This commentary examines the consequences, from a system perspective, of modeling system components using only their failure-rates, viz, the inverse of their MTTF, when, in actuality, they have a lifetime distribution with either an increasing or a decreasing hazard function. Such models are often used because: they are tractable; they are thought to be "robust;" they depend only on average values; or only small amounts of data are available for calculations. However, the results of such models can greatly understate the system-reliability for some time periods and overstate it for others. Using MTTF as a figure of merit for system-reliability can be especially misleading. Furthermore, the redundancy in a redundant system might provide very little of the reliability improvement predicted by the constant failure-rate model, and series systems might, in fact, be much more reliable than predicted. The overall result is that a constant failure-rate model can give very misleading guidance for system-design.

The analysis of system reliability often requires the use of subjective-judgments, uncertain data, and approximate system models. By allowing imprecision and approximate analysis fuzzy logic provides an effective tool for characterizing system reliability in these circumstances; it does not force precision where it is not possible. Here we apply the main concepts of fuzzy logic, fuzzy arithmetic and linguistic variables to the analysis of system structures, fault trees, event trees, the reliability of degradable systems, and the assessment of system criticality based on the severity of a failure and its probability of occurrence.>