This paper describes SERF, an expert system for repairing helicopter b
lades. Although very useful, it cannot evolve automatically with advan
ces in technology and expert knowledge. To address this problem, we ha
ve designed an inductive learning system (MEA) that uses rules or prec
lassified examples in order to incrementally build production rules. T
hese rules are of the following form: if description of the fault doub
le right arrow repair and can be used by KEE (knowledge engineering en
vironment), an expert system generator. Both MEA and SERF use a repres
entation based on structured objects. In this paper some aspects of ME
A will be described, and the way MEA can extend and/or improve the ite
rative dichotomizer 3 (ID3) algorithm will be explained. MEA has been
tested on a real-life application concerning the repairing of helicopt
er blades. Results show that it is efficient, simple to use, and helpf
ul to the expert.