Issues are validated by 24/7 condition monitoring analysts before triggering automated work orders through TOMS, the Tire and Operations Management System
The Number That Leads
According to Kal Tire’s published case comparison, two mines running 57-inch haul truck tires produced sharply different outcomes when they committed to different strategic priorities using the same tire management software.
The site focused on fleet availability averaged 4.3 tire changes per tire and accepted a 5% reduction in tire life. In exchange, it captured $10 million in additional truck use. The site prioritizing tire longevity averaged 6 changes, extended tire life by 13%, and saved $500,000 in replacement spend.
Both numbers matter — but they answer different questions. The $500,000 outcome is a cost reduction. The $10 million outcome is a production decision. Treating them as interchangeable is a strategic error that most tire management conversations quietly make.
Separately, an Australian mine reported saving 233 hours of planned downtime over 12 months by using AI-enhanced planning within the same system. These figures originate from Kal Tire’s own reporting and have not been independently audited — which matters for how you weight them — but the scale of the differential is operationally significant regardless of where the precise margin lands.
What Sits Behind the Number
The mechanism is a layered technology stack, not a single monitoring tool. Kal Tire’s KalPRO TireSight uses thermal imaging cameras powered by Pitcrew AI to detect early tire damage — hot spots, tread issues, belt separation — without requiring trucks to stop for inspection. Issues are validated by 24/7 condition monitoring analysts before triggering automated work orders through TOMS, the Tire and Operations Management System.
TOMS is where data becomes strategic. Using AI modeling aligned to each site’s defined objectives — whether tire life, fleet availability, or a hybrid — the system identifies what tire work is needed, when, and how orders can be grouped to minimize unplanned stoppages. Kal Tire reports that performance data in TOMS is drawn from more than 12,000 pieces of equipment across commodities, tire sizes, and site conditions, giving the system reference points a single-site approach cannot replicate.
A second layer, KalPRO HaulSight, was developed in collaboration with Decoda and places truck-mounted sensors across haul roads to detect non-compliant berm heights, spillage, and road undulations in real time. This is an upstream intervention — reducing tire damage at the road-tire interface before degradation begins, rather than catching it at the inspection stage.
The combined effect shifts the maintenance model from scheduled inspections triggered by elapsed time or visible failure to continuous condition monitoring that escalates priority work as it develops. Some sites have reportedly reduced truck isolation time for hot tire events to zero hours, meaning thermal issues are resolved before they become unplanned shutdowns.
What This Is Worth in Your Operation
For a Mining Operations Director running a large surface fleet, the real question is not whether to adopt tire monitoring technology — most operations already carry Tire Pressure Monitoring Systems. The question is whether existing monitoring infrastructure is connected to production planning, or whether it still operates as a standalone maintenance alert with no visibility into fleet scheduling.
The case comparison illustrates the cost of leaving those two functions disconnected. A site that monitors tires for safety and maintenance but does not feed tire service events into fleet planning carries a quantifiable productivity gap — unmanaged and uncosted. When commodity prices are high and throughput drives the revenue line, a strategy optimized for tire life at the expense of truck availability is a misaligned priority. The converse applies when margins are compressed and capital conservation becomes the operating directive.
The 41% reduction in tire technician exposure to trucks at the availability-focused site is a secondary signal worth tracking independently. Reduced technician-to-truck interaction is a measurable safety outcome, and it broadens what tire strategy delivers beyond uptime and cost.
Operations working toward autonomous or semi-autonomous fleet transitions should also note that sensor-connected tire management systems are already operating at scale — not in pilot. That integration precedent is relevant to how tire strategy fits into a broader equipment intelligence framework as fleet architectures evolve.
What the Data Does Not Say
The cases presented originate from Kal Tire’s own commercial reporting. No independent third-party audit of the figures has been disclosed, and neither mine site is named or independently described. The 233 hours saved and the $10 million productivity figure should be treated as directional indicators, not verified benchmarks transferable across all operational contexts.
Site conditions introduce material variation. Haul road quality, ore hardness, elevation change, and fleet specification all influence tire wear rates in ways that a cross-fleet dataset can approximate but not fully resolve at the individual site level. An operation running at high altitude, under heavy cyclic loading, or with road maintenance constraints may see outcomes that diverge materially from the published cases.
The 12,000-equipment dataset is cited without a breakdown by commodity type, geographic region, or tire size category. Its statistical applicability to any specific operation — particularly those at scale in geologically complex or climatically demanding environments — is not established from the available evidence.
The Implementation Question
Before committing budget to an integrated tire management platform, take one question to your fleet and maintenance teams: are your current tire service events visible in your production planning system, and if not, can you quantify what that blind spot costs you per operating quarter?
If tire data lives only inside the maintenance function, the strategic capability described in these cases does not yet exist in your operation — regardless of what monitoring hardware is already installed. Connecting those systems is less a technology investment than a planning model decision, and that framing determines who needs to be in the room when the procurement conversation starts.
Sources
- Mining — How Innovation, Data & Strategy Are Redefining Mining Tire Performance (Link)
