Spares optimization
Spares optimization that stocks what runs out and flags what never moves.
Spares optimization in MaintenanceIQ reads how fast each part is actually consumed on your work orders and turns it into days of cover, stockout risk, overstock and dead-stock flags, with a suggested reorder point. It helps your stores in-charge keep the right spares on the shelf, and helps your maintenance manager free up money tied up in parts nobody uses.
The problem
Too few of the parts you need, too many of the ones you don't
Your stores in-charge sets reorder points once, often years ago, from a supplier's suggestion or a gut feeling. Then the plant changes. A pump gets a new duty, a conveyor is retired, a press starts eating seals. The reorder points stay where they were.
The result is familiar. A line waits on a seal kit that ran out last week, while the shelf next to it holds bearings for a machine that left the plant. Both problems cost money, and neither shows up until someone goes looking.
The fix is to let the record do the looking. When every part issued is consumed against a work order, the consumption rate is already known. All that is left is to read it.
The signals
How spares optimization reads your consumption
MaintenanceIQ works out each part's consumption rate from its stock transactions and turns it into signals your stores in-charge can act on. Each signal points to a different action: reorder, hold, or clear the shelf.
The suggested reorder point is a starting point grounded in real use, not a decision. Your team reviews it and sets the reorder point it wants.
- Days of cover: how long current stock lasts at the current rate of use
- Stockout risk: parts likely to run out before you would normally reorder
- Overstock: parts held far beyond what consumption needs
- Dead stock: parts that have not moved
- Suggested reorder point: based on actual consumption, for you to accept or adjust
The idea
Days of cover, in one line
Days of cover is the simplest way to see whether stock matches use.
Days of cover = Quantity on hand ÷ Average daily consumption- Quantity on hand
- The current stock of the part in the store.
- Average daily consumption
- How many units were consumed per day over the recent period, from issue transactions.
A part with very few days of cover is a stockout risk. A part with years of cover is overstock. A part with no consumption at all is a dead-stock candidate.
Worked example
Three parts, one review
Worked example (illustrative)
Your stores in-charge looks at three parts over the last 90 days. The machines are illustrative.
| Part | On hand | Used in 90 days | Daily use | Days of cover | Signal |
|---|---|---|---|---|---|
| Seal kit for P-07 pump | 6 | 18 | 0.2 | 30 | Watch for stockout |
| Bearing for CV-03 conveyor | 40 | 4 | 0.044 | About 900 | Overstock |
| Gasket set for a retired line | 12 | 0 | 0 | No use | Dead-stock candidate |
The seal kit has about a month of cover, so it is reordered before the pump needs it. The bearing has years of cover, so the next order can wait. The gasket set has not moved, so it is reviewed for return or disposal and the money stops sitting on the shelf.
Why the data is trustworthy
Good signals need clean stock records
Spares optimization is only as good as the stock behind it. MaintenanceIQ keeps that stock honest with the same spare parts inventory your team uses every day.
- Issue, receive and adjust are atomic transactions, so on-hand counts do not drift.
- Parts are consumed against the work order that used them, which is where the consumption rate comes from.
- Critical spares are flagged, so the parts whose stockout would stop production get attention first.
- Spares are linked to the machines they fit, so your planner knows what to stock for each asset.
- Part numbers are unique regardless of letter case, so the same part is not counted twice under two spellings.
- Parts with history can be retired instead of deleted. They leave the list, and their history stays.
Beyond the store
Spares in the wider maintenance picture
Parts spend is one of the two components in maintenance cost analytics, next to the charges recorded against each breakdown. Spares optimization tells you whether that spend reflects real use.
When a breakdown is reported, the triage hints show the parts most often used on past repairs of that machine. That is the floor-level view of the same consumption history, and it helps your technician take the right part on the first trip. See breakdown and downtime tracking.
Frequently asked questions
How are reorder points suggested?
From each part's actual consumption rate, worked out from its stock transactions. The suggestion is shown alongside days of cover and the risk flags, and your team decides the reorder point.
What counts as dead stock?
Parts that have not moved. They are flagged so your stores in-charge can review them for return, transfer or disposal.
Does spares optimization order parts for me?
No. It shows which parts need attention and suggests reorder points. Purchasing stays with your team and your existing process.
What about critical spares that are rarely used?
Flag them as critical spares. A part that is used rarely but stops production when missing should be stocked on judgment, not on consumption alone, and the critical flag keeps it visible.