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A knowledge based expert system for moulded part design

Lockett, Helen and Guenov, Marin (2007). A knowledge based expert system for moulded part design. In: 16th International Conference on Engineering Design (ICED 2007), 28-31 Aug 2007, Paris, France.

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Abstract

In today's competitive market many consumer products are designed with complex curved shapes to meet customers' demands for styling and ergonomics. These styled products are commonly manufactured using moulding processes because they can produce a wide range of freeform shapes at relatively low cost. However, although injection moulding and metal casting allow a great deal of design freedom they also make significant demands on the designer to ensure that parts are designed with due regard for manufacturability. This paper describes a knowledge based moulding advisor that has been developed to provide design for moulding advice to designers during the design process. The main contributions of the research are the development of a hierarchical knowledge representation to allow moulding advice to be generated at different levels of detail and the integration of the expert system with a geometric part description extracted from a Computer Aided Design (CAD) solid model. A demonstrator for the manufacturing advisor has been implemented using the expert system shell CLIPS and integrated with CAD using feature recognition. The moulding advisor is able to generate tailored design for moulding advice for a range of manufacturing processes and materials and evaluate the manufacturability of a designed part at the feature level. The paper provides a case study for a simple moulded test part.

Item Type: Conference or Workshop Item
ISBN: 1-904670-02-4, 978-1-904670-02-5
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Engineering and Innovation
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Item ID: 49620
Depositing User: Helen Lockett
Date Deposited: 03 Aug 2017 12:32
Last Modified: 07 Dec 2018 13:10
URI: http://oro.open.ac.uk/id/eprint/49620
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