# Preventive Replacement Interval Cost Calculator (Weibull Model) > Source: https://netray.co/tools/preventive-replacement-interval-weibull-cost-calculator > Publisher: Netray (netray.co), AI and integration engineering for ERP and manufacturing systems. > Section: Free Tools ## Short answer Compare cost per hour of age-based replacement against run to failure for a wear-out component, with an interval sweep chart. ## Category maintenance ## Industry Manufacturing ## Audience - Reliability engineer - Maintenance planner - Asset manager ## Tool **Kind:** calculator **Currency:** $ **Inputs:** #### Weibull shape (beta) **Key:** beta **Type:** number **Default:** 3 **Min:** 1.1 **Max:** 8 **Step:** 0.1 **Help:** Above 1 means wear-out. Around 3 to 4 is typical for fatigue and wear. #### Weibull scale (eta, characteristic life) **Key:** eta **Type:** number **Default:** 8000 **Min:** 100 **Step:** 100 **Unit:** h **Help:** Hours by which 63.2% would have failed. #### Mean time to failure, run to failure **Key:** mttf **Type:** number **Default:** 7150 **Min:** 100 **Step:** 50 **Unit:** h **Help:** About 0.89 x eta when beta is 3. Use your observed MTTF. #### Cost of planned replacement **Key:** cp **Type:** number **Default:** 1500 **Min:** 0 **Step:** 100 **Help:** Parts, labor and planned downtime. #### Cost of failure **Key:** cf **Type:** number **Default:** 12000 **Min:** 0 **Step:** 500 **Help:** Parts, labor, secondary damage, lost production and expediting. #### Replacement interval **Key:** interval **Type:** number **Default:** 4000 **Min:** 100 **Step:** 100 **Unit:** h **Outputs:** #### Probability of failure before interval **Key:** f_t **Expr:** 1 - exp(0 - pow(interval / eta, beta)) **Format:** decimal **Description:** Between 0 and 1. #### Probability of reaching interval **Key:** r_t **Expr:** 1 - f_t **Format:** decimal #### Approximate mean cycle length **Key:** cycle_h **Expr:** interval * r_t + interval / 2 * f_t **Format:** integer **Description:** Assumes failures occur on average mid-interval. #### Cost per hour, preventive policy **Key:** cost_pm **Expr:** (cp * r_t + cf * f_t) / cycle_h **Format:** currency **Primary:** true #### Cost per hour, run to failure **Key:** cost_rtf **Expr:** cf / mttf **Format:** currency **Primary:** true #### Saving versus run to failure **Key:** saving_pct **Expr:** if(gt(cost_rtf, 0), (cost_rtf - cost_pm) / cost_rtf * 100, 0) **Format:** percent **Chart:** #### Cost per hour vs replacement interval **Type:** line **X:** interval **From:** 500 **To:** 12000 **Steps:** 40 **Series:** - cost_pm - cost_rtf **Disclaimer:** The mean cycle length is an approximation. For a formal optimum, integrate the reliability function numerically or use a dedicated reliability package. ## Content **Intro:** 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. **Sections:** #### How to use it **Body:** 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 **Body:** 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. **Bullets:** - 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 **Body:** 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. **Bullets:** - Underestimating the true cost of failure - Mixing several failure modes into one Weibull fit - Setting the interval from the vendor's catalogue only **Cta:** Netray can extract failure and replacement history from ERP work orders so Weibull parameters come from your own data. **Faq:** #### When is preventive replacement worthwhile? **Answer:** 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? **Answer:** 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? **Answer:** 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? **Answer:** 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. ## Search terms preventive replacement interval calculator, optimal PM interval calculator, age replacement policy cost, run to failure vs preventive maintenance cost, weibull maintenance interval, when to replace component calculator, optimum replacement interval, PM interval cost model --- Talk to an engineer: https://netray.co/contact?intent=erp_ai | Machine catalog: https://netray.co/agent/catalog.json