Fpo application guide ver 11 26 11-04

FPO Application Guide 1 of 32 Version 11
Table of Contents
Nomenclature 2
1. Introduction 4
2. General overview of a typical Haul Road 5
2.1. Load Area & Pit Floor 5
2.2. Main Haul Road 6
2.3. Waste Dump 7
3. Guidelines for collecting representative haul road cycle data 8
4. Composite Pressure Limits 9
4.1. Background 9
4.2. Composite pressure limit values 9
5. Mine Severity Index 11
5.1. Haul Road Condition index 11
5.2. Payload Distribution index 13
5.3. Mine Severity Index estimation 14
5.4. MARC rates estimation using MSI data 15
6. Machine performance and haul road assessment using control charts 18
6.1. Speeds on curves and superelevation 18
6.2. Manoeuvring in dump areas 26
6.3. Gear selection 27
6.4. Crossfall 30
7. Acknowledgements 31
8. References 31
9. Appendices 32
NOTE: This document should be read in conjunction with the FPO User Manual located in the Guides/Tools
section of the Caterpillar Knowledge Network Community: “Mining Project Manager’s Toolkit”. For those
Cat/Dealer staff with a Corporate Web Security logon, visit:
https://kn.cat.com/guides.cfm?id=6232
Caterpillar Confidential: Green
FPO Application Guide
Mining Fleet Productivity Optimization
Version 11 - 26 November 2004

Nomenclature
Abbreviations
LF: Left-Front position. RF: Right-Front position.
LR: Left-Rear position. RR: Right-Rear position.
OHT: Off-highway Truck, such as 785, 793 and 797 trucks.
GMW: Gross Mass Weight.
Definitions
Machine Rack: or just Rack, is the difference between strut pressures diagonally across the
centre of the truck; i.e. (LF + RR) - (RF + LR) which tend to ‘twist’ the frame, and highly
load machine components.
Machine Bias: or just Bias, shows whether placement of the load is central or to one side of
the truck during the loading cycle (Payload BIAS). It also shows whether significant
‘dynamic’ loading is occurring as the machine negotiates cross-slopes, or corners at speed
where super-elevation is not sufficient; called ‘Machine BIAS’. Both Payload BIAS and
Machine BIAS are defined as the difference in strut pressures between the totals down each
side of the truck; i.e. (LF + LR) - (RF + RR)
Machine Pitch: or just Pitch, is the difference between the totals of strut pressures of both
front wheels and both rear wheels; i.e. (LF + RF) - (LR + RR). By design, axle loading
should generate rear strut pressures equal to approximately double front strut pressures.
Composite strut pressures: Any of the Rack, Bias or Pitch pressures.
10/10/20 payload rule: The mean of the Payload distribution shall not be more than the
Rated/Target Payload; no more than 10% of loads may exceed 1.1 times Rated/Target
Payload, and no single load shall exceed 1.2 times Rated/Target Payload.
Variations in 2-second interval - Frame twisting can be more severe than the overall value
indicates if the rate of change is fast. Twisting over a longer time span will cause less distress
than a quick reaction.
Minimum strut pressure - Values as low as 1800 kPa are cause for concern as this is the
approximate charging pressure of the suspension cylinder. A low pressure may indicate that
the cylinder piston could be contacting the head.
Axle split – Caterpillar trucks are designed to generate a distribution of approximating 33%
front axle, 66% rear axle when loaded. Strut pressures in the table approximate this
condition. Consistent operation outside this design level will cause a corresponding reduction
to the life of the components listed previously, such as frame and suspension cylinders.
Rolling Resistance This is described as the measure of force that must be overcome to
roll or pull a wheel over the ground. Rolling resistance is effected by ground conditions and
vehicle load. The deeper the wheel sinks into the ground the higher the resistance to motion.
Effects on Components – Increase in fuel burn with high rolling resistance which inturn
reduces engine life. Increased loads on final drives, wheel bearings, tyres and drive train
to drive through high rolling resistances.
Effects on Production – High rolling resistance increases haulage cycle times and
operating costs due to elevated fuel burn rates and reduced production outputs.
Super Elevation The purpose of superelevation is to maintain even pressure distribution
over the machine suspension and safely maximise the speed of the truck through the radius of
the corner. The recommendation of superelevation for a corner depends on the radius and the
desired speed to negotiate. Superelevation is incorporated to minimise lateral tyre forces.

Effects on Components – Too little superelevation increase loads to wheel bearings,
steering components, chassis and suspension cylinders. Tyre wear will also increase with
poor superelevation.
Effects on Production – With negative or little superelevation production costs increase
due to increased tyre wear, reduced safe operating speeds and increased cycle times,
increase road maintenance due to spillage and gouging from tyres. With correct
superelevation operator comfort in improved due to the reduce G-forces and reduced
effort of negotiating the corner.
Gradient The suggested grade for caterpillar trucks is the one that will keep the truck
within second transmission gear. The estimation of such grade should consider a range for
rolling resistance, which typically falls between 1.5% to 2.5%. Performance Handbook or
FPC software may be used to evaluate these conditions.
Effects on Components – Increased gradients increase fuel burn and brake wear, reduce
transmission and drive train life due to higher energy shifts up ramps and higher energy
braking when travelling down ramps loaded.
Effects on Production – Increased fuel costs, increased cycle times, increased spillage
requiring more clean up, tyre damage to trailing trucks from spillage and possible
bunching of haul trucks if split fleets are working on the same ramp.
Crossfall Crossfall is the difference in elevation between the road edges, used to drain
water from the haul road. The recommended maximum Crossfall is 3% to allow water
drainage [Guiachi, 1990].
Effects on Components – Too much Crossfall increases tyre wear, wheel bearing and
final drive loads.
Effects on Production – Too much Crossfall increased tyre costs and pending of road
base could cause scoring or erosion.
Too little Crossfall may causes excessive water accumulation on the Haul Road.
Vertical Curves Vertical curves are the curves from the point of flat gradients to either
descending or ascending ramps. For instance the top of the ramp and the bottom of the ramp.
A general rule is a minimum of 100m of Sag radius and Crest Vertical Curve.
Effects on Components – With sharp Vertical curves on the ascend to the ramp can
cause harsh down shifts and heavy drive train loads.
Horizontal Alignment This relates to switch backs, corners and intersections. The
minimum radius of a horizontal curve for a given vehicle speed can be determined on the
type of gradients and land available.
Effects on Components – Tight sharp switch backs and corners cause severe loads on
final drives and wheel bearing parts. Tyre wear increases as well. Heavier braking is
required to negotiate sharp corners causing increased brake temperatures and reduced
component life.
Effects on Production – Increases in spillage can occur when both corners and
superelevation is incorrect. This also adds loads and erosion to the road surface as well as
increasing cycle times negotiating sharp corners.

1. Introduction
This document builds upon data collected from ‘real-time’ TPMS, or 'data logger' VIMS files
that have been analysed using the Fleet Productivity Optimisation (FPO) software program. It
allows a quantitative assessment of haul road condition and its interrelationship with the truck.
Such analysis can be used to develop improvement strategies, and to trend the effect of past
actions and mining programs.
Once data has been graphed using FPO, plots can be reviewed to determine whether individual,
and/or composite strut pressures are exceeding ‘Management Limits’. It is then possible to
identify opportunities for improvement of the haul cycle using a ’Haul Road Condition Index’.
The Haul Road Condition Index is then combined with an assessment of Payload data, to
establish a ‘Mine Severity Index’. Once an initial ‘index’ has been determined, continued regular
analysis of haul road condition and Payload history can be scheduled to help identify areas in
need of attention, and to maintain these improvements.
Release of VIMS Supervisor has significantly improved a Project Manager‘s ability to analyse
Payload data from a fleet of trucks, using the Fleet Payload Summary and Payload Management
options. Conformance with CAT’s 10/10/20 Payload policy can quickly be determined.
Application Severity Analysis (ASA) is the name for previous versions of FPO. It was found
amongst ASA users that by assessing machine severity and reporting the associated values to the
customer, it did not provide the correct language to explain to the Truck users how they can
reduce the overall cost per ton with ASA.
The name ASA was changed to FPO to highlight the opportunity this software provides to
improve operating conditions and to create a win-win situation between Truck’s users and
Maintenance people. In this new approach, FPO user would analyse where haul road defects are
and how machine application can be improved , instead of rating machine severity alone.
FPO is increasingly being used in MARC contracts with MARC contract rates conditional on
Mine Severity Index ratings for Payload and Haul Road Condition indices. While this move is
commendable and a logical extension of the FPO theory it should be remembered that the
program was initially intended as a tool to help identify and address haul road design and
maintenance issues in a constructive dealer/customer relationship rather than a punitive process.
As a result of the push towards better management of MARC contracts there has been an
increasing need to quantify Mine Severity ratings against expected increases (and decreases) in
contract costs. At present there is nothing more to offer than general comment, as field data to
relate these two factors is unavailable. Any data from sites that are in a position to correlate
longer term operating costs against haul road conditions will be always welcomed.

2. General overview of a typical Haul Road
2.1. Load Area & Pit Floor
Depending on environmental conditions, the loading tool, and support equipment available. The
conditions in the loading area can vary dramatically.
Compare the extremes in conditions on Figures 1 and 2. The condition shown in Figure 1 is a
hard rock gold mine in Australia with very little rainfall. The second one shown in Figure 2 is an
iron ore mine in southern Australia with poor material for building roads, higher rainfall, and
environmental regulations that stipulate rainwater must be drained into the pit, not into a close-
by river.
Look at the floor conditions. What are the differences?
Wet floors mean increased chance of tyre cuts.
Rough floor conditions are uncomfortable for the operator and production is slowed.
Cramped conditions mean truck exchange time is slowed along with production.
What are some possible solutions?
Change drainage or slope the pit floor to keep water away from the loading zone?
Sheet the floor with rock or high-grade ore (if there is concern about ore dilution)?
Is the support equipment being utilised effectively if nothing else is possible?
Can the operator lock the truck in 1st
gear to reduce the impact load on the truck? (Remember
impact load is a function of vehicle weight and ground speed)
Figure 1 – Hard Rock Gold Mine pit floor conditions

Figure 2 – Iron Ore Mine pit floor conditions
2.2. Main Haul Road
In some FPO traces, you may find the main haul road does not generate any composite strut
pressure spikes outside the management or “limit” lines.
However, consider the two primary road features that generate FPO spikes outside the
management limits:
Off camber corners cause weight transfer to the outside tyres and a bias spike. Use the
Caterpillar Performance Handbook (Chapter 26) or table 1 to determine the correct
superelevation for a given corner radius and desired travel speed.
Table 1 – Superelevation in curves (Taken from Caterpillar Performance Handbook)
Truck Speed (kph)Turn
radius
(m) 16 24 32 40 48 56 64 72
15 13% 30% - - - - - -
30 7% 15% 27% - - - - -
45 4% 10% 18% 28% - - - -
60 3% 8% 13% 21% 30% - - -
90 2% 5% 9% 14% 20% 27% - -
150 1% 3% 5% 8% 12% 16% 21% 27%
200 1% 2% 4% 6%. 9% 12% 15% 19%
300 1% 2% 3% 4% 6% 8% 11% 14%
Potholes and other road defects can generate rack spikes if struck by a single wheel.
Potholes should be ripped, filled, watered and compacted to repair them, and the road crown
or Crossfall should be checked and repaired if necessary to reduce standing water on the
road.

2.3. Waste Dump
The waste dump is often a neglected section of the haul cycle. In addition, since dumps are
generally flat, loaded trucks can accelerate to higher ground speeds and increase the magnitude
of impact on major components.
What can be done on waste dumps to improve machine application?
Can we build a good quality single lane road most of the way across the dump so loaded
trucks can travel quickly to the tip head?
Can we sheet the floor with rock? Or even high-grade ore if the customer is concerned about
ore dilution?
Are operators braking parallel to the tip head, THEN turning to reverse back, or are they
generating large bias spikes and frame stresses by conducting high speed turns?
Is the support equipment being utilised effectively to minimise the impact of the dump area?
Can the operator lock the truck in 1st
gear to reduce the impact loading on the truck?

3. Guidelines for collecting representative haul road cycle
data
The following steps provide a guideline to capture representative data, which will maximise the
accuracy of sampled haul road condition the machines are experiencing, and importantly,
customer credibility will be established and maintained.
Ensure the chosen truck to collect the sample data has correct suspension cylinder oil and
nitrogen charge, and is considered to be performing normally (i.e.. power, ride, shift points,
etc.).
All suspension cylinders should be completely discharged, and then recharged with oil, then
nitrogen at least once every 12 months or 6000 hours.
The condition of the grease relief fitting in front struts is assessed regularly to ensure it is not
becoming blocked, as grease can be forced into the oil/nitrogen space if it blocks. There
should be small amounts of grease present at the fittings in normal operation.
When taking real-time TPMS data, be sure to set the Real Time Log Delay to one (1) second
intervals. The FPO program will not accept data if taken at any other time intervals.
Be sure that recordings of the haul cycle are truly representative of a typical haul. To ensure
this, observe several load cycles before collecting data, and ride with the operator a time or
two.
When feel comfortable for the cycle, set the recorder (TPMS or VIMS Data Logger) running
as the truck waits in the queue about to drive under the loader, then, once loaded, follow
along behind in a light vehicle to observe that the truck:
o has a typical payload, both in tonnage and load position (i.e. no significant BIAS)
o is not obstructed by a grader, or another machine stopped on the haul road
o is operated as normal, and is not ‘babied’ just because you are watching
Drive the complete haul cycle in a light vehicle and record ‘features’ that may influence the
cycle, and their distance from the loading zero point. By recording this haul road features, a
better interpretation of FPO data would be done when analysed. Time and distance from the
loading zone can be written down using a stopwatch and the pick-up truck’s odometer. It is
advisable to record features such as:
o the beginning and end of the Loading and Dump zones
o the location of all significant corners, curves and switchbacks
o the beginning and end of haul road grade changes
o any speed restriction zones or Stop / Give Way signs
o any road sections with one-way traffic restrictions
o any significant humps, gutters, wash-aways, or rough road sections

4. Composite Pressure Limits
4.1. Background
For some time Caterpillar, Dealers, Decatur CMT and several other Caterpillar subsidiaries have
been collecting strut pressure data from various mine operations and comparing FPO graphical
information with known product performance, component life and actual observations of haul
road conditions.
Analysis of this data suggests that a direct relationship exists between racking of the machine
frame over time, and damage to the frame and other machine components; final drive & wheel
bearing components, tyres & rims, steering ball studs, ‘A’ frame bearings, etc.
Additional studies have been undertaken regarding haul road assessment and truck interaction on
different types of road surfaces. Outstanding work was done by the following authors:
• Assessment of soft ground roads by using strut pressures and vertical acceleration
[Joseph, 2003; Joseph, T.G. and Sharif-Abadi 2003].
• Designing and managing haul roads for 300+ tonne trucks for optimal performance
[Thompson, R. J. and Visser, A. T. 2002].
• Behaviour of OHT pitch on haul roads [Prem and Dickerson, 1992].
• Analysis of composite pressure limits for Machine Rack and Bias [Trombley, 2001; and
Wohlgemuth, 1997].
There are other factors such as PITCH and BIAS (as a result of poor loading techniques and due
to cornering at speed without adequate super-elevation) and the rate of change of strut pressures
adversely affects the service life obtained from these components.
4.2. Composite pressure limit values
From the experience gained by Caterpillar and other authors listed in the previous section, a table
of composite pressure limits were established. These limits are intended to promote objective
and consistent assessment of haul road conditions and to counter the level of subjectivity that
exists when haul roads are reviewed.
Studies have been done in the design of haul roads (see for example [Giacchi, 1990], but few
studies have been made in proactive haul road maintenance (i.e. Planning and scheduling
maintenance in haul roads) for trucks of over 300 tonnes GMW.
The proposed composite pressure limits attempt to locate and quantify haul road defects that may
be reducing mine productivity. It also attempts to facilitate tasks such as:
• Creation and scheduling of backlogs associated with haul road pending repair jobs
• Programmed maintenance (PM) practices for haul road networks throughout the year
• Develop haul road condition monitoring strategies for haul roads.
Values of composite pressures included in table 2 for models 785 to 797 are the result of
considerable experience, but we recommend values for trucks smaller than 777 be evaluated and
applied carefully. CAT Global Mining welcome comment on the validity of sub-777 and
recently developed parameter values and Management Limits for the 797 truck.

Table 2 – Composite pressure limits for Caterpillar OHT (Pressures in kPa)
Parameter 769 - 777 785 789 - 793 797
Management limit ± 6000 ± 8000 ± 8500 ± 12500
Warning limit ± 10000 ± 12000 ± 12000 ± 16500
Rack and Bias
(Moving truck)
Action limit ± 14000 ± 16000 ± 16000 ± 20000
Bias (loading stationary truck) ± 3000 ± 3000 ± 4000 ± 5500
Max. variation in 2 sec interval ± 5500 ± 7000 ± 8000 ± 12000
Maximum Strut Pressure ± 12000 ± 14000 ± 14000 ± 22700
The Management, Warning and Action limits shown above are used in assessing dynamic
machine loading situations, as measured using ‘real time’ TPMS or VIMS Data Logger data
taken during the ‘Travelling Loaded’, and ‘Travelling Empty’ cycles.
Loading stationary truck Bias pressure limit is to be used during the loading phase.
By assigning limit values to composite pressure graphs during plotting and printing, control
charts can be easily generated to assess and analyse machine and haul road performance.
It is important to note that the Haul Road Condition Index shown in the next section used to rate
a particular haul road cycle are not absolute numbers, but are intended to establish criteria that
help indicate where the opportunities for improvement are. They have been developed by
comparing practical field data with historical component life data on many mine sites around the
world.
It is also advisable to use these limits in conjunction to RAC FELA numbers to provide a holistic
assessment of the haul road/truck interaction. Refer to RAC Application Guide for more
information.

5. Mine Severity Index
Haul Road Condition index and Payload Distribution index are used to estimate the Mine
Severity Index of the haul road under consideration.
5.1. Haul Road Condition index
Once suspension cylinder pressure data has been assessed using the limits shown in Table 2, a
Haul Road Condition (HRC) index can be assigned to rate the condition of the haul road. HRC
index uses data from the composite pressures control chart of the FPO analysis, and looks at
peak values, or spikes in Machine Rack and Machine Bias pressure traces that exceed
management, warning and action limits.
Table 3a – HRC index logic table number 1
Rating Spikes > ML Spikes > WL Spikes > AL
1 0 AND 0 AND 0
2 1 or 2 AND 0 AND 0
6 9 - 10 AND 0 AND 0
7 11 - 13 AND 0 AND 0
8 14 - 16 AND 0 AND 0
9 17 - 19 AND 0 AND 0
10 20 AND 0 AND 0
Table 3b – HRC index logic table number 2
1
2 1 AND 0
3 2 AND 0
4 3 AND 0
5 4, 5 or 6 AND 0
6 7, 8 or 9 AND 0
7 10, 11 or 12 AND 0
8 13, 14 or 15 AND 0
9 16, 17 or 18 AND 0
10 19 AND 0
Table 3c – HRC index logic table number 3
1
2
3
4
5
6
7
8 1, 2 or 3
9 4, 5 or 6
10 7
Table 3a, 3b and 3c were developed to provide a coherent definition of HRC index under all of
the possible combinations of peaks and pressures. The logic structure presented in tables 3a, 3b

and 3c is more suitable to be translated in computer language than previous versions and is
therefore more easily incorporated in FPO.
Cells shown in grey are not considered during calculation of rating when other logic events take
place. ML, WL, and AL represent Management, Warning and Action Limits respectively.
Table 3a covers conditions where composite pressures exceed ML but there are no spikes
exceeding WL and AL.
If one or more of the spikes exceed WL but none exceed the AL, table 3b should be also
considered.
When composite pressure spikes exceed AL, table 3c must also be used.
The HRC index should be evaluated for each of tables 3a, 3b and 3c. The HRC index will be the
highest index obtained from each of the tables individually.
Table 4 provides examples of how table 3a, 3b and 3c can be used when composite strut pressure
is given.
Table 4 – Examples of Haul Road Condition (HRC) Index evaluation
Condition Rating value Rating yielded by
There are only 6 spikes over ML, no WL, no AL 4 Table 3a
10 spikes over ML and 1 over WL, no AL 6 Table 3a
13 over ML, 16 over WL, and 1 over AL 9 Table 3b
12 spikes over ML, 3 over WL and 1 over AL 8 Table 3c
There are only 4 spikes over AL 9 Table 3c

5.2. Payload Distribution index
An index value can be assigned to Payload Monitor Summary data (through either TPMS or
VIMS) in the same way. The index is called Payload Distribution (PLD) index, and it is based
on Caterpillar's 10/10/20 Payload Rule.
PLD index is generated using a similar logical approach than HRC index (Table 5). PLD index
uses the two payload limits described in 10/10/20 rule.
Table 5 – PLD index ratings
Rating Conditions
A 100% of loads less than 110% of Rated Payload.
B 95% of loads less than 110% of Rated Payload, and none exceeding 120%.
C 90% of loads less than 110% of Rated Payload and none exceeding 120%.
D 85% of loads less than 110% of Rated Payload and none exceeding 120%.
E 80% of loads less than 110% of Rated and/or up to 2% of loads exceeding 120%.
F 75% of loads less than 110% of Rated and/or up to 5% of loads exceeding 120%.
G 70% of loads less than 110% of Rated and/or up to 10% of loads exceeding 120%.
H 65% of loads less than 110% of Rated and/or up to 15% of loads exceeding 120%.
I 60% of loads less than 110% of Rated and/or up to 20% of loads exceeding 120%.
J 55% of loads less than 110% of Rated and/or 20+ % of loads exceeding 120%.
It is highly advisable to evaluate the PLD index using VIMS payload data of the chosen truck
only (not the whole fleet) of the previously used FPO sample record, i.e. weekly fortnightly or
monthly.

5.3. Mine Severity Index estimation
The concept of a Mine Severity Index (MSI) acknowledges the fact that machine application
severity is related to both haul road condition, and machine payload. Previously, both
parameters have been rated on a scale from 1 to 10. HRC and PLD indexes are then compared
together to generate the Mine Severity Index (MSI).
To avoid confusion when reporting the Mine Severity Index (eg. when entering values into
SIMS), the PLD index scale has been changed to a letter scale, i.e. A to J.
It is the intent of the analysis to establish a baseline index of the current haul cycle, then to
reassess conditions at regular intervals to identify, and rectify areas of the haul road causing
significant machine stresses. Feedback of this data to a customer’s Mine Planning and Haul Road
Maintenance departments has proven to be a constructive way of improving both haul road
condition, Payload management, and also in:
Reducing operating costs through extending component life (for customers and sites under
dealer MARC contracts).
Improving productivity (through increased average road speed and reduced cycle times).
Reduced fuel consumption through reduced rolling resistance.
Improving operator comfort and safety (through reduced effort and the onset of fatigue).
Proving the value to the customer of the Caterpillar / Dealer value chain.
In order to remain within design and Gross Vehicle Weight parameters, PLD index should not
exceed a Rating of C. Similarly, HRC index should not exceed a Rating of 5. Therefore, the
highest acceptable MSI would be C5, being the combination of these two Rating numbers.
J
I
H
G
F
UNACCEPTABLE
RANGE
E
D
C X
B
A
ACCEPTABLE
RANGE
PAYLOADINDEX
1 2 3 4 5 6 7 8 9 10
HAUL ROAD CONDITION INDEX
Figure 3 - MSI Rating map
This may be represented graphically, as shown in Figure 3.
Using the graphical method shown in Figure 3 has proven to be a very useful way to illustrate
current Payload management and Haul road conditions to mine management. Using green in the

‘Acceptable Range’ area, red in the ‘Unacceptable Range’ and placing a yellow ‘X’ to show the
current site conditions allows easy identification of current haul road and machine application
situation.
In the example shown in Figure 3, a MSI of C6 has been added, showing that Payload is being
managed within Caterpillar’s 10/10/20 payload rule, but haul road conditions are in need of
attention to bring the HRC index back into the acceptable range.
5.4. MARC rates estimation using MSI data
Figure 4 – Haul Road and Payload distribution sensitivities concept
Two new parameters can be defined to show the influence on Haul Roads and Payload
distribution in MARC associated costs:
Payload distribution sensitivity (SPL)
SPL is the estimated percentage of additional cost MARC rates will increase when trucks are
overloaded while haul roads are in good conditions. In other words, it is evaluated under the
following conditions:
• Payload distribution rated as maximum “J”
• Haul road index rated as “5”, which correspond to an acceptable level.

Haul Road sensitivity (SHR)
It is the estimated percentage by which MARC rates would increase if trucks were experiencing
the poorest haul road conditions at a normal payload distribution. In other words:
• Haul road index rated as maximum “10”
• Payload distribution rated as “C”, which correspond to an acceptable level.
SPL and SHR define two lines that can be integrated to generate a surface for the whole range of
HRC and PLD indexes combinations (Figure 5).
Figure 5 – A surface is generated from the two lines defined by SPL and SHR
If the PLD index is changed to a numeric scale, such that:
A=1 ; and C=3 ; and J=10
then the equation for the plane generated would be:
×+×+×= PLHRPLHR S
7
3
S-(y)S
7
1
S
5
1
z )(x …………… (Eq. 1)
where,
x: Haul Road Condition index
y: Payload Distribution index
z: resulting MARC rate increment axis
Equation 1 can then be integrated back in the MSI rating map (Figure 3). Tables 6 provides an
examples, where:
SPL=17 and SHR=10
Both lines shown in Figure 5 are highlighted in this table.

Table 6 – MARC rates variations using a planar distribution. SPL=17 and SHR=10.
J = 10 9 11 13 15 17 19 21 23 25 27
I = 9 7 9 11 13 15 17 19 21 23 25
H = 8 4 6 8 10 12 14 16 18 20 22
G= 7 2 4 6 8 10 12 14 16 18 20
F = 6 -1 1 3 5 7 9 11 13 15 17
E = 5 -3 -1 1 3 5 7 9 11 13 15
D = 4 -6 -4 -2 0 2 4 6 8 10 12
C = 3 -8 -6 -4 -2 0 2 4 6 8 10
B = 2 -10 -8 -6 -4 -2 0 2 4 6 8
A = 1 -13 -11 -9 -7 -5 -3 -1 1 3 5
1 2 3 4 5 6 7 8 9 10
Haul Road Condition index
PayloadDistributionIndex
Notice that negative values of SPL and SHR can also be used; for example when contract
availability would be plotted instead of MARC rates.
This approach facilitates how the map shown in Table 6 can be generated. There are only two
values needed to generate the whole set of values for a given MSI map.
What it does not provide are both Payload distribution and Haul road sensitivities, which must be
estimated according to each particular mining operation.

6. Machine performance and haul road assessment using
control charts
The most important factor is being familiar with the site’s haul roads. In particular, it is
important to be aware of the site conditions during the data logger run that was used in order to
generate a verbal or written description of the features on the haul road that are generating spikes
on the FPO control charts.
FPO generates a number of control charts for a variety of purposes, which are described in the
FPO User Manual.
It is very difficult to provide suggestions for machine application improvement while the truck is
travelling empty. Impact loads on trucks due to poor road conditions are the result of vehicle
weight and ground speed. Therefore, many of the FPO control charts used in this section
comprise machine loaded.
Many studies have been previously done using control charts to manage engineering processes,
for example [Oakland, 2003].
The following sections analyse FPO control charts and their application to optimise machine
application. It is highly recommended to use this section in conjunction to the FPO User
Manual.
6.1. Speeds on curves and superelevation
Switchbacks can be identified using FPO by looking at Bias and Rack values. The relationship
between Rack and Bias when a lateral force is applied to the truck can be estimated using the
following methodology.
Machine Bias attempts to evaluate force reaction induced by lateral forces. Figure 6 illustrates
typical forces on a truck when a lateral force is applied; for example when the truck is bouncing
side ways or when cornering.
Figure 6 –Forces on an OHT when bouncing transversely (Front view)

The following expressions are then found from Figure 6:
WRR RL =+ …………………….………. (Eq. 8)
LRHFLR LR ×=×+× ………..…………….. (Eq. 9)
Combining equations 8 and 9:
F
L
HW
RR ×−=
22
…………………………. (Eq. 10)
F
L
HW
RL ×+=
22
…………………………. (Eq. 11)
Notice that reactions RL and RR vary in the same proportion when a lateral force “F” is applied.
The second term at the right side of equations 10 and 11 adds and subtracts the same magnitude
when the truck is bouncing or cornering.
Given that Bias is the difference between left and right strut pressures, Bias will be direct
proportionally to the difference RL-RR, therefore:
F
L
H
RR RL ×=−=BiasMachine …………………… (Eq. 12)
Equation 12 shows a linear relationship between any lateral force and Machine Bias values for
small amounts of truck bouncing. Therefore, it would be expected to observe symmetrical
positive and negative values of Bias in the control charts when the truck has no payload
imbalance and bounces sideways or negotiates a corner.
Figure 7 – Rack forces on an OHT under normal payload distribution
If payload imbalance is introduced, the first term at the right side of equations 10 and 11 (i.e.
2
W
), will decrease in one and increase in the other, causing machine Bias to fluctuate
symmetrically about a non zero pressure value.
Machine Rack is also close related to Bias variations, when the truck bounces sideways or during
cornering.
Figure 7 shows a top view (figure on the left) and left side view (figure on the right) of an OHT,
where reaction forces are illustrated. Lets assume that the longitudinal weight distribution is
twice on the rear axle than on the front, then:

( ) ( )RRLL RRRR ×+×−×+×= 2121BiasMachine ………..……….. (Eq.13)
)(3 RL RR −×= …………….…… (Eq. 14)
Similarly,
)21()21( LRRL RRRR ×−×−×+×=RackMachine ……… (Eq. 15)
)(1 RL RR −×−= …………………………… (Eq. 16)
Equations 14 and 16 comprise the common factor )( RL RR − . Notice that Bias and Rack from
these equations always have opposed signs and Bias magnitude will be three times more than
Rack.
Figure 8 – Rack and Bias relationship
Therefore, it would be expected that Rack and Bias traces would have opposed signs when the
truck bounces sideways or turns a corner, assuming that:
• Truck has a weight distribution of one-third at the front and two-thirds at the rear
• There is no longitudinal acceleration
• Slight forces are introduced to unbalance the truck transversely.
Equations 14 and 16 are plotted in figure 8 using the parameter )( RL RR − at the x-axis to show
the lineal relationship of both magnitudes.

Figure 9 illustrates Rack and Bias relationships with an example. Notice the mirror-shape of
both traces, where Bias (blue trace) magnitude is mostly higher than Rack (green trace) at the
peaks.
Figure 9 – Example of Rack and Bias relationship.
Notice the Rack and Bias mirror-shape
The current analysis shows the behaviour of Rack and Bias pressure traces for an OHT when
slightly bouncing or cornering. In order to identify in which case the truck is turning, we need to
use additional data from VIMS regarding rear wheel speed.
Figure 10 – OHT rear wheel speeds when turning
Figure 10 shows the relationship between left and right rear wheel speeds on a truck when
turning about an instantaneous circle.
The two vertical vectors shown in Figure 10 represent the instantaneous displacement of each
individual wheel around the associated center of rotation, where:
R: Turning circle radius around the instantaneous center of rotation

e: Truck tyre tread distance
T: Instantaneous time
WR, WL: Right and Left wheel speeds respectively
From Figure 10:
e-R
WT
R
WT LR ×
=
×
…………………..……. (Eq. 17)
Therefore:
LR
R
W-W
W
e2R2diameterturningInstant. ××=×= …….… (Eq. 18)
Equation 18 provides the instantaneous turning diameter based on truck tyre tread distance and
wheel speed. Notice that the turning diameter will be infinite when the truck follows a straight
line so both left and right wheel speeds are the same.
Minimum turning diameter (2R) and tyre tread distance (e) can be found in the Performance
Handbook. Values for OHT are listed in table 7:
Table 7 – Values of Minimum turning diameter and tyre tread distance for OHT
769D/
771D
773E/
775E
777D 785C 789C 793C 797B
Machine clearance
turning circle (m)
20.3 23.8 28.4 30.5 30.2 32.4 42.1
Front tyre tread (m) 3.10 3.28 4.17 4.85 5.43 5.61 6.51
Using the front tyre tread from Table 7 as ‘e’ in equation 18 and rear wheel speeds as WL and WR
in equation 18, the instant turning diameter can be evaluated for different truck conditions.
Wheel speeds need to be exported from VIMS database. Figure 11 shows the screen on VIMSpc
from which data can be exported. Speed data can then be saved in a spreadsheet to integrate
equation 18.
Figure 12 shows an example of how VIMS data can be manipulated in this manner. Wheel
speed differential is the arithmetic difference between left and right rear wheel speeds. When
this value is plotted in conjunction with Bias and Rack, the following events can be determined:
• Traction loss (Wheel spin): Rack and Bias follows the predicted relationship of
equation 14 and 16 near to zero, but the wheel differential show high values.
• Switchbacks: Rack and Bias show big spikes with opposed signs, and wheel differential
speed also show high values, either positive or negative.

Figure 11 – Exporting wheel and ground speed from VIMSpc
Figure 12 – Calculated data from VIMSpc used to assess traction loss and switchbacks

Figure 13 – Example of traction loss effects on OHT
Figure 13 shows an example of traction loss found by using this methodology. Severity of
traction loss can be evaluated easily by looking at the blue trace and its location on the haul road.
Traction loss has a direct impact in tyre life, and can be corrected when the areas where tyre
slippage occurs are identified and fixed. The truck’s Traction Control module will apply
individual right or left parking brakes to the wheel that is rotating at higher speed when the ratio
between both speeds is higher than 1.6 and the truck travels slower than 19 kph.
Figure 14 – Typical traces of truck bouncing and switchbacks
On the other hand, when wheel speed differential stays close to zero, Bias and Rack follow the
predicted relationship given by equations 14 and 16 within management limits, it is most likely
that the truck is just bouncing within limits, as shown on the left marked area of figure 14.
When there is a significant difference between wheel speeds followed by Bias and Rack peaks, it
is most like that the truck is turning as shown on the right marked area of figure 14, which has

been expanded for analysis in figure 15. A table showing calculated values has been added to
indicate the instantaneous turning circle values, as given by equation 18.
Figure 15 – Instantaneous turning circle diameter estimation on switchbacks
The minimum turning diameter in the example shown in Figure 15 is 79 meters when the truck is
travelling at a ground speed of 20.5 kph. By interpolating Table 1 values, it can be found that for
a curve of 79 meter radius and when the truck is travelling at 20.5 kph, a superelevation of 4.5%
is recommended. This can then be compared with the actual superelevation for that particular
curve.
If the actual superelevation is higher than 4.5% for this example, the superelevation should be
reduced in that particular curve until the Bias and Rack traces approach the management limits.

6.2. Manoeuvring in dump areas
In some application trucks require significant manoeuvring at the dump area because the:
• Dump area is too small for the truck size
• There is a number of support equipment working in the area
• Poor operating skills of the truck operator
The methodology described in the previous section can be used to assess machine application at
the dump area to estimated the minimum turning circle diameter and compare it with values
shown in table 7.
Figure 16 shows an example where Bias and Rack traces show elevated values (spikes) while the
truck is travelling loaded at low speed.
Figure 16 – Example of heavily manoeuvred truck at the dump area
The trace shows the effect of brake application in both Bias and Rack traces. Ground speed
drops from 8 kph to 5 kph creating a peculiar trace signature that is reflected in Bias and Rack.
Using the methodology explained in the previous section, turning circle diameter can be
estimated for this example. Resulting values are shown in table 8

Table 8 – Calculated values of identified curves in figure 16
Curve location – meters from loading equipmentParameter
345m 368m 383m
Time 5:14:01 am 5:14:13 am 5:14:26 am
Direction Left Right Left
Ground Speed (kph) 12 8 5
Turning circle diameter (m) 56 -43 28
Important parameters to assess machine application in the dump area are time between curves,
ground speed and turning circle diameter.
From Table 8, it can be seen that the operator switched from a curve of –43m (right turn) to the
28m turning circle diameters in less than 15 seconds. The severity of the combination of these
hard right to left turn can be assessed by comparing the time taken with steering cycle times from
the SIS, which falls between 7 to 9 seconds.
It can be seen that in the last two curves, the operator needs to turn from right to left in around 13
seconds, which might be consider as a hard turn. It may also indicate a safety hazards and
machine abuse. In addition, it was also observed that the operator applied the brakes while
turning hard at the same time. Both events (hard turn and brakes) contribute to build up RACK
and BIAS spikes seen in this example.
6.3. Gear selection
Gear selection is done automatically at the truck by the electronic transmission control according
to machine speed and other machine operational conditions. The operator can limit the
maximum transmission gear using the shift lever located in the cab, for example to prevent
transmission hunting. Detailed information can be found in the associated service manual.
The selection of the correct gear shift to machine application provides the following advantages:
• Extends transmission life by decreasing then number of transmission shifts
• Optimise truck productivity when severe transmission hunting is observed
FPO provides a control chart showing actual gear and machine speed vs. haul distance, which
can be used to quickly evaluate if machine operation can be improved by limiting gears or
selecting the right gear at the right place in a particular haul road. If a more detailed analysis is
needed, Performance Handbook and FPC software would be needed.
Rimpull curves can be found in the Performance Handbook for each model of the OHT. Figure
17 illustrates Rimpull characteristics for 793C, where ground speeds for each of the six
transmission gears are shown.
There is a ground speed overlap region for each gear change as shown in figure 17, where
transmission hunting could be observed under some particular machine operational conditions.
There are six combinations of total resistance (grade plus rolling resistance) and machine gross
weight that induce transmission hunting in these regions. The combination for an 8% of total
resistance and MGW of 383 ton is shown in Figure 17 (red arrows) as an example. Notice that at
this point the transmission will be changing from 2nd
to 3rd
gear (hunting). This condition may
be eliminated by:
• Decrease rolling resistance
• Modify or smooth ramp grade
• Limit gear selection to 2nd
gear

Table 9 provides the full list of machine operational combinations that will induce transmission
hunting to a 793C.
Table 9 – Transmission hunting conditions (Taken from CAT Performance Handbook)
Hunting
condition
Gross Weight
(kg)
Speed
(kph)
Total Resistance
(Grade + Rolling Resistance in %)
1st
TC and 1st
DD 383 727 8 15
1st
DD and 2nd
383 727 12 11
2nd
and 3rd
383 727 16 8
3rd
and 4th
383 727 21 6
4th
and 5th
383 727 27 4.5
5th
and 6th
383 727 37 3.5
In order to analyse if the impact on machine productivity by limiting gear shifts, FPC should be
used. The haul road details, such as grades and distances, can then be defined using FPC. The
haul road can be segmented in accordance with (Figure 18):
• Distance of the segment (meters)
• Rolling resistance (%)
• Grade (%)
It is highly advisable to use FPC and Rimpull curves to make the decision whether it would be
better to limit the transmission to the lowest gear and therefore elimination transmission hunting.
The overall performance can be assessed in terms of increased cycle time and associated cost per
tonne.

Figure 17 – 793C Rimpull-Speed-Gradeability curves (Performance Handbook, edition 34)
Figure 18 – Haul road simulation using FPC. Speed limit and rolling resistance can be
defined at each haul road segment.

6.4. Crossfall
The purpose of the Crossfall is to drain water from the haul road. However, there are some
applications where the Crossfall angle is too high may induce higher pressure values to one side
of the truck than the other side (Figure 17).
Figure 17 – Effects of Crossfall in pressure readings
Bias and Rack will be affected under this condition, because even that the payload mass is
centred in the truck’s body there will be positive or negative Machine Bias trace consistently
along the haul road under these circumstances.
Figure 18 shows an example from a mine site where the Crossfall is excessive causing a
considerable positive pressure offset on machine Rack and negative pressure offset on machine
Bias.
Figure 18 – Example of high Crossfall angle
Both Machine Bias and Rack have clear negative and positive trends. Notice the number of
spikes out of the Management Limits caused by the induced Crossfall pressure offset. HRC
index for this Haul Road is 10, because the excessive Crossfall.

7. Acknowledgements
This document should be used in conjunction with the Fleet Productivity Optimisation (FPO)
Program and Users Guide, and the document “Assessing the effects of a mine profile on the
performance of Off-Highway Trucks”, by Denis Mills.
Assistance is gratefully acknowledged from Denis Mills, Keith Williams, John Saban, Jason
Price, Geoff Perich and Jim Davey for their work in developing the Management Limits, and
creating useable information from extensive information of VIMS dataloggers, and real-time
TPMS data.
8. References
[1]. Joseph, T.G., “Large Mobile Mining Equipment Operating On Soft Ground”, 18th
International
Mining Congress and Exhibition of Turkey, IMCET (2003), pp 143-147.
[2]. Joseph, T.G.; and Sharif-Abadi, A.D., “Large haul truck strut pressures in soft and firm ground
conditions”, Mining Industry Conference & Exhibition, Montreal (2003).
[3]. Thompson, R. J.; and Visser, A. T., “An integrated Haul Road Design System to Reduce Cost
per Tonne Hauled”, World Mining Equipment Haulage 2002 Conference, Tucson, Az., USA.,
19-22 May (2002).
[4]. Prem, H; and Dickerson, A.W., “A study of steady state roll-response of a large rear-dump
mining truck”, SAE International Off-Highway and Powerplant Congress and Exposition (1992),
Document number 921735.
[5]. Trombley, N., “Vital Information Management System”, Co-Op work term presentation at
Syncrude (2001).
[6]. Wohlgemuth, P., “Structural fatigue Cracking trends”, M.Eng. Thesis, University of Alberta
(1997).
[7]. Giacchi, A., F., “Guidelines to the Design, Construction and Maintenance of Haul Roads”,
Caterpillar of Australia Pty Ltd publication (1990).
[8]. Oakland, J.S., “Statistical Process Control”, Fifth Edition. Butterworth-Heinemann (2003),
ISBN 0 7506 5766 9.
[9]. Caterpillar Inc., “Performance Handbook – Edition 34” Caterpillar Inc., Peoria Illinois, USA.
SEBD0344 (2003).

Appendices
Table 10 - Document Change Chronology
V2 – 14 Oct 99 Expanded to include the introduction of VIMSpc99
V3 – 26 Apr 00 Improved explanation of Management Limits
Expanded Management Limits into smaller OHT models
V4 - 19 Jan 01 Corrected 10/10/20 policy, clarity of Mine Severity Index limit
V5 – 20 Jun 01 Mine Severity Index changed to include alpha characters in Payload Index
Data export procedures changed to delete VIMS 2.4X references and include data
export from pre & post V2.0.3 versions of VIMSpc99
Expanded Management Limits, and export procedures for 797 truck
V6 – 19 Nov 01 Modified to include the introduction of VIMSpc2001 & VIMS Supervisor, and to
clarify 10/10/20 Payload Rule range definitions
V7 - 26 Apr 02 Modified to include exporting from VIMSpc2001
V8 – 16 Oct 02 Modified to correct export parameter detail [need Engine Speed, not Engine
Load] and to include release of VIMSpc2002
V9 – 28 Mar 03 Modified to include revised Haul Road Condition Index Rating criteria
Inclusion of data collected using TPMpc and notes covering use of ASA in
MARC management
Significant Pressure criteria and clarification of Composite Strut Pressure trace
interpretation
V9b – 25 Jun 03 Modified to correct 797 pressure value typo in Haul road Condition Index note
V10 – 23 Oct 03 Modified to include the use of RAC FELA data
V11 – 26 Nov 04 New software version: PFO V1.5
New logic tables to assess Haul Road condition index
References from other authors included
Analysis of MARC rates planar distribution
Analysis of switchbacks, gear selection, wheel spin, and Crossfall using FPO
RAC FELA data extracted to another separate document
For comments, questions or errors, please contact:
Matt McLeod Oscar Villalobos
Regional Equipment Management Consultant Equipment Management Consultant
CAT Global Mining Asia Pacific CAT Global Mining Asia Pacific
mmcleod@cat.com Villalobos_Oscar_E@cat.com

Fpo application guide ver 11 26 11-04

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