This Demonstration shows the interaction between a system's availability, the system's critical spare part reliability, and the spare part's repair times, throughout a specific operating period. Use the controls to change the corresponding parameters and observe the effects on the system availability, using four different display sets.
A Monte Carlo simulation process generates pseudorandom scenarios for the spare part failure and repair times and then approximates the density of the system availability during the selected operating period. This Demonstration is based on the assumptions that the spare part's mean time to failure (MTTF) derives from a constant failure rate, and that the repair turnaround times (TAT) follow a three-parameter lognormal distribution.
Choose among four different display sets:
• The first display set illustrates the scenarios for the available spare parts during the operating period, taking into consideration pseudorandom failure and repair times. Use the "seed" slider to regenerate pseudorandom scenarios. As you increase the number of scenarios, you get more reliable forecasts, but this requires more computational time. The spare parts boundary (horizontal dashed line) shows the required number of spare parts that correspond to the system "availability boundary."
• The second display set shows the histogram of the available spare parts at the end of the operating period. It also shows the probability that the system availability is higher than the selected "availability boundary."
• The third display set illustrates the density of the system availability during the operating period.
• The fourth display set shows the system availability confidence interval (dark blue area) during the operating period, within the selected lower (thick red line) and upper (thick blue line) percentiles. The red and blue dashed lines represent the 0.0001 and 0.9999 system availability percentiles, respectively, while the horizontal black dashed line shows the selected "availability boundary."