This paper presents a conceptual framework for the development of Knowledge Management (KM) systems to support experts in complex design activities. Designing a complex object is not simple, since it is concerned not only with problem solving issues, but also with the needs for capturing and managing the core knowledge involved in it. A complex object is typically made of a huge number of parts that are put together according to a first set of constraints (i.e. the dynamic knowledge or functional knowledge), dependable on the functional properties it must satisfy, and a second set of rules, dependable on what the expert thinks abut the problem and how he/she would represent it (i.e. the static knowledge or ontological knowledge). The paper introduces how to unify both types of knowledge, exploiting the SA-Nets formalism to capture the dynamic knowledge and an ontological approach to represent static knowledge.
Colombo, E., Colombo, G., Sartori, F. (2005). Managing Functional and Ontological Knowledge in the Design of Complex Mechanical Objects. In S. Bandini, S. Manzoni (a cura di), AI*IA 2005: Advances in Artificial Intelligence 9th Congress of the Italian Association for Artificial Intelligence Milan, Italy, September 21-23, 2005, Proceedings (pp. 608-611). Springer [10.1007/11558590_62].
Managing Functional and Ontological Knowledge in the Design of Complex Mechanical Objects
COLOMBO, ETTORE;COLOMBO, GIANLUCA;SARTORI, FABIO
2005
Abstract
This paper presents a conceptual framework for the development of Knowledge Management (KM) systems to support experts in complex design activities. Designing a complex object is not simple, since it is concerned not only with problem solving issues, but also with the needs for capturing and managing the core knowledge involved in it. A complex object is typically made of a huge number of parts that are put together according to a first set of constraints (i.e. the dynamic knowledge or functional knowledge), dependable on the functional properties it must satisfy, and a second set of rules, dependable on what the expert thinks abut the problem and how he/she would represent it (i.e. the static knowledge or ontological knowledge). The paper introduces how to unify both types of knowledge, exploiting the SA-Nets formalism to capture the dynamic knowledge and an ontological approach to represent static knowledge.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.