Diagnosis using neural nets

Abstract

Diagnosis is an important part of the product quality assurance cycle. The construction of diagnosis systems with neural nets, which solves problems hitherto unsolved, creates effective real-time opportunities, and a new level of robustness is discussed. The application of neural nets is illustrated in three examples. The first example shows how the effect of medication can be diagnosed. The other two involve automotive applications. They were derived from industrial products created by Expert Informatik GmbH over the years 1989 to 1992.<>