Spare Parts Reorder Point Calculator

Statistically: safety stock = z × σ_demand-over-lead-time, where z sets service level (z = 1.65 for 95%, 2.33 for 99%). With Poisson-ish failure demand, σ ≈ √(mean demand over lead time): a part averaging 4 failures per lead time needs ~1.65×2 ≈ 3–4 units of safety stock for 95% service. For critical single points of failure, ignore the statistics and stock the insurance level — math optimises cost, not consequence.

Yes — trigger on inventory position (on-hand + on-order − backorders), not bin count alone, or you'll double-order during the lead time. Most CMMS/ERP systems do this automatically; manual bin systems need the discipline of an 'on order' card in the bin. Two-bin systems implement the ROP physically: when the first bin empties, that's the reorder point made of cardboard.

Use fleet failure math instead of issue history: number of installed components × operating hours per day ÷ component MTBF gives expected daily demand even when history is sparse. Cross-check criticality: a two-in-three-years part that stops production for its 3-week lead time probably deserves min/max of 1/2 regardless of optimisation — slow-moving ≠ safe to zero-stock.

Typically 15–30% of unit value per year (capital cost + storage + obsolescence + shrinkage); maintenance spares lean to the high end because obsolescence bites when equipment retires. The practical use isn't precision — it's tie-breaking: when this calculator suggests stocking 6 of an expensive item, the carrying percentage tells you what shortening the lead time or negotiating supplier-held stock would be worth annually.