University of Huddersfield Repository Developing a Knowledge-based System for Complex Geometrical Product Specification (gps) Data Manipulation. Original Citation (2010) Developing a Knowledge-based System for Complex Geometrical Product Specification (gps) Data Manipulation. Knowledge University of

Geometrical product specification and verification (GPS) matrix system is a universal tool for expressing geometrical requirements on product design drawings. It benefits product designers through providing detailed description of functional requirements for geometrical products, and through referring to corresponding manufacturing and verification processes. In order to overcome current implementation problems highlighted in this paper, a GPS knowledge base and a corresponding innovative inference mechanism have been researched, which led to the development of an integrated GPS knowledge-based system to facilitate rapid and flexible manufacturing requirements. This paper starts with a brief introduction of GPS, GPS application problems and the project background. It then moves on to demonstrate a unified knowledge acquisition and representation mechanism based on the category theory (CT) with five selected examples of this project. The paper concludes with a discussion on the future works for this project.

[1]  Zhijie Xu,et al.  Category theory-based object-oriented data management for web-based virtual manufacturing , 2008 .

[2]  B. Nick Rossiter,et al.  Prototyping a Categorical Database in P/FDM , 1995, ADBIS.

[3]  Michael Barr,et al.  Category theory for computing science (2. ed.) , 1995, Prentice Hall international series in computer science.

[4]  Zhijie Xu,et al.  Category Theory-Based Object-Oriented Data Management for Virtual Manufacturing , 2008 .

[5]  Gerti Kappel,et al.  Database Requirements of CIM Applications , 1995, Information Management in Computer Integrated Manufacturing.

[6]  Paul J. Scott The case of surface texture parameter RSm , 2006 .

[7]  Paul J. Scott,et al.  The structure of surface texture knowledge , 2005 .

[8]  Zhijie Xu,et al.  Machining surface texture knowledge management using a category theory-based object-oriented database , 2007 .

[9]  B. N. Rossiter,et al.  The Functorial Data Model-An Extension to Functional Databases , 1994 .

[10]  Donald Firesmith,et al.  The Patterns Handbook: Techniques, Strategies, And Applications , 1998 .

[11]  P. H. Osanna,et al.  A general approach to workpiece characterization in the frame of GPS (Geometrical Product Specification and Verification) , 2001 .

[12]  Benjamin C. Pierce,et al.  Basic category theory for computer scientists , 1991, Foundations of computing.

[13]  Paul J. Scott,et al.  Pattern analysis and metrology: the extraction of stable features from observable measurements , 2004, Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[14]  Alex Ballu,et al.  Univocal expression of functional and geometrical tolerances for design, manufacturing and inspection , 1996 .

[15]  Son H. Bui,et al.  A framework for Internet-based surface texture analysis and information system , 2005 .

[16]  Michael Barr,et al.  Category theory for computing science , 1995, Prentice Hall International Series in Computer Science.

[17]  S. Maclane,et al.  General theory of natural equivalences , 1945 .