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Towards Predictive Design: Tracking a CNC Fixture Design Process to Identify the Requirements

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

Authors

David Purves

Jonathan Corney

Michael Canavan

John Quigley

Andrew Sherlock



Abstract

Training novice production engineers to design manufacturing fixtures is a time-consuming process involving significant input from experienced experts. Motivated by the vision of providing an intelligent support system for general mechanical design, this paper develops a list of requirements for predictive suggestion mechanisms focused on creating fixtures for holding components during machining. To do this, the email communications between nine novices and one expert during the design of machining fixtures were studied. The analysis classified the expert’s feedback into ten coded themes. The significance of these themes was assessed by quantifying the resulting changes in the CAD models of the fixtures designs and fixture requirements. The identified results lay the foundation for developing a comprehensive CAD predictive suggestion system to support fixture design. Novice designers will benefit from this predictive suggestion system by correcting their design errors in real-time and reducing the need for experts’ time in the training process.

Citation

Vasantha, G., Purves, D., Corney, J., Canavan, M., Quigley, J., & Sherlock, A. (2022). Towards Predictive Design: Tracking a CNC Fixture Design Process to Identify the Requirements. In Advances in Manufacturing Technology XXXV (187-192). https://doi.org/10.3233/atde220589

Conference Name International Conference on Manufacturing Research ICMR 2022
Conference Location Derby, UK
Start Date Sep 6, 2022
End Date Sep 8, 2022
Acceptance Date May 25, 2022
Publication Date Nov 8, 2022
Deposit Date Jun 22, 2022
Publicly Available Date Mar 28, 2024
Publisher IOS Press
Pages 187-192
Series Title Advances in Transdisciplinary Engineering
Series Number 25
Book Title Advances in Manufacturing Technology XXXV
ISBN 978-1-64368-330-0
DOI https://doi.org/10.3233/atde220589
Keywords Predictive design, fixture design, CAD suggestion system
Public URL http://researchrepository.napier.ac.uk/Output/2881101

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