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ntroduction
The importance of reliability
can be best demonstrated using an
anecdote I was told by a friend back
in 2008; when working for a major
IC firm from San Francisco, he had
received a shipment of new and
somewhat problematic desktop PCs.
Within months these PCs had started
to crash, with the IT department being
rolled in to fix the assumed operating
system gremlins and / or viruses that
were affecting these new computers –
to no effect. After much investigation,
and with many a stripped down PC,
it was eventually revealed that the
problem was caused by substandard
bulk capacitors in the ac-dc power
supply. These had deteriorated in use,
and were causing the supply rails to
be out of regulation, producing the
random crashes.
The episode highlights that, while
power supplies may not have the
glamour, nor get the attention that
processors and displays receive, they
are just as vital to system operation.
Here we look at reliability in power
supplies, how it’s measured and how
it can be improved.
Predicting the power
supply's expected life
First, a few definitions:
Reliability, R(t): The probability that a
power supply will still be operational
after a given time
Failure rate, λ: The proportion of units
that fail in a given time, note, there is
a high failure rate in the burn-in and
wear-out phases of the cycle – see
figure 1
MTTF, 1/λ: The mean time to failure.
MTBF (mean time between failures)
is also commonly used in place of
MTTF and is useful for equipment that
will be repaired and then returned
to service. MTTF is technically more
correct mathematically, but the two
terms are (except for a few situations)
equivalent and MTBF is the more
commonly used in the power industry.
A supply's reliability is a function of
multiple factors: a solid, conservative
design with adequate margins,
quality components with suitable
ratings, thermal considerations with
necessary derating, and a consistent
manufacturing process.
To calculate reliability - the probability
of a component not failing after a
given time - the following formula is
used:
For example, the probability that a
component with an intrinsic failure
rate of 10-6 failures per hour wouldn’t
fail after 100,000 hours is 90.5%,
after 500,000 this decreases to
60.6%, and after 1 million hours of
use this decreases to 36.7%.
Going through the mathematics can
reveal interesting realities. First, the
failures for a constant failure rate are
I
Back to basics - Reliability considerations in
power supplies
By CUI Inc
44 l New-Tech Magazine Europe