Maintenance of a Case-Base for the Retrieval of
Rotationally Symmetric Shapes for the Design of
Metal Castings

Tony Mileman, Brian Knight, Miltos Petridis, Keith Preddy, and Patrick Mejasson

University of Greenwich, School of Computing and Mathematics,
Park Row, Greenwich, London SE10 9LS UK
{b.knight,m.petridis}@greenwich.ac.uk



Abstract: In this paper, we discuss the problem of maintenance of a
CBR system for retrieval of rotationally symmetric shapes. The special
feature of this system is that similarity is derived primarily from graph
matching algorithms. The special problem of such a system is that it
does not operate on search indices that may be derived from single
cases and then used for visualisation and principle component analyses.
Rather, the system is built on a similarity metric defined directly over
pairs of cases. The problems of efficiency, consistency, redundancy,
completeness and correctness are discussed for such a system.
Performance measures for the CBR system are given, and the results for
trials of the system are presented. The competence of the current case-
base is discussed, with reference to a representation of cases as points in
an n-dimensional feature space, and a Gramian visualisation. A
refinement of the case base is performed as a result of the competence
analysis and the performance of the case-base before and after
refinement is compared.
References

1.	Campbell, J. Castings, Buttterworth-Heinemann, 1991
2.	Jolly, M. Overview and appraisal of numerical analysis software for the
simulation of casting processes, BICTA bulletin 3, 1996
3.	Mavis, Diana. Aiphacast software Ltd, England
4.	Simular. Aluminium Pechiney, Aluval, BP27 38340 Voreppe, France
5.	SOLSTAR. Corbett, C. F. Right first time.. .with Solstar, Foundry Practice,
Number 218, December, 1989
6.	AutoCAD. Autodesk Inc. USA.
7.	Knight, B; Cowell, D.; Preddy, K. An object-oriented support tool for the
design of casting procedures, In Engineering Applications of Artificial
Intelligence, Volume.8, Number 5, pp: 56 1-567, 1995
8.	NovaCast: Sillen, R. Using artificial intelligence in the foundry, Modem
Casting, December, 1991
9.	Ravi, B. Computer-Aided Casting Design - Past, Present and Future, Special
Issue of Indian Foundry Journal, January, 1999
10.	See p. 374, Marir, F; Watson, I. Case-based reasoning: a categorized
bibliography, The Knowledge Engineering Review, Vol.9: 4, pp: 355-381,
1994
11.	Raphael, B; Kumar, B. Indexing and retrieval of cases in a case-based design
system, Artificial Intelligence for Engineering Design. Analysis and
Manufacturing, 10, pp: 47-63, 1996
12.	Hennessy, D; Hinkle, D. Applying case-based reasoning to autoclave loading,
IEEE Expert, pp: 2 1-26, October 1992
13.	Kumar H. S.; Krishnamoorthy, C. S. Case-based reasoning in bridge design,
pp: 197-205, Advances in Computational Structures Technology, Civil-Comp
Press, Edinburgh, 1996
14.	Yeh, I. Case-Based approaches for preliminary design of steel building
frames, Microcomputers in Civil Engineering, 12, pp: 327-337, 1997
15.	Gebhardt, F. Survey on structure-based case retrieval, The Knowledge
Engineering Review, Vol.12: 1, pp: 41-58, 1997
16.	Price, C. I.; Peglar, I. S.; Ratcliffe, M. B.; McManus, A. From troubleshooting
to process design: closing the manufacturing ioop, Lecture Notes in Artificial
Intelligence. 1266, Case-based reasoning research and development. Springer-
Verlag, 1997
17.	Biederman, I.; Hummel, J. E.; Cooper, B. B.; Gerhardstein, P. C. From image
edges to geons to viewpoint invariant object models: A neural net
implementation, Applications of Artificial Intelligence X: Machine vision and
robotics, 1992
18.	Wlodawer, R Directional solidification of steel castings, Pergamon, Oxford,
1967
19.	Coulon, C. H. General geometric and topological retrieval and adaptation
(Topo). In Bomo, K, editor, Modulus for design support, Vol. 35 of Fabel
report, pp: 3 3-445, GMD, Sankt Augustin, 1995
20.	Tammer, B. C; Steinhofel, K; Schoner, 5; Matuschek, D. Anwendung des
Konzepts der strutrellen Almlichkeit zum Fallvergleich mitterls Term- und
Graph-representationen, Fabel report, 38, GMD, Sankt Augustin, 1995
21.	Bunke, H; Messmer, B. T. Similarity measures for structured representations.
In Burkhard, H. D. and Lenz, M, editors, Topics in Case-Based reasoning: First
European workshop, EWCBR-93, selected papers; Lecture notes in Artificial
intelligence, 837, pp: 106-118, Springer-Verlag. 1994
22.	Guida, G; Maui, 6. Evaluating performance and quality of knowledge-based
systems: foundation and methodology, IEEE Transactions on Knowledge and
Data Engineering, 5, 2, pp: 204-224, April 1993
23.	Preece, A. D. Towards a methodology for evaluating expert system, Expert
Systems, 7(5), pp: 14-20, 1992
24.	Racine, K; Yang, Q. Maintaining unstructured case. Proceedings of the 2nd
International Conference of Case-Based Reasoning, pp: 553-564, RI, USA,
1997
25.	Smyth, B. Case-Based Maintenance, Proceedings of the 11 th International
Conference on Industrial & Engineering Applications of At & Expert Systems.
Springer-Verlag, 1998
26.	Price, C. J.; Peglar, I. S. Deciding parameter values with case-based
reasoning, Progress in case-based reasoning (ed. Ian D. Watson), Springer-
Verlag, pp: 121-133, 1995
27.	See page 123. Price, C. J.; Peglar, I. S.; Bell, F. Case based reasoning in the
melting pot, Int. Journal of Applied Expert Systems, vol.1, no.2, pp: 120-133,
1993
28.	Hennessy, D; Hinkle, D. Applying case-based reasoning to autoclave loading,
IEEE Expert. pp: 21- 26, October 1992
