Towards intelligent engineering design systems

Assuring the quality of design descriptions through the use of design configuration spaces
(Link to project web site)

Mission of the project

The quality of design descriptions, such as the technical data packages that are developed through engineering product development processes, has a significant impact on the performance of a product through its life. The aim of this project was to establish theoretical foundations for the reconfiguration of bills of materials (BoMs) with a view to assuring the consistency of technical data packages when the structures and compositions of design descriptions are modified for use in specific engineering or downstream activities.

In the first year of the project (2018/19) we produced a video to provide an overview of the problem we were addressing and the ways in which we intended to address it.

Through the project we explored the application of two core technologies to the problem of design configuration:

  • given a collection of parts, lattice theory was used to generate a representation of all possible configurations which, in turn, was used to enable the definition of new configurations (BoMs) that, as a collection, were self-consistent with each other and the initial collection of parts; and

  • given a collection of part shapes, machine learning was used to cluster these shapes, so enabling users to select shapes that were similar to each other.

Together these informed work in the area of organisational psychology and human factors on requirements for design configuration tools and perspectives on shape similarity.

The project brought together expertise from three academic disciplines (engineering design, machine learning and human factors) as illustrated below.

The project resulted in deeper understanding of the problem of design configuration, the potential of machine learning as a technology in the development of engineering design tools, and how such technologies might be used in engineering product development processes to improve the efficiency and effectiveness of such processes. New knowledge and capabilities in the following areas are introduced in this web site: