OptimalSPARES™ Wiki / Spares optimisation
The frame
Spares optimisation
Every spare part is a bet against a failure. Hold too few and a stockout turns a quick repair into a long shutdown; hold too many and capital, storage and obsolescence quietly drain away. Spares optimisation is finding the holding that balances the two, part by part.
The two ways to be wrong
| Stockout | The part is not there when the asset needs it. A short repair becomes an extended outage while the part is expedited or made. The cost is the downtime, not the part. |
|---|---|
| Overstock | Capital sits on a shelf, insured, stored, counted and slowly going obsolete. Most storerooms carry a large tail of parts that have not moved in years. |
The two errors pull in opposite directions, so the answer is never a blanket rule like hold two of everything. It is a per-part decision driven by how much a stockout would cost and how hard the part is to get.
Not all spares are alike
| Consumables | Gaskets, filters, fasteners: low value, steady demand, easy to model with classical inventory maths. |
|---|---|
| Rotables and repairables | Assemblies that are swapped and refurbished, so the pool and the repair loop must be managed, not just the buy. |
| Insurance and capital spares | Rarely or never demanded, but catastrophic and long-lead if missing. Held on risk, not on demand history, and classical EOQ does not apply. |
Across the network: pooling and redeployment
The largest reductions often come not from a single store but from across the network. When several sites hold the same part, the aggregate safety stock can be pooled: one shared or virtual holding covers them all at a far lower total than each site stocking on its own, and an emergency at one plant can be met from another in hours rather than weeks. The same cross-site view exposes the excess and obsolete stock sitting in one store that another site actually needs, so material is redeployed, resold or returned rather than written off. This only works on harmonised data, where the same physical part is recognised as the same across every site and ERP, which is why the data foundation on the next pages matters so much.
Spares serve the strategy
Spares are the physical enabler of the maintenance strategy. Reliability and RCM decide which failures are managed and how; the spare is what makes the planned job actually happen on the day. This is why criticality flows from the asset to the part: a spare is only as critical as the failure it lets you fix. The bill of materials is the link, and the criticality is inherited from the analysis on the next page.
Where OptimalSPARES™ fits
OptimalSPARES™ holds the whole picture as one model: the materials data, the asset links, the criticality, the demand history and the stocking policy. Change a criticality or a lead time and the recommended min, max and reorder move with it, so the storeroom stays matched to the plant rather than frozen at whatever was set years ago.