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Spare Parts Reorder Calculator - Safety Stock, ROP & EOQ for MRO

Calculate Reorder Points and Safety Stock for Slow-Moving and Fast-Moving Maintenance Spare Parts

Free source-aware MRO spare parts inventory screen for maintenance planners, storeroom managers, and reliability engineers. Enter annual demand, lead time, unit cost, service level target, ordering cost, and holding-rate assumptions to screen a local reorder point (ROP), safety stock prompt, and economic order quantity (EOQ). The app uses a Poisson prompt for annual demand below 10 units and a normal-distribution prompt for faster movers, then keeps CMMS/ERP data quality, supplier lead time, criticality, shelf life, finance policy, and qualified-review gaps visible.

Pro Tip: Treat the output as a review worksheet, not a min/max update. A low-cost belt, a specialty bearing, and an obsolete control board can have different lead-time risk, failure consequence, shelf-life limits, and finance treatment even when the arithmetic looks simple. Segment parts by demand history and criticality, then reconcile the local prompt with CMMS records, supplier data, OEM support, downtime consequence, and approval workflow before changing stocking levels.

Review PM interval assumptions before changing parts demand

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Budget fleet PM costs beside separate parts inventory review

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Read the spare parts inventory management guide

Spare Parts Inventory Guide →

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Spare Parts Reorder Calculator
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How It Works

  1. Enter Demand Data

    Input the average annual issue count for the part. Treat PM-derived demand, failure-driven demand, and cleaned CMMS history as assumptions until source records are reconciled.

  2. Set Lead Time

    Enter the lead time to screen. Supplier promises, internal approval time, shipping variability, expediting options, and current availability still need source review.

  3. Specify Service Level

    Choose a cycle service-level prompt. The right target depends on criticality, downtime consequence, safety/environmental constraints, holding cost, and site policy.

  4. Enter Cost Parameters

    Input unit cost, annual holding-rate assumption, and cost per order. Replace defaults with finance-approved cost-of-capital, storage, obsolescence, receiving, inspection, and purchase-order assumptions before relying on output.

  5. Review Source Gaps

    Use the ROP, safety-stock, EOQ, holding-cost, ordering-cost, and stockout-risk prompts as a review package. Resolve CMMS data, supplier, OEM, criticality, shelf-life, and approval gaps before changing min/max values.

Built For

  • Maintenance planners screening candidate min/max levels before CMMS master-data review
  • Storeroom managers comparing slow-moving and faster-moving part assumptions without hiding source gaps
  • Reliability engineers preparing criticality and downtime-consequence questions for spare-parts review
  • Procurement specialists checking whether local EOQ prompts conflict with MOQ, price breaks, shelf life, or supplier constraints
  • Plant managers collecting inventory assumptions before finance or operations review
  • CMMS administrators identifying parts where demand history, lead time, or approval workflow needs cleanup
  • Maintenance supervisors comparing VMI or consignment proposals against a transparent local worksheet

Features & Capabilities

Dual Distribution Prompt

Automatically selects a Poisson prompt for annual demand below 10 units and a normal prompt for demand of 10 units or more. The model choice is a screen and still depends on clean demand history.

Reorder Point Calculation

Screens ROP = average demand during lead time + safety stock. Normal prompts use z-score times standard deviation during lead time; Poisson prompts use a cumulative probability lookup.

Economic Order Quantity

Screens the classic EOQ formula sqrt(2 times annual demand times ordering cost / annual holding cost per unit). MOQ, price breaks, shelf life, pooling, and supplier constraints remain source gaps.

Cost Prompt Breakdown

Displays annual holding cost and annual ordering cost from the entered assumptions. It does not calculate expected downtime loss, stockout cost, or a finance-approved business case.

Source Warnings

Keeps CMMS data quality, supplier lead time, criticality, shelf life, obsolescence, finance policy, and qualified-review warnings visible in the app and exports.

State and Export Guardrails

Normalizes shared URL and autosave state before calculation, and carries source pointers into report/PDF output.

Assumptions

  • Annual demand, unit cost, lead time, ordering cost, holding rate, and service level are user-entered assumptions.
  • Demand is treated as stationary and lead time as deterministic for the local screen.
  • Annual demand below 10 units uses a Poisson prompt; demand of 10 units or more uses a normal prompt with the entered coefficient of variation.
  • EOQ assumes fixed demand, fixed cost basis, no MOQ, no price breaks, no shelf-life limit, and instantaneous replenishment at the trigger.
  • Cycle service level is a local prompt, not an annual fill-rate guarantee or site policy.

Limitations

  • Does not fit intermittent-demand forecasts, Croston models, Weibull failure models, or Bayesian insurance-spare decisions.
  • Does not model lead-time variability, service-level optimization, MOQ, price breaks, shortage cost, shelf life, obsolescence, pooling, kitting, consignment, or VMI control terms.
  • Does not update CMMS/ERP min/max fields or validate issue-history cleanup.
  • Does not approve stocking levels for safety-critical, environmental, warranty, insured, obsolete, or production-critical parts.
  • Does not replace maintenance, reliability, operations, procurement, finance, safety, legal, or management approval.

References

  • NIST/SEMATECH Engineering Statistics Handbook - Poisson distribution and standard-normal CDF source pointers.
  • MIT OpenCourseWare inventory and EOQ models source pointer.
  • MIT-hosted APICS Magazine safety-stock reading for cycle-service-level and z-score context.
  • NIST SP 811 Appendix B.8 - unit/rounding context.
  • Site CMMS/ERP records, supplier data, OEM manuals, finance policy, and qualified maintenance/supply-chain review control field use.

Frequently Asked Questions

The app uses a Poisson prompt when annual demand is below 10 units because low-count demand is discrete. It uses a normal prompt for faster movers. That branch selection is not proof that the part history fits the distribution; clean CMMS history, seasonality, shutdown work, and lead-time variability still need review.
Use the holding-rate basis approved by your organization. Cost of capital, storage, insurance, taxes, obsolescence, cycle counting, and handling can vary by part family and accounting policy, so generic percentages should be treated as placeholders.
Zero-history parts are usually insurance-spare or criticality questions, not statistical ROP questions. Review equipment status, acceptable downtime, OEM support, lead time, shelf life, and consequence of not having the part before stocking or removing it.
The app does not choose a target. Criticality, safety/environmental consequence, downtime cost, repair alternatives, expediting options, and finance policy should set the target before the arithmetic is used.
Review when utilization, supplier lead time, equipment status, PM intervals, failures, part revision, MOQ, price breaks, or stockout history changes. Formal cadence is a site policy decision, not an output from this screen.
Disclaimer: This screen provides local inventory prompts from user-entered assumptions. It is not a CMMS/ERP master-data update, stocking-policy approval, supplier forecast, purchase recommendation, finance approval, reliability engineering decision, safety review, or professional supply-chain advice. Reconcile source records and qualified review before changing inventory levels.

Learn More

Shops & Outbuildings

MRO Spare Parts Inventory: Reorder Points, Safety Stock, and Storeroom Strategy

How to calculate reorder points and safety stock for maintenance spare parts, handle slow-moving items with Poisson distribution, and build a storeroom strategy that balances cost against stockout risk.

Read Guide →

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