Over the last decade, there has been a significant increase in the development, application,
and use of advanced diagnostics and artificial intelligence technology in field service.
Research* carried out in the early 1980s, in fact, showed that service problem
diagnostics could result in avoidance of between 30% and 35% of all on-site field service
calls, and that in-depth diagnostic evaluation could significantly reduce the number of
“broken” field service calls through more intelligent dispatch and assignment of both
parts and service engineers (Blumberg, 1984). Since that discovery, there has been a great
deal of work carried out attempting to both develop and apply advanced diagnostics technology
in the field service industry. It is, therefore, of value to examine both the current
state-of-the-art and the experience in the application and use of problem diagnostics and
resolution technology in the health equipment field service industry, as well as to pragmatically
explore both the successes and failures of artificial intelligence and advanced
remote diagnostics and decision support methodology in service. This analysis is summarized
in this report.