Odoo ERP for Mining, Quarrying and Aggregate Operations

Why standard ERPs lose track of mining costs

A mine or quarry does not produce units, it moves material, and its economics really live in cost per tonne by pit, bench and product. A standard ERP chart of accounts records diesel, explosives, tyres and contractor hours as plain expense lines with no link back to the tonnes they produced, so the site ends up knowing what it spent without ever knowing what it cost. Meanwhile, the biggest capital items are mobile and maintained on engine hours rather than the calendar, and the largest inventory line is a stockpile that no system can actually count. Odoo addresses all of this through analytic accounting, Maintenance and disciplined inventory design.

Could you show cost per tonne, broken down by pit and by product?

Diesel, explosives, drilling consumables, contractor invoices and plant maintenance all land in general ledger accounts covering the whole site. So when a bench turns out more expensive than planned, there is no way to pull apart the drill and blast cost, the haul cost and the processing cost sitting behind that tonnage.

We build an analytic structure across pit, bench, cost centre and product so that every purchase, timesheet, fuel issue and work order posts against the material it actually produced. Drill and blast, load and haul, processing and rehandling each become their own analytic plan, and cost per tonne gets reported by period, by pit and by product instead of being reconstructed at year end.

Is heavy equipment maintained on hours or on hope?

Excavators, haul trucks and crushers get serviced whenever the operator reports a problem, or whenever someone happens to remember. Because service intervals run on engine hours rather than calendar dates, a unit can drift 200 hours past its interval before a component fails mid-shift, and then an unplanned rebuild takes the fleet down for a week.

Odoo Maintenance triggers preventive work orders directly off meter readings, so an intervention gets raised at the hour threshold instead of on a guessed date. Each asset carries its own service history, parts consumption and downtime, spare parts reserve automatically against scheduled jobs in Inventory, and mean time between failures per unit shows you which machines are driving cost and which are due for replacement.

Do your stockpiles agree with your books?

Crushed product gets stockpiled, rehandled, sold from and topped up, and the book figure is really just a running calculation from production and sales. When the quarterly survey turns up thousands of tonnes of difference, the adjustment gets posted without explanation, and nobody can say whether it comes from a scale calibration issue, a moisture assumption, or product going out the gate unrecorded.

Each pile becomes its own stock location with its own movements, so production in, rehandling between piles, plant feed and sales out are tracked as separate transactions rather than folded into one net figure. Weighbridge tickets post against delivery orders, survey volumes get entered as counts with a documented reason and density assumption, and variance is trended per pile, which makes a calibration drift distinguishable from a genuine loss.

What we implement for mining and quarry operators

• Analytic accounting broken down by pit, bench, cost centre and product, with cost per tonne reported across drill and blast, load and haul, and processing.
• Odoo Maintenance built around meter-based preventive triggers, asset history, downtime tracking and spare parts reservation for the mobile fleet and plant.
• Stockpiles modelled as stock locations, weighbridge-linked deliveries, survey reconciliation and documented variance trending by product.
• Odoo Purchase and Inventory covering consumables, explosives and contractor management, with approval workflows and landed cost on imported parts.