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

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, September). Towards Predictive Design: Tracking a CNC Fixture Design Process to Identify the Requirements. Presented at International Conference on Manufacturing Research ICMR 2022, Derby, UK

• Presentation Conference Type: Conference Paper (published)
• Conference Name: International Conference on Manufacturing Research ICMR 2022
• 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: Jun 22, 2022
• 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