Reliability Engineering
Reliability engineering involves developing a statistical model of an existing or proposed system, which is used to predict its performance and optimize its design or its maintenance program. These models are frequently used to inform decisions about required levels of redundancy and to evaluate risk. They can also be used to compare design alternatives on the basis of metrics such as warranty and maintenance costs.
Reliability Engineering in GoldSim
GoldSim is well-suited for reliability engineering through dynamic simulations repeated in a Monte Carlo analysis. Dynamic simulation allows the analyst to develop a representation of the system whose reliability is to be determined, and then observe that system’s performance over a specified period of time. The primary advantages of dynamic Monte Carlo simulation:
- The system can evolve into any feasible state and its properties can change suddenly or gradually as the simulation progresses.
- The system can be affected by random processes, which may be either internal (e.g., failure modes) or external.
- If some system properties are uncertain, the significance of those uncertainties can be determined.
In Monte Carlo simulation, the model is run many times with random sampling of uncertain variables and events (each run is called a realization). These realizations are each considered equally likely, and can be combined to provide not only a mean, but also confidence bounds and a range on the performance of the system. In addition to the statistical data these realizations provide, multiple realizations may also reveal failure modes and scenarios that may not be apparent, even to experienced reliability modelers.
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