Operations

Mining Production KPIs and Core Calculations

A. Introduction

Fleet-management data becomes useful only when the underlying KPIs are clearly defined.

This article covers the most important production-control concepts:

  • Production
  • Productivity
  • Equipment time states
  • Physical Availability (PA)
  • Use of Availability (UA)
  • Loader and truck cycle time
  • Excavator productivity
  • Truck productivity
  • Match factor

The exact definitions may vary between mine sites. Every operation should maintain an approved KPI and time-classification dictionary.

B. Production

Production measures the total material moved during a defined period.

Common units include:

  • Tonnes per hour
  • Tonnes per shift
  • Tonnes per day
  • Bank cubic metres per hour
  • Number of trips

Production should be compared with:

  • Shift target
  • Daily plan
  • Material target
  • Source and destination plan

A high tonnage result is not enough if the wrong material was moved.

C. Productivity

Productivity is output per unit of productive time.

Productivity=Total outputWorking hours\text{Productivity} = \frac{\text{Total output}}{\text{Working hours}}

Possible units include:

  • tonnes/hour
  • BCM/hour
  • trips/hour

Example:

A loader produces 1,050 tonnes during seven working hours.

=1,0507=150 tonnes/hour\begin{aligned} &= \frac{1,050}{7}\\ &= 150\text{ tonnes/hour} \end{aligned}

Always state the time basis. Productivity based on working hours is different from production divided by total scheduled shift hours.

D. Equipment Time States

A simplified time relationship is:

MOHH = WH + SH + BD
Scheduled Time = Working Hours + Standby Hours + Breakdown/Repair Hours

Different sites may use different terms, such as:

  • MOHH (Machine on Hand Hours)
  • Scheduled Machine Hours
  • Available Hours
  • Operating Hours
  • Mechanical Downtime

Do not mix these terms without checking their definitions.

Working hours (WH)

Working time is the period in which equipment performs productive activities.

For a haul truck, this may include:

  • Spotting
  • Loading
  • Hauling loaded
  • Dumping
  • Returning empty

Some sites also count queueing as operating time. Others classify it separately.

Standby (SH)

Standby means the unit is mechanically ready but not working.

Examples:

  • No operator
  • No production requirement
  • Waiting for instruction
  • No supporting equipment

Standby is not always waste. Some standby may be planned. Usually, a delay is categorized as SH too.

Delay

A delay is an interruption to productive work.

Examples:

  • Meal break
  • Prayer break
  • Shift change
  • Refueling
  • Blasting clearance
  • Road obstruction
  • Waiting for supervision

A delay may be classified as controllable, uncontrollable, planned, unplanned, internal, or external.

Breakdown and maintenance downtime

Downtime occurs when equipment cannot operate because of a mechanical or electrical condition.

Examples:

  • Unscheduled repair
  • Planned maintenance
  • Tyre repair
  • Component replacement
  • Electrical troubleshooting

Many sites separate planned maintenance from breakdown, so the site definition must be checked.

E. Physical Availability (PA)

A common simplified formula is:

PA=Scheduled timeDowntimeScheduled time×100%PA = \frac{\text{Scheduled time}-\text{Downtime}} {\text{Scheduled time}} \times100\%

PA=MOHHBDMOHH×100%PA = \frac{\text{MOHH}-\text{BD}} {\text{MOHH}} \times100\%

Example:

  • Scheduled time: 12 hours
  • Downtime: 2 hours
PA=12212×100%=83.3%PA = \frac{12-2}{12}\times100\%= 83.3\%

Physical Availability answers:

How much of the scheduled time was the equipment mechanically available?

F. Use of Availability

A common simplified formula is:

UA=Working timeScheduled timeDowntime×100%UA = \frac{\text{Working time}} {\text{Scheduled time}-\text{Downtime}} \times100\%

UA=WHMOHHBD×100%UA = \frac{\text{WH}} {\text{MOHH}-\text{BD}} \times100\%

Example:

  • Scheduled time: 12 hours
  • Downtime: 2 hours
  • Working time: 7 hours
UA=7122×100%=70%UA = \frac{7}{12-2} \times100\%= 70\%

Use of Availability answers:

How much of the available time was actually used?

G. Payload Performance

Average payload alone can hide inconsistency.

A better payload review includes:

  • Average payload
  • Median payload
  • Standard deviation
  • Percentage underloaded
  • Percentage within target
  • Percentage overloaded
  • Payload by loader, operator, truck, and material

The objective is not the highest possible payload. The objective is stable loading within the approved range.

H. Loading-Unit Cycle Time

A typical excavator bucket cycle includes:

  1. Digging
  2. Swinging loaded
  3. Dumping
  4. Swinging empty

[
CT_b =
t_{dig}
+
t_{swing\ loaded}
+
t_{dump}
+
t_{swing\ empty}
]

Truck loading time consists of several bucket cycles:

[
\text{Loading time}
\approx
\text{Number of passes}
\times
\text{Average bucket cycle time}
]

Other factors include:

  • Truck spotting
  • Truck exchange
  • Loader repositioning
  • Face cleanup
  • Fragmentation
  • Bucket fill
  • Operator technique

Cycle time can be measured through manual observation, video, onboard systems, or FMS events.

Manual observation remains useful for validating automatic timestamps.

I. Haul-Truck Cycle Time

A truck cycle usually includes:

  1. Queueing at loader
  2. Spotting at loader
  3. Loading
  4. Travelling loaded
  5. Queueing at dump
  6. Spotting at dump
  7. Dumping
  8. Returning empty

[

CT_{truck}

t_{queue\ loader}
+
t_{spot\ loader}
+
t_{load}
+
t_{loaded\ travel}
+
t_{queue\ dump}
+
t_{spot\ dump}
+
t_{dump}
+
t_{empty\ travel}
]

The start and end points must be consistent. Different reports may use arrival-to-arrival, dump-to-dump, or loading-completion-to-loading-completion definitions.

Excavator Productivity

There are several valid calculation methods.

Bucket-based estimate

[

Q_{excavator}

\frac{3600}{CT_b}
\times q
\times FF
\times \rho_l
\times E
]

Where:

  • (CT_b) = bucket cycle time in seconds
  • (q) = bucket capacity in loose cubic metres
  • (FF) = fill factor
  • (
    ho_l) = loose density in tonnes per loose cubic metre
  • (E) = efficiency factor

This method is useful for estimating potential capacity.

Truck-service method

[

Q_{loader}

\frac{3600}
{t_{loading}+t_{truck\ exchange}}
\times
\text{Average payload}
]

This method is useful when loading-event and payload data are reliable.

Actual productivity

[

Q_{actual}

\frac{\text{Actual tonnes loaded}}
{\text{Actual working hours}}
]

This method is best for reporting achieved performance.

These formulas answer different questions and should not be treated as interchangeable.

Truck Productivity

For one truck:

[

Q_{truck}

\frac{3600}{CT_{truck}}
\times P
\times E
]

Where:

  • (CT_{truck}) = truck cycle time in seconds
  • (P) = average payload
  • (E) = efficiency factor

Be careful not to double-count losses. If actual cycle time already includes normal delays, applying another general efficiency factor may reduce the result twice.

For identical trucks:

[

Q_{fleet}

N
\times
Q_{truck}
]

For mixed fleets:

[

Q_{fleet}

\sum_{i=1}^{n}Q_i
]

Match Factor

Match factor compares hauling capacity with loading capacity.

A simplified formula is:

[
MF =
\frac{N_t \times Q_t}
{Q_l}
]

Where:

  • (N_t) = number of trucks
  • (Q_t) = productivity per truck
  • (Q_l) = loader productivity

Interpretation:

  • (MF < 1): hauling capacity is lower than loading capacity
  • (MF \approx 1): capacities are approximately balanced
  • (MF > 1): hauling capacity is higher than loading capacity

Under-match

Possible effects:

  • Loader waiting
  • High hanging time
  • Underused loading capacity
  • Lower production

Over-match

Possible effects:

  • Truck queueing
  • Increased idle time
  • Higher fuel use
  • Lower truck productivity

Exactly 1.00 is not always the practical optimum.

The best target depends on:

  • Cycle-time variability
  • Equipment reliability
  • Mixed truck fleets
  • Material priority
  • Haul distance
  • Cost of truck waiting
  • Cost of loader waiting

A control band such as 0.90–1.10 may be useful at one site, but it is not a universal standard.

Worked Example 1: Under-Matched Fleet

Given:

  • 3 trucks
  • 55 tonnes/hour per truck
  • Loader productivity of 250 tonnes/hour

[
MF =

\frac{3\times55}{250}

0.66
]

The fleet is under-matched.

With four trucks:

[
MF =

\frac{4\times55}{250}

0.88
]

With five trucks:

[
MF =

\frac{5\times55}{250}

1.10
]

The correct choice depends on production requirements, variability, and cost.

Worked Example 2: Over-Matched Fleet

Given:

  • 6 trucks
  • 60 tonnes/hour per truck
  • Loader productivity of 300 tonnes/hour

[
MF =

\frac{6\times60}{300}

1.20
]

The fleet is over-matched.

With five trucks:

[
MF =

\frac{5\times60}{300}

1.00
]

Under stable assumptions, five trucks provide a theoretical balance.

Cost per Tonne

High production does not always mean economic efficiency.

[

\text{Cost per tonne}

\frac{\text{Total operating cost}}
{\text{Total tonnes moved}}
]

Operating cost may include:

  • Fuel
  • Tyres
  • Maintenance
  • Labour
  • Equipment ownership
  • Road maintenance
  • Support services

Production, productivity, and cost should be reviewed together.

Conclusion

Mining KPIs are useful only when their definitions are consistent.

Before comparing equipment, shifts, or fleets, confirm:

  • What time basis is being used
  • How delays are classified
  • Whether payload data is reliable
  • How cycle time is defined
  • Whether efficiency losses are already included
  • Whether the fleet is homogeneous or mixed

A correct formula with inconsistent inputs still produces a misleading result.

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