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State-of-the-Practice
Fault diagnosis at PMS
2.4 Optimal Fault Diagnosis
2.4.2 Evaluation Current Approach
Throughout the years the diagnostic performance steadily became suboptimal. When the first
Cardio-Vascular systems were placed in hospitals, the systems could easily be diagnosed and repaired
manually. There was only one power supply, a couple of cables, and the more complex
components could be manually measured quite easily. Almost all functionality was implemented
by hardware. Therefore, analog measuring was the most efficient way for diagnosing these systems.
The skills and knowledge of service engineers perfectly fitted the diagnostic tasks. However, ever
since, various trends have changed the situation:
1. Increased complexity, caused by evolved techniques and additional functionality.
2. a shift from a hardware-centric to software-centric embedded system.
3. An increased number of third party components.
These trends have decreased the presence of the items that an ideal approach should have. These
items are used as criteria to evaluate the current approach, as follows:
• Accuracy. The current process and available tools do not allow the determination of how
accurate the diagnosis is. For this, it should be known if a replacement of the diagnosed
FRU recovered the failure, and this information is not available. The only way to estimate the
accuracy, is to examine job sheets for reoccurrence of problems, or to interview troubleshooters
for their experiences. Both sources make it plausible that today’s diagnostic process is
not very accurate, unless failures are known and very well understood. Unfortunately, it is
impossible to quantify this attribute with the current techniques.
• Speed of diagnosis. The Speed of diagnosis can be measured by recording the time between
the moment that a failure occurs and the moment that a troubleshooter isolates the root cause
of that failure. In the current situation it can be recorded per failure, by interviewing operators
and examining job sheets. The period is several days in case of a mainstream problem. Otherwise
the problem has to be escalated through one or more of the help desks (recall Figure
2.3) and could take weeks, if not months.
• Low Uncertainty. The uncertainty of today’s diagnoses is, like the accuracy, hard to determine.
Again, only job sheets and interviews can give some insights. These indicate that
the certainty of service engineer is disputable in many cases. However, it is not possible to
quantify this because the job sheets do not provide a list of possible diagnoses.
• Context Independency. Section 2.3.1 described the actions that employees perform for solving
a failure of the power supply. It shows that, nowadays, many diagnostic knowledge depends
on current employees. Therefore, reliance on many people is seen as a drawback of
the current approach. It indicates strong environmental influences on the diagnostic process;
if people change jobs, the diagnostic capabilities within the organization degrades. Consequently,
the current practice is not very independent of its environment.
• Development Costs. The development costs of a diagnostic process that aims at maintaining
complex systems, such as the Philips Cardio-Vascular X-Ray System, are expected to be very
high, and so they are. So, any qualification is always relative to other approaches. The exact
development costs are not examined, but it is known that the development costs typically
outweigh the runtime costs.
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