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Design as a Marked Point Process

Quigley, John; Vasantha, Gokula; Corney, Jonathan; Purves, David; Sherlock, Andrew

Authors

John Quigley

Jonathan Corney

David Purves

Andrew Sherlock



Abstract

Although AI systems which support composition using predictive text are well established there are no analogous technologies for mechanical design. Motivated by the vision of a predictive system that interactively suggests features to designer, this paper describes the theory, implementation and assessment of an intelligent system that learns from a family of previous designs and generates inferences using a form of spatial statistics.
The formalism presented, models 3D design activity as a `Marked Point Process' that enables the probability of specific features being added at a particular locations to be calculated. Because the resulting probabilities are updated every time a new feature is added the predictions will become more accurate as a design develops. This approach allows the cursor position on a CAD model to implicitly define a spatial focus for every query made to the statistical model. The authors describe the mathematics underlying a statistical model that
amalgamates the frequency of occurrence of the features in the existing designs of a product family.
Having established the theoretical foundations of the work, a generic six step implementation process is described. This process is then illustrated for circular hole features using a statistical model generated from a dataset of hydraulic valves. The paper describes how the positions of each design's extracted hole features can be homogenized through rotation and scaling. Results suggest that within generic part families (i.e. designs with common structure) a marked point process can be effective at predicting incremental steps in the development of new designs.

Citation

Quigley, J., Vasantha, G., Corney, J., Purves, D., & Sherlock, A. (2022). Design as a Marked Point Process. Journal of Mechanical Design, 144(2), Article 021713. https://doi.org/10.1115/1.4052844

Journal Article Type Article
Acceptance Date Aug 20, 2021
Online Publication Date Dec 6, 2021
Publication Date 2022-02
Deposit Date Sep 3, 2021
Publicly Available Date Dec 6, 2021
Print ISSN 1050-0472
Electronic ISSN 1528-9001
Publisher American Society of Mechanical Engineers
Peer Reviewed Peer Reviewed
Volume 144
Issue 2
Article Number 021713
DOI https://doi.org/10.1115/1.4052844
Keywords Feature based Design, Predictive Design, Marked Point Process
Public URL http://researchrepository.napier.ac.uk/Output/2763969
Publisher URL https://asmedigitalcollection.asme.org/mechanicaldesign

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