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.
