In an increasingly competitive marketplace system complexity
continues to grow, but time-to-market and lifecycle are reducing. The
purpose of fault diagnosis is the isolation of faults on defective
systems, a task requiring a high skill set.This
has driven the need for automated diagnostic tools. Over the last two
decades, automated diagnosis has been an active research area, but the
industrial acceptance of these techniques, particularly in
cost-sensitive areas, has not been high.This
paper reviews this research, primarily covering rule-based,
model-based, and case-based approaches and applications. Future
research directions are finally examined, with a concentration on
issues, which may lead to a greater acceptance of automated diagnosis.Increasing
costs, shorter product lifecycles, and rapid changes in technology are
driving the need for automated diagnosis. Although research has been
active over the last two decades, much remains to be done.Primarily,
the developed techniques must be scaled up to deal with current and
future technologies but with improved development times and costs.
Otherwise, acceptance will be difficult, particularly in cost sensitive
domains, such as PCs and consumer electronics.To
date, there have been some applications, but the general use of
intelligent diagnostic solutions for electronic system diagnosis has
yet to happen..