Patdex is an expert system which carries out case-based reasoning for the fault diagnosis of complex machines. It is integrated in the Moltke workbench for technical diagnosis, which was developed at the university of Kaiserslautern over the past years, Moltke contains other parts as well, in particular a model-based approach; in Patdex where essentially the heuristic features are located. The use of cases also plays an important role for knowledge acquisition. In this paper we describe Patdex from a principal point of view and embed its main concepts into a theoretical framework 1 General Considerations Patdex 1 is an expert system which carries out case-based reasoning for the fault diagnosis of complex machines. It is integrated in the Moltke workbench 2 for technical diagnosis, which was developed at the university of Kaiserslautern over the past years (cf. e.g. [4, 5, 23]), Moltke contains other parts as well (cf. e.g. [16]), in particular a model-based approach (cf. [21, ...

Abstract. We propose in this paper a general framework for integrating inductive and case-based reasoning (CBR) techniques for diagnosis tasks. We present a set of practical integrated approaches realised between the KATE-Induction decision tree builder and the PATDEX case-based reasoning system. The integration is based on the deep understanding about the weak and strong points of each technology. This theoretical knowledge permits to specify the structural possibilities of a sound integration between the relevant components of each approach. We define different levels of integration called "cooperative", "workbench " and "seamless". They realise respectively a tight, medium and strong link between both techniques. Experimental results show the appropriateness of these integrated approaches for the treatment of noisy or unknown data. 1