8.6 Degree of Modeling Accuracy

All reliability analyses are based on failure rate data. It must be recognized that such data is highly variable. Allegedly identical components operating under supposedly identical environmental and operating conditions are not realistic assumptions. For a given level of detail, the apparent precision offered by certain modeling methods is not compatible with the accuracy of the failure rate data. As a result, it may be concluded that simplified assessments and the use of relatively simple models will suffice. More accurate predictions can be both misleading, as well as a waste of time, money, and effort. In any engineering discipline, the ability to recognize the degree of accuracy required is of the essence. Since reliability parameters are of wide tolerance, judgments must be made on one-, or at best two-, figure accuracy. Benefits are obtained from the judgment and subsequent follow up action, not from refining the calculations. [ ^[4]] Simplifications and approximations are useful when they reduce complexity and allow a model to become understandable. [ ^[14]] For example, if a simple model indicates the risk reduction factor of a system is 55, there's little point in spending an order of magnitude more time and effort, or hiring an outside consultant, to develop a model that indicates the risk reduction factor is 60. Both answers indicate the middle of the SIL 1 range (i.e., a risk reduction factor between 10 and 100).