Where should a spare live: on site, at a regional store, with the manufacturer, or at a repair shop? Most organisations answer with rules of thumb, vendor recommendations, or whatever the last stockout scared them into.
Spares holding is a trade-off between two curves. The cost of holding, capital tied up, storage and obsolescence, rises with inventory. The cost of not holding, extended downtime while a part travels at your production loss rate per hour, falls with inventory. Somewhere those curves cross, and that crossing point depends entirely on the failure characteristics of the equipment the spare protects. Which means you cannot optimise spares in a spreadsheet that does not know your failure distributions.
Why the Interaction Matters
- Demand is driven by the failure model. A wear-out component generates a demand pattern very different from a randomly failing one at the same average rate, and the difference decides how many spares protect you through a planning horizon.
- Lead time interacts with consequence. A $30 consumable with a one-day lead time and a $200,000 gearbox with a nine-month lead time are not the same problem, and the difference is not just price. It is lead time multiplied by failure probability multiplied by downtime cost, and that product only resolves inside a reliability model.
- Echelons change the answer. On-site, regional, manufacturer and repair-shop stocking levels each trade response time against pooled holding cost, and the right split differs by part, not by policy.
- Kitting discipline converts the strategy into wrench time. Optimised holdings only pay off if planning and kitting deliver the right parts to the job; our white paper High Precision Planning, High Precision Maintenance covers how complete kitting and tooling discipline multiply first pass quality.
How the Tools Help You Discover the Benefit
Availability Workbench treats spares as first-class citizens of the availability model: costs, lead times and stocking levels across all four echelons, interacting with the failure models and maintenance tasks in the Monte Carlo simulation. Run the simulation and you see stockout events, delay costs and holding costs in the same output, per part, per location, alongside the lifecycle cost totals they roll into. AWB Enterprise and the drag-and-drop library make proven spares configurations reusable across projects and analysts, and bills of material can be imported directly from your maintenance system through the SAP Portal or Maximo Portal.
The benefit you discover cuts both ways: some of your insurance spares are wasted capital, and some of the spares you are not holding are the most expensive absences in your storeroom. The model names both.
Go Deeper
- Software: AWB Availability Simulation, Life Cycle Cost, AWB Enterprise
- Services: Availability Simulation, Maintenance Planning and Scheduling Uplift
- White papers: High Precision Planning, High Precision Maintenance, Working on the Right Things
- Podcast: Getting it Right
- Next in the series: Lifecycle Cost and CMMS Integration
How can we help? Talk to us at contact@mantua.group.
