Spare parts management is the control of repair parts inventory, deciding which parts to stock, in what quantity, and reordering before stock runs out.
Spare parts management is the discipline of controlling the inventory of repair parts and maintenance consumables - deciding which parts to stock, in what quantity, where they live, and when to reorder so that stock arrives before it runs out. It exists for one reason: a repair that waits for a part is downtime you chose in advance. How quickly equipment comes back from failure - the metric MTTR tracks - is often decided by what was on the shelf, not by how fast anyone worked.
Deciding which parts to stock
Stocking everything is unaffordable and stocking nothing is reckless, so the decision runs part by part on three questions:
- Criticality - if this part failed today, what stops, and for how long? Parts that idle a revenue-earning asset such as a truck justify shelf space that a spare office keyboard does not.
- Lead time - parts available same-day locally rarely need stocking; parts on a six-week order from one supplier almost always do.
- Usage rate - filters, belts, brushes, and seals consumed by routine preventive maintenance have predictable demand and are the easiest wins.
The intersection of high criticality and long lead time defines the critical spares - items held even if they are used once in five years, because the holding cost is trivial next to the outage they prevent.
Min-max levels and reorder points
Most spare parts stock runs on a min-max rule. Each part gets a minimum level (the reorder trigger) and a maximum level (the top-up target): when a withdrawal takes stock to the minimum, an order goes in for the difference. The minimum has to cover expected usage during the supplier’s lead time, with a margin for the unexpected - a minimum of zero is just a stockout with paperwork. The numbers are guesses at first; what matters is recording every withdrawal so the guesses improve. Failure history helps here too: a part’s usage follows the asset’s MTBF, so a machine that fails more often than planned should pull its spares’ minimums up with it.
Common failure modes
Spare parts stores fail in familiar ways. Stockouts on critical parts turn a one-hour corrective repair into a week of waiting. Ghost stock - the system says three, the shelf says none - comes from unrecorded withdrawals, and quietly defeats every reorder rule. Squirrel stores appear when technicians stop trusting the store and hoard parts in vans and drawers, making real usage invisible. And dead stock accumulates when assets are retired but their spares are not - parts for a machine sold two years ago, still occupying shelf and balance sheet.
Spare parts management in practice
The habits that keep a store honest are unglamorous: one named location per part, every withdrawal recorded against the asset or job it served, supplier and lead time captured on the part itself, and a periodic cull of spares for equipment you no longer own. In AMPthilly, consumable parts carry a reorder point, target stock, supplier, and per-supplier purchase details, and receiving an order updates stock levels - so the numbers behind every reorder decision live on the part record rather than in someone’s memory. Whatever the tooling, the test of good spare parts management is the same: when something breaks, the part is there.
Related terms
- Preventive Maintenance - the scheduled work that consumes parts predictably
- Corrective Maintenance - the repairs that stall without the right spare
- Predictive Maintenance - condition data that warns you to stage a part early
- MTBF - failure frequency, the demand signal behind stocking levels
- MTTR - repair time, the metric stockouts inflate most