Equipment Availability in Mining: How to Calculate and Improve It

The Correct Availability Formula for Mining

The correct formula for equipment availability in a mining context is:

This looks straightforward, but the critical detail lies in the definition of productive hours. This is where most operations get it wrong.

What Are Productive Hours?

Productive hours are not simply 24 hours in a day. They are the planned operating hours for a machine after subtracting any planned maintenance allocation. In other words, productive hours represent the time during which the machine is expected to be working or available for work.

Every mining operation has a shift configuration that defines how the day is structured. A typical configuration might allocate 20 hours for production across two shifts and reserve 4 hours for planned maintenance, inspections, and shift changeovers. In this example, the productive hours are 20, not 24.

Planned Maintenance Does Not Reduce Availability

This is a crucial concept that is frequently misunderstood. Planned maintenance (PM) is a scheduled, expected allocation of time. Because it is planned and accounted for in the shift configuration, it is already excluded from the productive hours denominator. Planned maintenance does not reduce availability. It is part of good practice and is built into the operating plan.

Only unplanned breakdowns reduce availability. These are the events where a machine fails unexpectedly and cannot operate during time that was allocated for production.

A Worked Example

Consider a haul truck operating on a shift configuration that allocates 20 productive hours per day (with 4 hours reserved for planned maintenance and shift change). During the day, the truck experienced 2 hours of unplanned breakdown due to a hydraulic hose failure.

Notice that the 4 hours of planned maintenance did not affect the availability calculation at all. The truck achieved 90% availability because it was available for 18 out of its 20 productive hours. If the truck had experienced zero breakdowns, it would have achieved 100% availability, even though it was not physically running for 24 hours.

Common Mistakes in Calculating Availability

Availability is one of the most misreported metrics in mining. Here are the most common errors that lead to inaccurate figures and poor decision-making.

1. Using 24 Hours as the Denominator

The most widespread mistake is dividing by 24 calendar hours instead of actual productive hours. When you use 24 hours as the denominator, your availability will always appear lower than it truly is. A machine with 2 hours of breakdown on a 20-hour productive day would show 91.7% with a 24-hour denominator instead of the correct 90%. While this might seem like a small difference, it distorts trends and makes benchmarking against industry standards unreliable.

2. Counting Planned Maintenance as Downtime

Some operations include planned maintenance hours in the breakdown or downtime category. This penalises the maintenance team for doing exactly what they are supposed to do. Planned maintenance is a proactive investment in reliability. When it is counted as downtime, the availability figure drops artificially, and there is a perverse incentive to skip or delay PMs to make the numbers look better. This is the fastest path to catastrophic equipment failure.

3. Not Accounting for Shift Configurations

Different equipment classes often have different shift configurations. A primary loader might operate on a 22-hour productive schedule while support vehicles might only be configured for 16 productive hours. If you apply a single denominator across all equipment, your fleet availability figures will be meaningless. Each machine or equipment class must be measured against its own configured productive hours.

4. Mixing Calendar Time with Productive Time

Weekly and monthly availability reports sometimes mix daily productive hours with calendar-based totals. For example, multiplying 24 hours by 30 days to get a monthly denominator of 720 hours, when the actual productive hours might only be 600. This inconsistency makes it impossible to track genuine trends over time and leads to confusion when comparing daily reports to monthly summaries.

What Affects Equipment Availability?

Understanding what drives availability down is the first step toward improving it. Here are the primary factors that cause unplanned downtime in mining operations.

How to Improve Equipment Availability

Improving availability is not about working harder. It is about building systems that prevent breakdowns, catch issues early, and minimise the time machines spend out of service.

1. Invest in Proactive Planned Maintenance

The single most effective lever for improving availability is a well-executed planned maintenance programme. This includes scheduled services at manufacturer-recommended intervals, condition-based monitoring, oil sampling, and component life-cycle tracking. Every hour spent on planned maintenance prevents multiple hours of unplanned breakdown. Operations that achieve a ratio of 80% planned work to 20% unplanned work consistently outperform their peers in availability.

2. Track Breakdowns in Real Time from the Control Room

When a machine goes down, the clock starts immediately. A modern control room should capture the exact time a breakdown occurs, the reason category, and the expected resolution. Real-time tracking ensures that breakdown events are recorded accurately, not estimated or back-filled from memory at the end of a shift. It also triggers immediate response from the maintenance team, reducing the time between failure and repair.

3. Implement Shift-Based Reporting

Availability should be reported per shift, not just per day or per month. Shift-level granularity reveals patterns that daily averages hide. You might discover that night shifts have consistently lower availability due to delayed maintenance response, or that specific operators are associated with higher breakdown rates. Shift-based reporting creates accountability and enables targeted interventions.

4. Analyse Breakdown Patterns

Not all breakdowns are random. Many are repeat failures caused by the same root issue. Tracking breakdown reasons by category (engine, hydraulics, electrical, tyres, structural) and by specific component allows the maintenance team to identify chronic problems and address them systematically. Pareto analysis of breakdown types often reveals that 20% of failure modes account for 80% of downtime.

5. Use Fleet Projection to Optimise Maintenance Windows

Fleet projection is the practice of forecasting when each machine will be due for its next planned service based on current operating hours and service intervals. By projecting maintenance requirements across the entire fleet, planners can schedule services to avoid having too many machines offline at the same time. This maximises the number of available machines at any given moment and prevents production bottlenecks caused by maintenance clustering.

Availability Benchmarks in Mining

What constitutes good availability? The answer depends on the type of equipment, its age, and operating conditions, but industry benchmarks provide a useful reference point.

World-class mining operations target 85% to 92% availability as their standard operating range for primary production equipment. Achieving this consistently requires not just good maintenance practices but also accurate measurement, robust tracking systems, and a culture of continuous improvement.

It is worth noting that availability targets should be set per equipment class. A fleet of new haul trucks should achieve higher availability than a set of aging support vehicles. Setting a single availability target across all equipment is a common management mistake that masks genuine performance issues.

How FanaGaLo Tracks Equipment Availability

FanaGaLo is a cloud-based CMMS platform built specifically for mining operations. Availability tracking is not an afterthought or an add-on. It is at the core of how the system works.