract additional industry support. This research will primarily target industrial design problems commonly identified in high value manufacturing and design industries.