Improving the Quality of Case Bases for Building Better Decision Support Systems
Proceedings of the Fifth German Workshop on CBR: Foundations, Systems, and Applications (Technical Report LSA-97-01E), University of Kaiserslautern, Department of Computer Science, (1997)Abstract
Time spent by airline maintenance operators to solve engine
failures and the related costs (flight delays or cancellations)
are a major concern to SNECMA which manufacture engines for
civilian aircraft such as BOEING 737s and Airbus A340s. The use
of CBR and Data Mining software contributes to improving customer
support and reduces the cost of ownership by increasing
troubleshooting accuracy and reducing airplane downtime. However,
CBR and Data Mining systems must obey the quality requirements of
the aeronautic industry. Our aim is to both assure the quality of
the core data mining and CBR software as well as the quality of
the technical information that is fed into the system (case
knowledge). The work achieved had helpded us improve the process
by which we develop quality decision support software by
obtaining better case descriptions and setting up an organization
to monitor their quality. The experience gained in the aircraft
industry contributes to raise the case quality culture for CBR
and data mining and will enable large scale deployment of these
technologies in other industries as well.