Ask a workshop manager why a machine sat for four days and the answer is usually "waiting for parts", which sounds like a supplier problem. Break that wait down and the supplier's delivery time is often the smallest piece of it. Most of the delay accumulates before anyone places an order — identifying exactly which part is needed, checking whether it is already on a shelf somewhere, raising a requisition, getting it approved, and finding a supplier who has it. All of that is administrative time, and almost all of it could have started days earlier, on the day the defect was first reported rather than the day the machine rolled into the workshop. You can see where your own wait actually sits in a free 30-minute session.
How Much Workshop Time Are You Losing to Parts?
Link inspection defects directly to parts procurement, so the part is identified, stock is checked, and the order is moving before the machine ever reaches the workshop bay.
What "Waiting for Parts" Is Actually Made Of
The delivery is one segment of this. The rest is internal, and the internal part is where the time is recoverable.
Diagnosing the fault precisely enough to know which part is required.
Establishing the correct part number for that exact machine and configuration.
Checking whether the part already exists in stores, at this site or another.
Raising the requisition and getting it through approval.
Identifying a supplier who actually has it available now.
Actual delivery lead time, the only segment genuinely outside your control.
The Clock Starts in the Wrong Place
The repair takes the same time either way. The bay occupancy does not.
Start Procurement Where the Defect Is Found
Defects raise work orders with parts attached, stock checked across sites, and orders moving while the machine is still productive.
What the Fleet Teaches You Over Time
Which parts you actually consume
Consumption logged against work orders shows real usage rather than what someone estimated when the stores list was written.
Where reorder points should sit
Usage rate combined with supplier lead time gives a reorder level that prevents both stockouts and money sitting on shelves.
Which machines drive parts spend
Repeat consumption on one asset is usually telling you something about that machine rather than about the part.
What stock already exists elsewhere
Visibility across sites prevents buying a part that is already sitting unused in another store.
Frequently Asked Questions
Can parts really be identified before the machine is properly diagnosed?
Often the likely parts are predictable from the defect and photo evidence, particularly for common failures on familiar machines. Where they are not, the value is still in checking stock and confirming supplier availability early. You can see how this works in practice on a call with our team.
What if we order a part and the diagnosis changes?
It happens, and for high-value or non-returnable items it is better to wait for confirmation. The approach works best on common wear parts where the risk of being wrong is low and the cost of waiting is high.
Does this need integration with our purchasing system?
HVI integrates with SAP, Oracle, and Tally, so requisitions and consumption data can flow into the purchasing process your finance team already uses.
Can we see stock across multiple site stores?
Yes. Visibility across stores is usually where the quickest gains appear, since parts are often bought while identical items sit unused at another site.
How long before reorder points become reliable?
They improve as consumption history builds, so early figures are a starting point rather than a settled answer. Start with a free trial to begin logging consumption.
Recover the Wait You Actually Control
Move parts identification, stock checking, and ordering to the moment the defect is logged, keep the machine productive while procurement runs, and let real consumption history set your reorder points instead of guesswork.
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