The above fault isolation process requires extensive knowledge of the serviced equipment;
service engineers obtain such knowledge from formal training, on-the-job training, accumulated
experience, and equipment manuals. Several trends, however, make it difficult for
service engineers to obtain and to preserve all of the knowledge required to perform their
jobs most efficiently. One such trend is the rising complexity of modern equipment. Another
is the number of different types of equipment that each engineer must service: Different
manufacturers, different models from the same manufacturer, different versions of the same
model, each one requiring a large amount of knowledge to be instantly available.
The results of these trends are increasing service costs and decreasing service quality.
Because service costs and perceived service quality have immediate and important effects
on sales and profits, many companies have decided to search for service support tools.
The application potential will vary as a function of type of diagnostic approach and by
the product technology employed, as well as by the application. For example, mechanical
and electromechanical equipment tends to fail gradually, and thus expert systems can
have value in identifying requirements for predicting the need for advance maintenance.
This preventive and predictive maintenance approach has proven to be of some value, particularly
for equipment such as heating, ventilation, and air conditioning (HVAC), medical
technology, and building automation. Diagnostics and troubleshooting for electronics
products tend to be on more of a “go-no-go basis” and therefore self-organizing systems
tend to have greater value in these applications. The overall assessment will, obviously,
change over time with new breakthroughs in the diagnostics and artificial intelligence
state of the art, and as a function of commitment to apply the technology for various types
of products and systems. From practical industry experience, it appears to be correct to
say that retrieval systems and the self-organizing systems have a role in service and that
the applicability of the technology will vary as a function of type of product (e.g., electronic,
electromechanical, or mechanical), and the stage of product use (e.g., new product
rollout versus mature product versus product being phased back). Specific examples of
technology application by company are shown in Figure 99-10.
Current Overview of Diagnostics Technology in
Field Service
In field service, a variety of new products to support diagnostics and repair decision making
have arisen as a result of extensive developments in the area of remote diagnostics
technology and artificial intelligence. These products seek to improve service-based
troubleshooting and repair capability for call and help desk-based diagnostics and call
avoidance, TAC support, and support in the field. These are shown in Figure 99-8. Fully
integrated help desk and technical assistance centers (TAC) systems are also available
separately, on a stand-alone basis or as part of an integrated field service management system
program.