Preventive Replacement Interval Cost Calculator (Weibull Model)
Preventive replacement only makes sense when failures become more likely with age and when a planned replacement is cheaper than a failure. This calculator compares the cost per running hour of replacing at a fixed interval with the cost of running to failure.
Your numbers
Above 1 means wear-out. Around 3 to 4 is typical for fatigue and wear.
Hours by which 63.2% would have failed.
About 0.89 x eta when beta is 3. Use your observed MTTF.
Parts, labor and planned downtime.
Parts, labor, secondary damage, lost production and expediting.
Your results
The mean cycle length is an approximation. For a formal optimum, integrate the reliability function numerically or use a dedicated reliability package.
Cost per hour vs replacement interval
Sweeps Replacement interval from 500 to 12000, holding your other inputs fixed.
Failure data to Weibull fit
Optional: pull failure times from ERP work orders and fit parameters.
Optional. The tool and every export work without this. No spam.
How to use it
Enter the Weibull shape and scale for the failure mode, taken from Weibull analysis of your failure history, plus the cost of a planned replacement and the full cost of an unplanned failure. Try several intervals. The chart shows cost per hour for the preventive policy against the flat run-to-failure cost, and the lowest point on the curve is your approximate best interval.
The model
Failure probability by time T is F(T) = 1 - exp(-(T / eta) to the power beta). Each cycle ends with a planned replacement with probability 1 - F, costing Cp, or a failure with probability F, costing Cf. Cost per hour is expected cycle cost divided by expected cycle length. With beta close to 1, failures are random and replacement by age gives no benefit. Higher beta and higher Cf to Cp ratios favor shorter intervals.
- Needs beta above 1 for age-based replacement to help
- Cf should include secondary damage and lost output
- Condition-based replacement may beat a fixed interval
Common mistakes
Using a Cf that only counts the part is the most common error and makes run to failure look cheap. Others include applying age replacement to random failures, using too few failures to fit beta, and ignoring that replacement itself can introduce infant mortality. Review the interval each year against recorded failures.
- Underestimating the true cost of failure
- Mixing several failure modes into one Weibull fit
- Setting the interval from the vendor's catalogue only
Frequently Asked Questions
When is preventive replacement worthwhile?
When the failure rate rises with age (Weibull beta clearly above 1) and the cost of failure is much larger than the cost of a planned replacement. For random failures it adds cost without benefit.
How do I get beta and eta?
Fit a Weibull distribution to times to failure from your records, using median rank regression or maximum likelihood. At least 8 to 10 failures give a rough estimate; more is better.
Is the lowest point the best interval?
It is the best interval under this approximate model. Because the curve is usually flat near the minimum, choosing a slightly shorter interval costs little and reduces risk.
Does this replace condition monitoring?
No. If you can detect degradation reliably, replacing on condition avoids both early replacement and failure. Use this model for components with no useful condition indicator.
Netray can extract failure and replacement history from ERP work orders so Weibull parameters come from your own data.
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