Use parametric growth curves to analyze data from a repairable system, in order to estimate growth curves of the mean number of failures and ROCOF over time. Minitab provides two types of models for estimating parametric growth curves:

- Power-law process: Use to model failure/repair times that occur at a rate that can be increasing, decreasing, or constant. The failure rate for a power-law process is a function of time.
- Poisson process: Use to model failure/repair times that occur at a rate that remains stable over time.

Using parametric growth curves, you can estimate the following:

- Expected cumulative number of failures as a function of time
- Failure rate as a function of time

You can estimate growth curves of the mean number of failures over time. Use these curves to determine whether a trend exists in times between successive failures, and whether the system failures are becoming more frequent, less frequent, or remaining constant.

A reliability engineer assesses the failure rate of a specific air conditioning unit that is used in commercial jet planes. The engineer collects failure data for air conditioning units in 13 airplanes. Each time a unit failed, it was repaired and returned to service.

The engineer wants to determine whether the failure rate is increasing, decreasing, or remaining constant over time. For these data, no air conditioning units were retired from service. All the data are exact failure times.