FM Global's insurance data shows 75% of mining losses come from production stoppages during repairs, not physical damage itself, with conveyor failures the leading cause at 32%.
At a glance
- FM Global's decade-long loss analysis found 75% of mining losses come from business interruption -- lost production during repairs -- versus 25% from physical damage itself.
- Conveyors cause the largest share of equipment-driven losses at 32%, ahead of heavy-duty mobile equipment (21%), motors (16%), mills (15%) and dryers (8%).
- A 30-day conveyor outage on an operation moving a million dollars of material daily can mean a $30 million loss -- far beyond the cost of the equipment itself.
- Fire is the single largest driver of the most severe mining losses, with hot work like cutting, welding and grinding the leading ignition source.
What happened
Insurer FM Global's engineering analysis of a decade of mining losses found that only 25% of the money it pays out traces back to physical damage or equipment failure itself -- the remaining 75% comes from business interruption, meaning the production that's lost while a mine waits for equipment to be repaired or replaced. "By far the majority of loss that we pay is the downtime associated with equipment being unavailable, as opposed to the actual physical cost of fixing things," Matt Pilgrim, FM's account engineering group manager, told Australian Mining. Within that equipment-failure category, conveyors are the single biggest culprit, responsible for 32% of losses, ahead of heavy-duty mobile equipment at 21%, motors at 16%, mills at 15% and dryers at 8%. FM Global illustrates the scale with a simple example: a mine might spend a million dollars replacing a damaged conveyor, but if it's moving a million dollars of material a day and that conveyor is down for 30 days, the actual loss is $30 million -- thirty times the repair bill itself. Fire ranks as the single largest driver of the most severe losses industry-wide, with hot work such as cutting, welding and grinding as the leading ignition source, and FM Global's data shows roughly 30% of total losses originate from just 2% of the mine sites it insures. The insurer now sends engineering teams to more than 600 mineral sites a year, layering AI-powered risk modelling on top of six decades of accumulated loss history to flag which operations are most exposed before a failure happens.
The details
The instinct when a piece of mining equipment breaks is to think about the repair bill. FM Global's data says that instinct is pointed at the wrong number. Fixing a conveyor, motor or mill is rarely what actually hurts a mine's finances -- it's everything that doesn't happen while the fix is underway. A processing plant that can't move ore isn't losing the cost of a belt; it's losing every tonne it would otherwise have shipped, priced at whatever that tonne was worth that day. That's the mechanism behind the 75/25 split: physical damage is a bounded, one-time cost, while business interruption compounds for every hour the line stays down.
That also explains why conveyors top the equipment list at 32% of losses even though they're mechanically simpler than a mill or a crusher. A conveyor isn't just one machine -- it's the connective tissue between every other stage of a mine's processing chain. When it stops, everything downstream of it stops too, which is precisely the kind of cascading, system-wide interruption FM Global's data says drives the bulk of the dollar losses. Mobile equipment, mills and motors follow for similar reasons: each sits at a point in the process where its failure doesn't just cost the machine, it costs the throughput of everything connected to it.
The concentration statistic -- roughly 30% of losses tracing back to just 2% of insured sites -- points to the same underlying idea from a different angle. Losses aren't randomly distributed across an operator's portfolio; they cluster at specific sites with specific vulnerabilities, whether that's an aging piece of critical equipment with no redundancy, a site layout that makes hot work near combustible material harder to isolate, or a location where a repair crew and spare parts are simply further away. That's why FM Global's engineering approach leans on site inspections and loss-history data rather than a blanket policy applied evenly across a company's assets: prevention spending is far more effective when it's aimed at the small number of locations actually carrying most of the risk, rather than spread thin across every site equally.
None of this is really an argument for spending more on equipment maintenance in the abstract. It's an argument for spending on the specific failure modes -- cascading downtime, fire from uncontrolled hot work, conveyor and mobile-equipment breakdowns -- that the loss data actually shows are doing the damage.
Why it matters
This isn't a story about one mine or one metal -- it's about the cost structure sitting underneath every large-scale mining operation MetalsCost tracks, from iron ore and copper to gold and nickel. A conveyor failure or an unplanned shutdown doesn't just show up in a company's maintenance budget; it shows up in quarterly production guidance, in shipment delays to customers, and ultimately in the supply-side numbers that move commodity prices. For readers tracking why a producer missed output guidance in a given quarter, FM Global's data offers a concrete, checkable reason to look at downtime and business interruption first, rather than assuming a headline number tells the whole story.
Our read
Outlook: neutral. This is an operational-risk and loss-prevention story rather than a price-moving event -- it describes a structural pattern in how mining losses occur, not a specific supply disruption happening now. Its price relevance is indirect: it explains why unplanned shutdowns at individual sites can have an outsized supply impact, a mechanism worth understanding rather than a directional signal in itself.
What to watch
- Producer disclosures on unplanned downtime or business-interruption events when quarterly production guidance is missed.
- Adoption of predictive-maintenance and condition-monitoring technology at large-scale mining operations.
- Insurance cost trends for mining operators, which can reflect how loss data like FM Global's is being priced into premiums.
For information only, not investment advice.
Iron price in India
metalscost.com India reference price as of 2026-10-03.
Detailed analysis
Mining Production
FM Global's loss data shows unplanned downtime, not the physical cost of repairs, is the dominant driver of mining production losses: 75% of losses stem from business interruption, conveyors alone account for 32% of equipment-driven losses, and roughly 30% of total losses concentrate in just 2% of insured mine sites -- meaning targeted prevention at high-risk sites and failure points has an outsized effect on protecting output.
What could lift prices
- Operators that act on this data by targeting prevention spending at high-risk sites and failure points (conveyors, mobile equipment, hot-work fire control) stand to protect production and reduce insurance costs relative to peers that don't.
What could weigh on prices
- Business interruption losses are structurally underappreciated relative to physical damage, meaning many operators may be under-investing in the specific prevention measures -- redundancy, spare-parts logistics, hot-work controls -- that would actually reduce their largest loss category.
- Risk is highly concentrated: with roughly 30% of losses coming from just 2% of sites, operators that haven't identified their own highest-risk locations remain exposed to disproportionately large single-site losses.
- A single 30-day unplanned shutdown on a high-throughput operation can cost tens of millions of dollars, a scale of loss that dwarfs typical equipment maintenance budgets.
Country impact
| Country | Impact | Reason |
|---|---|---|
| Australia | High | Australian Mining reported FM Global's loss-engineering data as directly relevant to Australia's large-scale mining sector, where bulk commodity operations depend heavily on continuous conveyor and mobile-equipment uptime. |
Industry impact
| Industry | Effect | Reason |
|---|---|---|
| Mining | Negative | Unplanned downtime from equipment failure and fire represents a systemic cost across the mining industry -- 75% of insured losses trace to lost production during repairs rather than the repair cost itself, directly affecting operators' output, shipment schedules and insurance costs. |
Who gains, who loses
- Mining insurers and risk engineers such as FM Global: Detailed loss data and site-level risk modelling let insurers price risk more precisely and position their engineering services as a way for operators to cut both losses and premiums.
- Operators that invest in targeted downtime prevention: Companies that use this kind of failure-mode data to direct maintenance and redundancy spending at their highest-risk equipment and sites can protect production volumes that would otherwise be lost to unplanned shutdowns.
- Operators with concentrated single-point failure risk: Sites that haven't addressed redundancy around critical equipment like conveyors remain exposed to the kind of extended, high-cost shutdowns the data shows drive most industry losses.
Other ways this could play out
- Wider adoption of predictive maintenance and IoT-based condition monitoring could shift the loss ratio over time if operators act on FM Global's data by catching equipment issues before they cause unplanned downtime.
- If prevention spending stays concentrated on physical-damage repair rather than business-interruption risk, the 75/25 split FM Global describes could persist largely unchanged across the industry.
Price risks
- An unplanned, extended shutdown at a major single-site operation (of the kind responsible for a disproportionate share of industry losses) could tighten supply and support prices for the affected commodity.
- Broader adoption of downtime-prevention technology across the industry could gradually reduce the frequency of supply-disrupting shutdowns over time, a mild offsetting factor against future price spikes tied to operational disruptions.
Historical comparison
- Decade-long loss analysis (through 2026): FM Global's engineering review of ten years of mining-industry losses found the 75% business-interruption / 25% physical-damage split has held consistently, with conveyors the leading single equipment-failure cause throughout.
Technical view
Price is mixed relative to its 20-period and 50-period moving averages, showing no clear trend alignment.
Computed from metalscost.com's own stored price history.
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