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, ...

this paper we focus on a deep integration of these technologies. First, we motivate our approach on a more intuitive basis. Chapter 2 results in a more or less concrete guideline for integrating inductive and case-based reasoning based on mechanisms known from the field of information retrieval. We introduce multidimensional retrieval structures for associative search, especially k-d trees and describe the basic algorithms for tree construction and search. These basic data structures and algorithms are then extended to meet all the requirements of real complex diagnostic problems. Finally, we discuss our approach from several scientific points of view. 2 Inductive and Case-Based Reasoning