β<4 these are wear out or end of life failures. They should not appear within the design life. Appropriate maintenance is often renewal. An ideal profile for equipment is to have a negligible failure probability throughout its design life followed by a steep b where the replacement age can be predicted. Age related failures include stress corrosion cracking, creep, high cycle fatigue, and erosion.

Today Weibull analysis is commonly being used to predict safe intervals for operation in applications such as warranty periods, shutdown intervals and increasingly in setting maintenance and inspection intervals. With more sophisticated CMMS in use, the collection of failure mode data is more reliable and data analysis can be handled electronically.

Many organizations have been keeping records of failures manually or in computer systems, but not using the data in any useful way. Failure data is the best source of reliability information available. It has relevance and is easy for site people to relate their own experience to. By transforming it into useful information from which failure forecasts can be made it can then be used to model the benefits of alternative strategies or to analyze the reliability of current systems and the capacity to meet operating needs.

LIFE CYCLE SIMULATION

Having determined the Weibull parameters that best represent failure mode behavior, they can be used to simulate performance over extended periods of time. Modern simulation packages involve a simulation engine that generates random numbers in accordance with the Weibull parameters over a specified system lifetime. Used in conjunction with Reliability Centered Maintenance (RCM) principles, the process of selecting maintenance and inspection intervals becomes a process of playing “what if” by comparing different reliability strategies.

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