Common Cause is one of those variables that is not always considered important when it comes to SIL compliance.  And yet, for redundant systems, it can have a significant impact on the PFDavg and Risk Reduction achieved (in Low Demand mode) or PFH (in high or continuous mode).  Most of the time redundant systems are not always in separate cabinets and so are exposed to the same potential common cause, influences, such as excessive heat, vibration, shock, and moisture, for example.  Moreover, when it comes to hot-standby systems, these have the same redundant, controllers in the same chassis, sharing a common backplane, which is also not always considered from a common cause aspect.

When considering a redundant 1oo2 system, if we take a simple example using Fault Trees and simplified equations and perfect proof test (for comparison purposes only):

Using simplified equations and perfect proof test (T), where to illustrate the difference.   is the portion of the dangerous failure rate associated with the common cause contribution and   is the independent portion of the dangerous failure rate, the simplified formula changes:

From this we can see that the common cause will impact the PFDavg in a negative way (I.e. will increase the PFDavg).  Therefore, we cannot ignore the common cause effect on the PFDavg of a redundant system.  The common cause is defined as the Beta Factor and is represented as the Greek symbol β and represents the fraction of the failure rate where two or more failures will occur due to a common stress, usually represented as λcc = βλ.  The IEC61508 standard, part 6 Annex D6, lists the Beta Factor as 0.005 to 0.05 for programmable electronic equipment and 0.01 to 0.1 for field equipment.  If using the exSILentia tool for SIL calculations, it automatically defaults to 10% (0.1).

Therefore, it is important to include a Beta Factor when calculating the PFDavg or PFH for a redundant set of equipment, otherwise we could be overstating the amount of risk reduction being provided by the Safety Instrumented Function (SIF) and thereby leading to overly optimistic results.

If this blog has piqued your interest, then look out for the upcoming “exida Explains…” video.

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