Overview of Parametric Growth Curve

Use Parametric Growth Curve to analyze data from a repairable system, in order to estimate the mean number of failures and the rate of occurrence of failure (ROCOF), also called the repair rate, over time. A repairable system is one in which the parts are repaired instead of being replaced when they fail. For example, automotive engines are usually repaired many times before being replaced.

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.

Use the estimated growth curves to examine the failure rate and the expected cumulative number of failures as a function of time, and to determine whether a trend exists in times between successive failures. For example, you can determine whether system failures are becoming more frequent, less frequent, or remaining constant.

By charting the performance of repairable systems, growth curves can help you establish:

How often the system will require maintenance
The number of replacement parts to have in inventory
Whether the system is performing at an acceptable level
Likely repair costs during the life of the system

For more information on growth curves, including the power-law process and the Poisson process models, go to Estimating parameters for growth curves.

Where to find this analysis

To perform a parametric growth curve analysis, choose Stat > Reliability/Survival > Repairable System Analysis > Parametric Growth Curve.

When to use an alternate analysis

If you cannot make assumptions about the distribution of the cost or the number of repairs in the system, use Nonparametric Growth Curve.