Thesis_3_10

i
AACCKKNNOOWWLLEEDDGGEEMMEENNTTSS
I would first like to thank God for making this all possible. I also owe a debt of
gratitude to DDrr.. AAhhmmeedd RRaagghheebb, for his encouragement and help with this project.
Another debt of gratitude is also due to DDrr.. KKhhaalleedd SShhaawwkkii, who was patient,
helping and encouraging throughout the writing. I must also thank DDrr.. WWaaeell KKaammeell
and DDrr.. HHeesshhaamm BBaassssiioouunnyy for their instructions.
Finally, without the love and support of my parents, and the rest of my family, I
could not have survived the first semester of graduate school, much less conducted
this research.

ii
AABBSSTTRRAACCTT
Earthmoving operations are often among the most vital operations in many
construction projects owing to their significant effect on the project cost and
duration. A trade-off between the highest production rate and the lowest cost of
earthmoving operations is most desirable. Therefore, it would be advantageous to
develop a tool to assist the managers of such projects in the decision making
process. A Decision Support Tool (PROEQUIP) utilizing simulation has been
developed in this research to assist in the selection of the appropriate earthmoving
combination of the hauling and excavating units. PROEQUIP can also predict and
help in monitoring the production rate and cost of earthmoving operations. Unlike
most previous methods and techniques which have been devised to simulate either
production rate or cost, PROEQUIP can simultaneously simulate the production rate
and cost of earthmoving operation using any available combination of equipment,
hauled material and road characteristics. PROEQUIP comprises an expandable
database and two calculation modules. The database contains the empty weight,
maximum payload, loaded truck speed, horsepower and heaped capacity for 27
types of trucks. Weight and filling factor characteristics of 23 materials as well as
the rolling resistance of 21 road materials are also stored in the database. The two
modules included into PROEQUIP can retrieve any data needed from this database.
The first of these two is a deterministic performance module which uses
commonplace empirical relationships to calculate the cost and production rate for a
specific combination of road and excavation material, and truck and excavator
specifications. The second module uses the simulation technique to predict the cost
and production rate for a number of possible combinations of truck/excavator
systems. PROEQUIP was validated using data collected from an earthmoving
project in Egypt and another in Saudi Arabia. The actual production rates were
estimated at the lower 7th and 28th percentile of the results simulated by
PROEQUIP, respectively.

iii
TTAABBLLEE OOFF CCOONNTTEENNTTSS
ACKNOWLEDGEMENTS............................................................................. i
ABSTRACT………………………………………………………………….ii
LIST OF FIGURES ........................................................................................ v
LIST OF TABLES .........................................................................................ix
LIST OF SYMBOLS......................................................................................xi
CHAPTER 1: GENERAL INTRODUCTION............................................. 1
1.1 INTRODUCTION........................................................................................2
1.2 RESEARCH AIM AND OBJECTIVES ......................................................3
1.3 ORGANIZATION OF THE RESEARCH...................................................4
1.4RESEARCHSCOPE AND LIMITATIONS .................................................5
1.5LAYOUT ANDMETHODOLOGY OF PROEQUIP ...................................6
CHAPTER 2: REVIEW OF LITERATURE............................................... 8
2.1 INTRODUCTION........................................................................................9
2.2 GENERAL REVIEW...................................................................................9
2.3COMPUTERS IN EARTHMOVING .........................................................12
CHAPTER 3: EARTHMOVING OPERATIONS..................................... 21
3.1 INTRODUCTION......................................................................................22
3.2 MANAGING EARTHMOVING OPERATIONS .....................................22
3.2.1 Safety...................................................................................................23
3.3HYDRAULIC EXCAVATORS..................................................................26
3.4 TRUCKS AND HAULING OPERATIONS .............................................30
CHAPTER 4: ESTIMATING TECHNIQUES.......................................... 34
4.1 INTRODUCTION......................................................................................35
4.2 PRODUCTIVITY ESTIMATING .............................................................36
4.3 COST ESTIMATING ................................................................................50
4.3.1 Fixed Costs ..........................................................................................52
4.3.2 Operating Costs ...................................................................................54
4.3.3 Labor Costs..........................................................................................58
4.4 SELECTING THE OPTIMUM EQUATION TO CALCULATE
TRUCK SPEED ........................................................................................58

iv
CHAPTER 5: DECISION SUPPORT TOOL FOR EARTHMOVING
PROJECTS......................................................................... 61
5.1 INTRODUCTION......................................................................................62
5.2 INPUTS, OUTPUTS AND DATABASE..................................................63
5.3 SYSTEM STRUCTURE............................................................................69
5.3.1 System Calculation..............................................................................69
5.3.2 The Simulation ....................................................................................74
5.4 USER INTERFACE...................................................................................79
5.5 THE RESULTS..........................................................................................85
5.6 EXAMPLES FOR TRADITIONAL CALCULATION USING
PROEQUIP (PROEQUIP VERIFICATION) ...........................................92
5.6.1 Example 1............................................................................................92
5.6.2 Example 2............................................................................................99
5.7 THE SIMULATION RESULTS ACCURACY:......................................104
5.8 APPLICATION OF PROEQUIP ON REAL CASES: ............................105
CHAPTER 6: CONCLUSION AND RECOMMENDATIONS............. 125
6.1 SUMMARY AND CONCLUSION.........................................................126
6.2 RECOMMENDATIONS FOR FUTURE RESEARCHE........................128
REFERENCES............................................................................................ 130
APPENDICES.. ........................................................................................... 135
Appendix A.....................................................................................................136
Appendix B.....................................................................................................146
Appendix C.....................................................................................................149
Appendix D.....................................................................................................151
Appendix E.....................................................................................................154
Appendix F .....................................................................................................156

v
LLIISSTT OOFF FFIIGGUURREESS
List of Figures Page
Figure 1.1 PROEQUIP results summary ……………………………… 7
Figure 2.1 A Graphical Model for Maximizing Production of a Pushed
Scraper ……………………………………………………... 10
Figure 3.1 Hydraulic hoe loading a truck ……………………………... 28
Figure 3.2 Wheel-mounted hydraulic hoe …………………………….. 28
Figure 3.3 Basic parts of a hydraulic hoe ……………………………... 28
Figure 3.4 Hydraulic hoe bucket capacity rating dimensions ………… 28
Figure 3.5 Maximize production of the earthmoving system ………… 29
Figure 3.6 Truck tractor unit towing ………………………………….. 31
Figure 3.7 Off-highway truck …………………………………………. 31
Figure 3.8 Highway rigid-frame rear-dump truck …………………….. 32
Figure 3.9 An articulated dump truck …………………………………. 32
Figure 3.10 An articulated dump truck moving through soft ground ….. 32
Figure 3.11 Off-highway tractor towing a loaded bottom-dump trailer .. 32
Figure 3.12 Highway bottom-dump ……………………………………. 32
Figure 3.13 Measurement of volumetric capacity …………………….... 33
Figure 4.1 Material-Volume Changes Caused by Construction
Processes …………………………………………………... 36
Figure 4.2 Performance chart for Caterpillar 793C Truck ……………. 47
Figure 4.3 Basic truck load cycle ……………………………………… 48
Figure 4.4 Equipment Cost Model …………………………………….. 51
Figure 5.1 Soil properties database figure …………………………… 65
Figure 5.2 Road condition database figure ………………………….. 66
Figure 5.3 Trucks form to add, edit and delete truck …………………. 67
Figure 5.4 Trucks form to search for existing truck …………………... 67
Figure 5.5 User interface parameters flowchart ………………………. 68
Figure 5.6 Production calculation flowchart for earthmoving system .. 70

vi
LLIISSTT OOFF FFIIGGUURREESS ((CCoonntt’’dd))
Figure 5.7 Unit cost calculation flowchart for earthmoving system …...... 71
Figure 5.8 Simulation model network diagram for the activities ……….. 77
Figure 5.9 Normal probability distribution for the random variables ….. 77
Figure 5.10 Beta probability distribution for the random variables ……… 77
Figure 5.11 The simulation model pseudocode …………………………... 78
Figure 5.12 User interface – Project information ………………………… 79
Figure 5.13 User interface – Job information ……………………………... 80
Figure 5.15 User interface – Haul road information ……………………… 81
Figure 5.15 User interface – Equipment selection section ……………….. 82
Figure 5.16 User interface – Equipment Unit Cost section ………………. 83
Figure 5.17 User interface – Equipment Cost section ……………………. 83
Figure 5.18 User interface – Simulation section ………………………….. 84
Figure 5.19 The production and cost results page ………………………… 85
Figure 5.20 The results data sheet page …………………………………... 86
Figure 5.21 The simulation calculations interface – trials section A …….. 88
Figure 5.22 The simulation calculations interface – trials section B …….. 88
Figure 5.23 The simulation calculations interface – trials section C …….. 88
Figure 5.24 The simulation results – unit cost ……………………………. 89
Figure 5.25 The simulation results – Production …………………………. 89
Figure 5.26 The overlay charts for productivity and cost ……………….... 90
Figure 5.27 The recommendations (advices) page ……………………….. 91
Figure 5.28 Safety video sample in the recommendations ……………….. 91
Figure 5.29 Caterpillar 725 Articulated Truck specifications ……………. 93
Figure 5.30 The results of example 1 in the Results page ………………… 98
Figure 5.31 Caterpillar 725 Articulated Truck specifications ……………. 99

vii
Figure 5.32 The results of example 2 in the Results page ………………… 103
Figure 5.33 GAZADCO project (site plan) ……………………………….. 106
Figure 5.34 GAZADCO project (shrimp pond works) …………………… 107
Figure 5.35 GAZADCO project (Earthmoving works) …………………… 107
Figure 5.36 GAZADCO project (Excavation works A) …………………... 108
Figure 5.37 GAZADCO project (excavation works B) …………………… 108
Figure 5.38 GAZADCO project (excavation works C) …………………… 109
Figure 5.39 GAZADCO project - Mercedes Benz 3328K (1987) ………... 111
Figure 5.40 GAZADCO project - Mercedes Benz 2638 (1993) ………….. 111
Figure 5.42 GAZADCO project - Volvo – FM12.420 (2004) ……………. 111
Figure 5.43 GAZADCO project - Mercedes Benz 2628(1983) ………….. 111
Figure 5.44 GAZADCO project - Hyundai R140 LC – 7 ………………… 111
Figure 5.45 GAZADCO project - Caterpillar 325 DL ……………………. 112
Figure 5.48 GAZADCO project - Kumatsu PC240 LC …………………... 112
Figure 5.49 GAZADCO project - Caterpillar 225 ………………………... 112
Figure 5.50 The productivity distribution for the first case ………………. 113
Figure 5.51 The simulation overlay charts for all study cases ……………. 114
Figure 5.52 The suggesting optimum cases to be selected …………….…. 115
Figure 5.53 NILE COMPANY project (site works) ……………………… 118
Figure 5.54 NILE COMPANY project - Mercedes Benz 3331 …………... 119
Figure 5.55 NILE COMPANY project - Scania 113H …………………… 119
Figure 5.56 Kumatsu PW160 ……………………………………………... 119

viii
Figure 5.57 Kumatsu PC210 LC …………………………………………. 119
Figure 5.58 The productivity distribution for the first case ……………. 120
Figure 5.59 The simulation overlay charts for all study cases …………… 121
Figure 5.60 The suggesting optimum cases to be selected ….……….…. 122
Figure 5.61 The simulation overlay - probability - charts for all study
cases …………………………………………………………. 124
Figure 6.1 The organization of the research ……………………………. 126

ix
LLIISSTT OOFF TTAABBLLEESS
List of Tables Page
Table 2.1 PROEQUIP and previous published models for earthmoving 18
Table 4.1 Material Volume Conversion Factors ………………………... 37
Table 4.2 Loading excavator cycle times for a 90o
swing (seconds) …... 39
Table 4.3 Excavator swing factors ……………………………………… 41
Table 4.4 Weight of Materials according to German Norm DIN/VOB ... 41
Table 4.5 Typical rolling resistance factors …………………………….. 44
Table 4.6 Operator Skill Factor, FO........................................................... 45
Table 4.7 Job Efficiency Factor, Fe……………………………………... 45
Table 4.8 Excavator operating efficiency ……………………………… 45
Table 4.9 Selecting ownership period based on operating conditions… 53
Table 4.10 Maintenance and repair rates as a percentage of the hourly
depreciation for selected equipment ………………………… 55
Table 4.11 Weights, fuel consumption rates, and load factors for diesel
and gasoline engines …………………………………………. 56
Table 4.12 Guidelines for tire life for off-highway equipment ………….. 57
Table 4.13 Summary of example 1 …...………………………………… 59
Table 4.14 Summary of example 2 …….……………………………….. 60
Table 5.1 Parameters for the Random Variables Used in the Models … 76
Table 5.2 User Interface – Window 1 description …………………….. 79
Table 5.3 User Interface – Window 2 description ……………………. 80
Table 5.4 User Interface – Window 3 description ……………………. 81
Table 5.5 User Interface – Window 4 description ……………………... 82
Table 5.6 User Interface – Windows5 and 6description ……………... 84
Table 5.7 User Interface – Window 7 description …………………….. 84
Table 5.8 The results of example 1 using PROEQUIP software ……… 98
Table 5.9 The results of example 2 using PROEQUIP software ……… 103
Table 5.10 The production results according to number of trials change 104

x
LLIISSTT OOFF TTAABBLLEESS ((CCoonntt’’dd))
List of Tables Page
Table 5.11 GAZADCO Project data and description ………..………….. 105
Table 5.12 GAZADCO Project Company Equipment (Trucks) ………... 109
Table 5.13 GAZADCO Project Company Equipment (Excavators) ……. 110
Table 5.14 GAZADCO Project Equipment available for renting
(Trucks) ……………………………………………………... 110
Table 5.15 GAZADCO Project Equipment available for renting
(Excavators) …………………………………………………. 110
Table 5.16 Kabary-Matrooh Project data and description ……………… 117
Table 5.17 Kabary-Matrooh Project Company Equipment (Trucks) ....... 118
Table 5.18 Kabary-Matrooh Project Equipment for renting (Excavators) 119

xi
LLIISSTT OOFF SSYYMMBBOOLLSS
SYMBOLS NOMENCLATURES UNIT
 Average material density ton/m3
A Equipment Availability factor
AS:D Angle of swing and depth (height) of cut
correction
B Bucket capacity m3
Bc Nominal bucket capacity m3
BCM Bank Cubic Meter m3
Bf Bucket fill factor
C Theoretical cycles/hr for a 90o
swing cycles/hr
c2, c3 Rolling resistance constant
Cbe Bucket heaped capacity m3
CCM Compacted Cubic Meter m3
CECE The Committee on European Construction
Equipment
Cht Truck heaped capacity m3
CIPROS knowledge based construction planning
simulation system
cr Rolling coefficient
CYCLONE Cyclic Operations Network
Di Distance from haul to dump site km
D Equipment depreciation per hour LE/hr
Dd Number of working days per week day
Dh Number of working hours per day hour
DISCO Graphical simulation modeling for bridge
construction
E Equipment efficiency

xii
LLIISSTT OOFF SSYYMMBBOOLLSS ((CCoonntt’’dd))
e Engine efficiency
ESEMPS Expert system using for road equipment
F Fuel cost per hour LE/hr
ff Bucket fill factor
Fl Fuel cost per liter LE
Ft Tractive force N
GHP The gross engine horsepower at governed engine
rpm
hp
GMW Gross machine weight kg
GR Road Grade resistance N
GPSS General Purpose Simulation System
h Helper cost per hour LE/hr
hp Equipment engine horse power hp
hpt Truck engine net power hp
HSM The Hierarchical Simulation Model
I Interest cost per hour LE/hr
i Interest rate %
IS Insurance cost per hour LE/hr
is Insurance rate %
K The weight of fuel used per brake hp/hour kg/br.hp-hr
KPL The weight of fuel kg/liter
L Labor cost per hour LE/hr
LCM Loose Cubic Meter m3
LF The load factor
LMPH The liters used per machine hour liter

xiii
Lt Rated truck load ton
M Maintenance and repair cost per hour LE/hr
m Vehicle mass kg
MicroCYCLONE Cyclic Operations Network using
microcomputers
Mta Mass on tractive Rear axle kg
Nb Number of excavator buckets bucket
Nh Number of helpers Helper
Nt Number of trucks truck
O Job operational factor
OA Equipment Operating Efficiency
Pe Energy power kW
P Production m3
/hr
PCSA Power Crane and Shovel Association
Pt Truck payload kg
PTF Propel time factor kg
Q heaped bucket capacity m3
Qs Excavator productivity m3
/hr
Qt Truck productivity m3
/hr
Rr Road Rolling resistance N
Rt Road Total resistance N
S Salvage value LE
s Slope of haul road %
Sf Swing factor
SAE Society of Automotive Engineers
SIMPHONY Special purpose construction simulation model

xiv
SPS Special Purpose Simulation
STROBOSCOPE State and Resource-Based Simulation of
Construction Processes
te Excavator cycle time Sec
T Taxes cost per hour LE/hour
t Taxes rate %
tc Excavator cycle time for a 90o
swing min.
TC Total unit cost per hour LE/hour
Tcc Tire change (replacement) cost LE
tce Excavator cycle time sec.
Tct Total truck cycle time min.
tct Truck cycle time min.
td Dump time min.
th Haul time min.
Tic Tire cost per hour LE/hour
tL Load time min.
tr Approximate tire life hours
tr Return time min.
TR Total resistance N
U Lubricant cost per hour LE/hour
UM-CYCLONE Cyclic Operations Network under DOS system
V Truck speed km/hr
VC volume correction for loose volume to bank
volume
VH Velocity of haul direction km/hr
Vhe Truck speed empty km/hr
Vhl Truck speed loaded km/hr

xv
Vl Load volume m3
Wet Truck empty weight kg
Wf Weight fully loaded ton
Wgt Gross weight of the truck kg
Wl Load weight kg
Ws Weight of soil kg/ m3
η Transmission efficiency
μ Coefficient of friction

CCHHAAPPTTEERR OONNEE
GGEENNEERRAALL IINNTTRROODDUUCCTTIIOONN

2
CCHHAAPPTTEERR 11
GGEENNEERRAALL IINNTTRROODDUUCCTTIIOONN
11..11 IINNTTRROODDUUCCTTIIOONN
Construction is an important industry in terms of the annual capital invested in
construction work and its high employment. The importance of the industry can also
be measured by its contribution to the gross national product. However, the
construction industry is in a difficult position due to the decline in construction
productivity which started in the mid 1970's [1]. The current stringent financial
situation aggravates these difficulties.
Facing these challenging problems, the construction industry became aware of the
importance of productivity improvement and cost reduction, and is striving for such
improvements. Historically, productivity improvement was often focused on labor
effort; this also applied to the construction industry. But there is a second important
term in production improvement especially in construction industry which is the
earthmoving equipment [1].
Earthmoving may include site preparation, excavation, embankment construction,
backfilling, dredging, preparing base course, subbase, subgrade, compaction, and
road surfacing. The types of equipment used and the environmental conditions will
affect the man- machine-hours required to complete a given amount of work. Before
preparing estimates, there is a need to select the best method of operation and the
type of equipment to use. Each piece of equipment is specifically designed to
perform certain mechanical tasks. Therefore, the equipment selection should be
based on efficient operation and availability. Earthmoving is characterized by the
intensive utilization of machines. It is therefore often one of the most important
operations in many construction projects in terms of its cost and productivity.

3
Hence, earthmoving planning is a potential area for further productivity
improvement.
To improve earthmoving planning, a variety of methods and techniques has been
tried. The rapid development of computer technology provides a useful means to
assist in construction management and planning. Proper equipment selection is
crucial to achieve efficient earthmoving and construction operations. The machine‘s
operational capabilities and equipment availability should be considered when
selecting this machine for a particular task. The manager should visualize how best
to employ the available equipment based on soil considerations, zone of operation,
and project-specific requirements. Cost and productivity estimates, productivity
control, and production records are the basis for management decisions. Therefore,
it is helpful to have a common method of recording, directing, and reporting
production.
11..22 RREESSEEAARRCCHH AAIIMM AANNDD OOBBJJEECCTTIIVVEESS
This research addresses the development of a decision supporting tool which could
be used for the selection of appropriate earthmoving equipment and for the
estimation of their productivity and cost. Furthermore, provide some important
safety recommendations for using earthmoving operations are later provided.
The overall aim of this research is to develop a simulation model in the form of
computer application to assist managers to manage and estimate the productivity,
duration and cost of earthmoving system.
In order to attain the above aim, four specific objectives will have to be achieved:
1) Collection of data needed to compile required databases of:
 Equipment database: provide truck empty weight, truck payload, truck
horsepower, top loaded speed of the truck and truck heaped capacity
 Excavated material database: provide material weight, bucket fill
factor and excavator cycle time based on material type.

4
 Rolling resistance database based on haul road type.
2) Design a mathematical model to perform the calculations necessary to
estimate productivity rate, cost and duration for a given earthmoving system
to be used for monitoring, control and improvement of ongoing operations.
3) Obtain performance data for as many earthmoving systems as possible to be
used in the simulation.
4) Design a simulation model integrated with a mathematical model to enable
the comparison among presented earthmoving systems.
11..33 OORRGGAANNIIZZAATTIIOONN OOFF TTHHEE RREESSEEAARRCCHH
The remainder of this research is organized as follows:
Chapter 2 covers a literature survey. The goal of this chapter is to present a
comprehensive review of the previous efforts on improving earthmoving project
performance, especially earthmoving equipment planning and selection using a
mathematical model or simulation.
Chapter 3 presents general information about two major earthmoving equipments:
trucks and excavators. This information can help in the selection of appropriate
equipment for particular earthmoving operations under certain working conditions.
Earthmoving equipment productivity and cost are the major parameters in the
selection of appropriate machines for earthmoving operations.
Chapter 4 discusses the productivity and cost estimating of earthmoving equipment
and factors influencing productivity.
Chapter 5addressesthe decision support tool (PROEQUIP) and explains the
component of this application and its database. The application user interface data
and the source of those data are presented.
Finally, Conclusions and Recommendations for further research development are
presented in Chapter 6.

5
Appendices include a list of selected visual basic programming codes, excavator
cycle time estimating method, unit cost calculation form and Excel formulas which
have been used in the simulation model.
11..44 RREESSEEAARRCCHHSSCCOOPPEE AANNDD LLIIMMIITTAATTIIOONNSS
Earthmoving equipment planning and management deals with a wide range of
issues, including equipment financing, standardization, maintenance scheduling,
replacement schemes, safety and routine operational planning. The focus of this
research is on:
1. The operational planning, particularly on the development of a computer
decision support tool which could be used for the selection of appropriate
earthmoving equipment to complete a given job
2. The estimation of the cost and duration of the job
In earthmoving operations, earthworks may include loosening, excavating, loading,
hauling, unloading, placing, spreading, grading, and compacting. For simplicity of
the tool, this research deals only with four phases: excavating, loading, hauling and
unloading.
The main outcome of this research is an interactive advisory decision support tool
for equipment selection which facilitates the comparison among the performances
of different earthmoving systems working under specified jobsite conditions
according to the following points:
1) The parameters that may affect equipment performance are described in
Chapter 3. However, the measurement of these parameters in the field was
not conducted.
2) It is assumed that the operator will always operate the truck at a constant
speed regardless of any acceleration and deceleration. In reality, however,
the operator will not operate the machine at maximum performance

6
throughout the haul segment and it might be possible that the operator never
operates the machine at maximum performance in a certain segment.
3) Earthmoving system production and unit cost is calculated using the
estimation technique described in detail in Chapter 4.
4) Not all equipment categories will be modeled (equipment categories describe
their general function, or type) and not all classes within each category will
be modeled (classes describe the weight, horsepower, or size of equipment
within its category);the categories and classes that will be analyzed are
machines that are fairly common throughout the industry. The study will be
limited to Caterpillar Articulated trucks, Caterpillar excavators and
equipment that will be described in the "Cases of Study" section in chapter 5.
5) Travel time will be calculated using the equation based on equipment
performance charts contained in the Caterpillar Performance Handbook [1]
that will be validated by two examples in chapter 4.
6) This work is also limited in that it will analyze historical data from a
relatively small number of companies. This does not necessarily mean that
the simulation result represent every firm type, size, geographic region, or
management style. Every construction company is unique. The study is
limited to the medium size construction industry projects that will be
described in the "Cases of Study" section in chapter 5. Mining and huge
projects were not being investigated.
7) The tool that will be developed in this research can be used by the contractor,
planners, project managers and construction engineers. The study
assumptions will be presented in "The Simulation" section in the chapter 5.
11..55 LLAAYYOOUUTT AANNDDMMEETTHHOODDOOLLOOGGYY OOFF PPRROOEEQQUUIIPP
A computer application (PROEQUIP) was developed using Microsoft Visual
Basic.Net and consists of three interfaces:

7
1. User Interface: is the one which the user will use to input the required
parameters.
2. Calculations and results interface: deals with calculations involved in
estimating production and the final results of production, duration and cost
and simulation results. The simulation part of this interface will be developed
using CRYSTAL BALL as an Excel add-in integrated within PROEQUIP,
Figure 1.1.
3. Recommendations Interface: is the location of some important safety
recommendations to assist applying safety while using earthmoving system.
Figure 1.1 PROEQUIP results summary
SIMULATION MODEL
•what is the best system to work in this area?
•What is the economical equipment
combination to finish the required job?
•Which site part will be finished first?
•What is the best system to finish the job
faster?
PERFORMANCE ASSESSMENT
AND OPTIMIZATION RESULTS
•Does the existing equipment combination
work fine?
•How to manage this job to gain the maximum
productivity?
•What are number of trucks and buckets
required to minimize the system cost?
•What are number of trucks and buckets
required to provide maximum productivity?
•When does this equipment combination finish
the required job?
•Does this equipment combination can
progress the work on time?
•Does this equipment combination work as
required or the work is behind the schedule?
Database

CCHHAAPPTTEERR TTWWOO
RREEVVIIEEWW OOFF LLIITTEERRAATTUURREE

9
CCHHAAPPTTEERR 22
RREEVVIIEEWW OOFF LLIITTEERRAATTUURREE
The literature review in this chapter contains two parts. The first part is an overview
of the research development in the area of earthmoving and the methods and
techniques used in previous work. The second part presents several models closely
associated with earthmoving equipment and deals with computer-aided programs
used in earthmoving projects.
22..22 GGEENNEERRAALL RREEVVIIEEWW
As the earthmoving planning process is a comprehensive one driven by many
factors, the identification of these factors is particularly important. Studies have
been conducted on these factors and their treatment. To find the solutions to specific
problems in earthmoving, many methods and techniques have been tried.
The Caterpillar Tractor Company developed a graphical model in 1968 (see Figure
2.1) for solving the machine matching problem by analyzing machine output. In
developing this model, it was found that the load of a scraper increases rapidly, but
the loading rate decreases as the scraper capacity is approached as shown by line
BDO in Figure 2.1 [1].
In Figure 2.1, the vertical axis indicates the amount of material loaded, and the
horizontal axis represents certain parts of the cycle time. Line BDO is a typical
load-growth curve for a bottom-loading scraper pushed by a track type tractor. Line
AO (2.7 minutes) is the cycle time les the loading time for this particular scraper
and soil, line CO (0.3 minutes) is the cycle time less the loading time of the pusher.
The slopes of lines connected from points A and C to the load-growth curve BDO
indicate the output per unit time of the scraper and loader respectively, and the two

10
lines would have their steepest slopes (maximum output per unit time) if they were
drawn tangential to the load-growth curve. In each case, the optimum loads are
determined to be about 31 and 23 cubic meters with pushing time being 0.8 and
0.35 minutes respectively. If the pusher works with two or more scrapers, this
model can determine the most optimum production of the fleet when the costs of the
pusher and scrapers are considered [1].
Figure 2.1 A Graphical Model for Maximizing Production of a Pushed
Scraper
In 1968, Griffis issued a paper on Queuing Theory and optimizing haul fleet size.
The main components of Queuing system are interiors (customers) and service
suppliers. When a customer refers to a system for receiving service, two different
cases may happen. If one of the service suppliers is free, then giving the service to
the customer begins immediately. On the other hand if all service suppliers are
busy, then the customers should wait and thus the queue will be made. In the truck
filling and refilling problem, the trucks are assumed as the customers of Queuing
system. Loaders are known as service providers in this system. One loader along
with specified number of trucks is known as a Queuing system. The objective of
solving this problem is to determine the number of loaders and trucks in a manner to

11
increase the probability of truck existence for one loader as much as possible. In
other words, by allocating appropriate number of trucks the loader will be always
busy [2].
In earthmoving operations, it is common for different types of machines to work
together to complete a job task. For instance, a Loader-truck fleet is often used to
move earth. Gates and Scarpa pointed out that a trade-off should be made between a
lesser number of large and expensive hauling units and a greater number of small
and relatively inexpensive hauling units [3]. Later, Gates and Scarpa carried out
research into the factors that affect the selection of earthmoving equipment and
summarized these factors into four categories [4]:
1) Spatial Relationships: In this category, the major factors were identified to be
the elevation of the working platform, the face and level of excavation,
obstructions in excavation and the configuration of excavation.
2) Soi1 Characteristics: This category covers the soil's ability to support
excavators and hauling units and other soi1 characteristics such as traction,
rolling resistance and gradeability.
3) Contract Provisions: The factors in this category include the quantities of
excavation, moving, and fill; the allowable time of construction; provisions
for payment cash flow.
4) Logistical Considerations: The factors included in this category involve the
availability of equipment and operators with applicable experience; the time
and cost to mobilize and demobilize crews; the use of equipment in
preceding and in subsequent operations (resource leveling); rental costs,
ownership costs, operating costs and production rates.
In 1989, Karshenas developed a model by applying probability theory to determine
the capacity and number of trucks matching the given loaders in a fleet. The
solutions of the model were given in several graphical formats. According to the
loader capacities, the capacity-number combinations of trucks, which possess a
minimum cost of production, can be quickly determined [5].

12
Heavy vehicles have high influence on pavement structure at the roads. Karami has
and Gillespie in 1993 paid attention on pavement damage from trucks and how to
predict dynamic loads along the roadways also the validity of the models is
presented. The authors focused on characteristics of trucks and pavement, and also
their interaction [6] [7].
In 1995, York and Maze briefly described applications of trucks size and weights
standards in the US. This research contains evaluation of truck size and weight
regulation in the United States and classification of performance criteria [8].
And in 2001 Nagatani has studied into the problem of modeling bunching
transitions in general traffic flow and bus routes. Bunching models capture the
tendency of moving objects to bunch together when moving in a line. This is
usually due to some of the objects being operated or moving more efficiently than
others. It can also be due to small unpredictable delays. Bunching is known to
reduce a fleet‘s ability to meet its maximum capacity [9].
22..33 CCOOMMPPUUTTEERRSS IINN EEAARRTTHHMMOOVVIINNGG
Several attempts have been made to develop computer-aided tools to assist in
equipment selection. For example, applications of simulation techniques to
earthmoving operations were made in the 1960s [10]. In 1972, Willenbrock
developed a model using a computer simulation language, GPSS (General Purpose
Simulation System), to estimate cost for earthworks. The GPSS is a programming
system designed for the simulation of discrete systems. These are systems that can
be modeled as a series of state changes that occur instantaneously, usually over a
period of time. Complexities in their analysis arise because there are many elements
in the system, and there is competition for limited system resources. The simulation
technique uses numerical computation methods to follow the system elements
through their changes of state, and predicts properties of the system from
measurements on the model. GPSS came into existence rapidly, with virtually no
planning, and surprisingly little effort. It came rapidly because it filled an urgent

13
need that left little time for exploring alternatives. The lack of planning came from a
happy coincidence of a solution meeting its problem at the right time. The economy
of effort was based on a background of experience in the type of application for
which the language was designed, both on the part of the designer and the early
users [10].
Simulation has been used extensively in many areas of Construction Engineering
starting with the introduction of CYCLONE by Halpin in 1977. This methodology
has been the basis for a number of construction simulation systems. Most of these
systems are general in nature forcing users to build models using abstract elements
such as activities, queues and resources. This allows for the modeling of scenarios
of unlimited complexity and in any field. Further, if the basic building elements are
not sufficient to a model a given situation, most systems also allow for the
integration of programming code in the form of user inserts or add-ons. Although
these systems prove extremely flexible and powerful from an academic stand point,
those who can benefit from its power the most, the industry practitioners, have not
embraced it. The generality and complexity of general purpose simulation systems
meant that industry members were forced to learn the equivalent of a new language
or hire an expensive simulation consultant to perform the required analysis. In the
construction industry, simulation can be most beneficial during the estimating stage
where limited time is available and costs incurred are typically not easily recovered
since only a small amount of estimates lead to a successful contract award.
Construction practitioners require a simulation tool that is easy to use and tailored to
their specific requirements with results that can be directly used as part of other
decision support systems such as computer estimating programs [11].
A linear programming model was presented by Mayer and Stark in 1981. In this
model the earthmoving costs were split into three components: costs for excavation,
costs for hauling, and costs for fill. These costs were linearly proportional to the
quantity of material to be handled. The cost of purchasing mil at the borrow pits
was also considered [12].

14
In 1982, Luch and Halpin presented a Simulation model called MicroCYCLONE.
MicroCYCLONE is a microcomputer based simulation program designed
especially for modeling and analyzing site level processes which are cyclic in
nature. In broader terms, it can be used to model construction operations which
involve the interaction of tasks with their related duration, and the resource unit
flow routes through the work tasks are the basic rationale for the modeling of
construction operations [13].
In the two models discussed above, cost rates were assumed constant. By
considering the variation in the unit cost of earthworks, an extension to the models
was proposed by Easa [14] in 1987. It was found that the major variation in the unit
cost of earthworks was the variation in the unit cost for purchasing and/or
excavating the soil at the borrow pits. Therefore, a stepwise unit cost function of
purchase and excavation for the borrow pits was modeled. Other cost components
were still assumed to be constant. A further modification was made to the stepwise
unit cost function by Easa [15] in 1988.
In 1988, Alkass and Harris designed a system to aid in equipment selection for road
construction. This system, ESEMPS, is an expert system [16].Expert systems
function by asking the user a series of yes/no questions. As these questions are
answered, a set of programmed rules allow the system to guide the user to the
―correct answer‖. This system is linked to a set of external databases which contain
information on machines, earth types, etc. The system also calculates projected
costs.
In 1989,Ioannou designed a Simulation UM-CYCLONE model. UM CYCLONE is
a discrete-event simulation system for construction operations based on activity
scanning and activity cycle diagrams and runs under DOS [17].
In 1992, Amirkhanian and Baker developed an expert system specifically geared
toward equipment selection. Their system, based in VP Expert, asks a series of
questions about project conditions and then recommends the type and number of

15
pieces of equipment needed. Equipment choices include dozers, scrapers,
excavators and trucks [18].
Hanna in 1994 created a similar system for crane selection. In this system, the most
appropriate type and size of crane or derrick is selected based on project parameters
such as heaviest lift, maneuverability, and job conditions. The program produces
output which lists the best type of crane, as well as setup parameters such as number
of lifts for a tower crane. The main focus of the system is to eliminate or reduce the
need for expensive consultations with crane experts. Results of the program were
positive, though limited by the available database [19].
In 1994, AbouRizk and Shi developed an optimization model that considers only
the quantities of resources being used along with their respective user-specified
boundaries. The system recommends a resource combination, within the specified
boundaries, closer to the optimum resource allocation [20].
In 1994, Huang et al. developed a DISCO Simulation model. The DISCO system
provides a graphical environment in which modeling and simulation of construction
operations can be conducted in an interactive fashion. The model developed for the
bridge construction and the results of the simulation are presented [21]. In the same
year Tommelein et al. designed a CIPROS which is a knowledge-based construction
planning simulation system that enables its users to formalize and test alternative
construction plans by relating project-specific design drawings and specifications to
a network of construction processes, elementary simulation process networks, and
associated resources [22].
In 1996, Christian and Xie developed an expert system built upon a rating system
for various types of equipment. A survey was sent out to experts in the field seeking
input on what type of machine was best for a variety of projects and soil types. This
information was compiled into a table that rated each type of equipment from 0 to
10 (10being best) for each set of project parameters. The expert system asks a set of
questions, and then uses the rating system to select the appropriate type and number
of equipment[23].

16
A STROBOSCOPE was proposed by Martinez in 1996. STROBOSCOPE is a
simulation system designed as the successor to UM-CYCLONE based on activity
scanning and activity cycle diagrams. The name STROBOSCOPE, an acronym for
state and resource-Based Simulation of construction processes, reflects the system's
major design objective: the ability to make complex dynamic decisions (and thus
control the simulation at run-time) based on the simulation system state and the
characteristics, attributes, and state of resources. Unlike other simulation systems,
STROBOSCOPE is based on three-phase activity scanning and not process
interaction. The activity scanning simulation paradigm makes STROBOSCOPE
better suited for modeling complex resource interactions such as those that
characterize cyclic operations where no distinction is made between resources that
serve (servers or scarce resources) and those served (customers or moving entities).
STROBOSCOPE simulation models use an easy-to-learn graphical network-based
representation similar to activity cycle diagrams [24]. In the same year Sawhney
and AbouRisk presented a HSM simulation system. HSM enhances and combines
the concepts of work breakdown structure and process modeling to arrive at an
advanced framework for planning [25].
Special purpose simulation (SPS) was proposed by AbouRizk and Hajjar in 1997 to
address the stated issues. The idea is to develop user friendly simulation tools native
to the application domain itself. This typically involves the development of custom
user interfaces, simulation engines, support libraries and integration modules. By
specializing, the full-fledged flexibility of a general purpose simulation tool is lost.
However, the resultant benefits far outweigh the limitations. SPS tools allow
industry practitioners to use simulation systems without prior knowledge of
simulation theory [26]. And after one year MaCabe introduced belief networks as a
diagnostic tool in order to obtain a near optimum solution, accounting for both the
quantity and capacity of each utilized resource [27].
In 1999, SIMPHONY simulation system was proposed by AbouRizk and Hajjar
which provides various services that enable the developer to easily control different
behaviors in the developed tool such as simulation behaviors, graphical

17
representation, statistics, and animation. These services allow building flexible and
user friendly tools in a relatively short time [28].
In 2000, Naoum and Haidar have developed a genetic algorithm model for the
equipment selection problem. Although their model satisfies the requirements for an
integer programming solution, the authors pursued a genetic algorithm solution. The
solution incorporates the lifetime discounted cost of the equipment, which is
formally attached to the assumption that the equipment is used from purchase until
official retirement age, and not sold or replaced before that time. The authors argue
that intelligent search techniques are necessary because integer programming is
incapable of solving a problem with more than one type of independent variable
[29]. In the same year Kannan et al. recognize that despite the complementary role
of academic research and industry applied simulation models, a gap exists between
the two: academia follow ―opportunity driven‖ models and industry aims for ―need-
based‖ models. The authors provide some defined requirements and ―success
factors‖ for simulation programming. A short but directed literature survey of
simulation modeling in the construction industry is also included [30].
In 2007, Bruno et al. propose a model using Stochastic Colored Petri Nets to
represent the operational dynamics of earth moving work. For this purpose, a
graphic and analytic model that represents the earth moving activities was idealized.
As a conclusion of this study, it can be stated that Petri nets models provide an
important instrument for decision makers when managing earth moving planning
and execution [31]. In 2008, Kapur et al. presented a new methodology for
integration of ‗variable productivity‘ data with a visualization model of earthwork
operations. The paper presents a prototype of a 4D visualization model which is
designed by integrating the road design data, quantities of cut and fill, productivity
model, algorithms for modeling terrain surfaces and a progress profile visualize.
The model generates automatically terrain surfaces of progress profiles for
earthwork operations and visualizes progress profiles throughout the construction
operations under different site and soil conditions. It is demonstrated with a real life
case study in a road project [32].

18
Finally Table 2.1 illustrates summary of the previous published models in the same
field of study.
Table 2.1: PROEQUIP and previous published models for earthmoving
n
Reference Model concept
and name
Description and Function
1 Willenbrock [10] Simulation (GPSS) to estimate cost for earthworks
2 Halpin [11] Simulation
(CYCLONE)
Allows the graphical representation and
simulation of discrete systems that deals with
deterministic or stochastic variables by dividing
the construction process into work tasks
3 Mayer and Stark
[12]
Linear
programming
model
Estimate excavation, hauling and fill cost
4 Luch and Halpin
[13]
Simulation
(MicroCYCLONE)
MicroCYCLONE is a microcomputer based
simulation program designed specially for
modeling and analyzing site level processes which
are cyclic in nature. In broader terms, it can be
used to model construction operations which
involves the interaction of tasks with their
related duration, and the resource unit flow
routes through the work tasks are the basic
rationale for the modeling of construction
operations.
5 Easa [14] Mathematical
model
Modification and improvement in unit cost
calculations
6 Easa [15] Mathematical
model
New modifications and improvement in unit cost
calculations
7 Alkass and Harris
[16]
Expert system
(ESEMPS)
Aid system using for selecting the road
construction equipment based on production rate
8 Ioannou [17] Simulation (UM-
CYCLONE)
UM CYCLONE is a discrete-event simulation
system for construction operations based on
activity scanning and activity cycle diagrams.
UM CYCLONE runs under DOS

19
9 Amirkhanian and
Baker [18]
Expert system Aid system using for selecting the equipment
based on productivity for dozers, scrapers,
excavators and trucks
10 Hanna [19] Mathematical
model
Selection the appropriate type and size of crane
base on project parameters
11 Rizk and Shi [20] Mathematical
model
Advice the optimum resource allocation in
construction sites
12 Huang et al. [21] Simulation
(DISCO)
The DISCO system provides a graphical
environment in which modeling and simulation
of construction operations can be conducted in
an interactive fashion. The model developed for
the bridge construction and the results of the
simulation are presented.
13 Tommelein et al.
[22]
Simulation
(CIPROS)
CIPROS is a knowledge-based construction
planning simulation system that enables its users
to formalize and test alternative construction
plans by relating project-specific design
drawings and specifications to a network of
construction processes, elementary simulation
process networks, and associated resources.
14 Christian and Xie
[23]
Expert system Advice the best type of machine for variety of
projects using rating system
15 Martinez [24] Simulation
(STROBOSCOPE)
STROBOSCOPE is a simulation system designed
as the successor to UM-CYCLONE. Based on
activity scanning and activity cycle diagrams.
16 Sawhney and
AbouRisk [25]
Simulation (HSM) HSM enhances and combines the concepts of
work breakdown structure and process modeling
to arrive at an advanced framework for
planning.
17 AbouRizk and
Hajjar [26]
Simulation (SPS) Selecting the equipment based on productivity
18 MaCabe [27] Network model
(MaCabe)
Diagnostic tool to obtain a near optimum solution
according for both quantity and capacity of each

20
resource
19 AbouRizk and
Hajjar [28]
Simulation
(SIMPHONY)
provides various services that enable the
developer to easily control different behaviors in
the developed tool such as simulation behaviors,
graphical representation, statistics, and animation.
These services allow building flexible and
userfriendly tools in a relatively short time.
20 Naoum and
Haidar [29]
Genetic algorithm Selecting the equipment based on life time
discounted cost
21 Kannan et al.
[30]
simulation Selecting the earthmoving equipment based on
literature survey
22 Bruno et al. [31] Stochastic colored
Petri nets
Instrument for planning earthmoving using
graphic and analytic model using productivity
results
23 Kapur et al. [32] new methodology
for integration of
‗variable
productivity‘ data
with a visualization
model
4D visualization model which is designed by
integrating the road design data, quantities of
cut and fill, productivity model, algorithms for
modeling terrain surfaces and a progress profile
visualize. The model generates automatically
terrain surfaces of progress profiles for
earthwork operations and visualizes progress
profiles throughout the construction operations
under different site and soil conditions.
24 Hassan Eliwah Simulation
(PROEQUIP)
It is an aid system using for earthmoving
equipment selection based on equipment
production rate only or equipment unit cost
only or equipment production rate and
equipment unit cost together.

CCHHAAPPTTEERR TTHHRREEEE
EEAARRTTHHMMOOVVIINNGG OOPPEERRAATTIIOONNSS

22
CCHHAAPPTTEERR 33
EEAARRTTHHMMOOVVIINNGG OOPPEERRAATTIIOONNSS
The function of heavy earthmoving equipment is to move or assist in the moving of
soil and rock from point A to point B. The purchase of this equipment constitutes a
particularly large investment on the part of the buyer. One cannot get into the
business of owning this type of equipment without substantial cash reserves and/or
financial backing. Regarding to that it is important that the reader have an
understanding of basics concerning the construction equipment. This section will
provide an introduction to the principles and vernacular of the field. The discussion
will cover in general the hydraulic excavator and hauler equipment.
33..22 MMAANNAAGGIINNGG EEAARRTTHHMMOOVVIINNGG OOPPEERRAATTIIOONNSS
The management of construction equipment is a difficult task. Equipment managers
are often called upon to make complex economic decisions involving the machines
in their charge. These decisions include those concerning acquisitions, maintenance,
repairs, rebuilds, replacements, and retirements. The equipment manager must also
be able to forecast internal rental rates for their machinery. Repair and maintenance
expenditures can have significant impacts on these economic decisions and
forecasts [33].
Managers must follow basic management phases to ensure that projects successfully
meet deadlines set forth in project directives. Additionally, managers must ensure
conformance to safety and environmental-protection standards. The basic
management phases are planning, organizing, staffing, directing, controlling and
executing [33].

23
Proper equipment selection is crucial to achieving efficient earthmoving and
construction operations. Consider the machine‘s operational capabilities and
equipment availability when selecting a machine for a particular task. The manager
should visualize how best to employ the available equipment based on soil
considerations, zone of operation, project-specific requirements, equipment total
cost and equipment productivity. Productivity estimates, productivity control, and
productivity records are the basis for management decisions. Therefore, it is helpful
to have a common method of recording, directing, and reporting production [34].
33..22..11 SSaaffeettyy
Engineers and safety officers are responsible for ensuring that personnel follow
safety standards. Time is usually the controlling factor in construction operations in
the theater of operations. The necessity for economy of time, coupled with the
temporary nature of much of the work, sometimes results in safety precautions that
are substantially lower than those used in civilian practice, but this does not mean
safety can be ignored.
Do not construe the lack of documentation of hazards as an indication of their
nonexistence or insignificance. Where safety precautions are necessary but are not
documented, or where existing precautions are judged to be inadequate, the
commanding officer must issue new or supplementary warnings. Each job has its
own particular safety hazards. Identify dangers and prepare a safety program to
reduce or eliminate all hazards. Supervisors must conduct all operations following
the guidance in the safety program [35].
The appropriate sections of safety manual identify safety rules for specific
equipment. Also, check applicable technical and operator manuals prior too perating
all equipment. Some general safety rules are as follows [35]:
 Inspect equipment before use, and periodically on a regular basis.
 Ensure that mechanized equipment is operated by qualified and authorized
personnel only.
 Use seat belts when they are available.

24
 Provide barriers to prevent personnel from walking under loading equipment
that has a hoist or lift capability.
 Operate equipment in a manner that will not endanger persons or property.
 Observe safe operating speeds.
 Shut down and turn off the engine when equipment is unattended.
 Stop the equipment completely (apply the parking brake if available) before
mounting or dismounting.
 Do not operate any machinery or equipment for more than 10consecutive
hours without an 8-hour rest interval.
 Post the safe load capacities at the operator's position on all equipment not
rigged to prevent overloading.
 Post the safe operating speeds at the operator‘s position on all equipment not
having a speed governor.
 Ensure that only the operator is on the equipment while it is running.
 Supervisors can authorize exceptions in emergency situations, some training
situations, and when required for maintenance.
 Shut down and turn off the engine when refueling motor vehicles and
mechanized equipment.
Before using a machine, a qualified, licensed operator should inspect and test the
equipment to determine its safe operating condition. Equipment operator
maintenance checks, service charts, and common sense ensure safe operation and
proper maintenance. Tag any unsafe machinery or equipment ―Out of Service, Do
Not Use‖ at the operator's position, to prevent its use until repaired. Ensure that the
equipment‘s safety features (backup alarms, lights, and so on) are operational [35].
For special repair and maintenance procedures follow those items: [35]
 Shut down or lock out equipment controls while a machine is being repaired,
adjusted, or serviced.
 Position the equipment in a place, away from the project area, that is safe for
the mechanic to work.

25
 Crib or block suspended machinery, equipment, or parts, and machines held
apart by slings, hoists, or jacks. Do not work underneath or between items
not properly blocked.
 Lower blades, bowls, hooks, buckets, and forks to the ground or onto
suitable blocking material when equipment is undergoing maintenance or
repairs.
When operating equipment at night
 Equip all mobile equipment with adequate headlights and taillights.
 Keep construction roads and working areas well illuminated until all workers
have left the area.
 Ensure that signalers, spotters, inspectors, maintenance personnel, and others
who work in dark areas exposed to vehicular traffic wear reflector zed vests
or other such apparel if the tactical situation permits.
When excavating
 Shore, brace, or slope excavations that are more than 4 feet deep, unless
working in solid rock, hard shale, hardpan, cemented sand and gravel, or
other similar materials.
 Design shoring and bracing to be effective all the way to the bottom of the
excavation.
 Use sheet piling, bracing, shoring, trench boxes, or other methods of
protection, including sloping, based upon calculation of the pressures exerted
by and the condition and nature of the materials being retained.
 Provide additional shoring and bracing to prevent slides or cave-ins when
excavating or trenching in locations adjacent to back-filled excavations or
when subjected to vibrations from traffic, vehicles, or machinery.

26
33..33 HHYYDDRRAAUULLIICC EEXXCCAAVVAATTOORRSS
Hydraulic excavators (back hoe) are designed to excavate below the ground surface
on which the machine rests. These machines have good mobility and are excellent
for general-purpose work, such as excavating trenches and pits. Because of the
hydraulic action of their stick and bucket cylinders, they exert positive forces
crowding the bucket into the material to be excavated. The major components of the
hydraulic hoe are the boom, the stick (arm), and the bucket. Fast-acting, variable-
flow hydraulic systems give hydraulic excavators high implement speed and
breakout force to excavate a variety of materials.
There are many variations in hydraulic excavators. They may be either crawler or
rubber-tire-carrier-mounted, and there are many different operating attachments.
With the options in types, attachments, and sizes of machines, there are differences
in appropriate applications and therefore variations in economical advantages [33].
Hydraulic power is the key to the advantages offered by these machines. The
hydraulic control of machine components provides: [33] faster cycle times,
Outstanding control of attachments, High overall efficiency, Smoothness and ease
of operation and Positive control that offers greater accuracy and precision.
Hydraulic excavators are classified by the digging motion of the hydraulically
controlled boom and stick to which the bucket is attached. A downward arc unit is
classified as a "hoe" [33]. To calculate the productivity of the excavator as a
separate unit (not as an earthmoving system) use equation (3.1) [33]:
Productivity = (3600 sec x Q x F x AS:D/t) x (E/60 min hr) x (1/VC) (3.1)
where
Q = heaped bucket capacity (Lcm), F = bucket fill factor, AS:D = angle of swing
and depth (height) of cut correction, t = cycle time in seconds (table 3.3), E =
efficiency (min per hour), VC = volume correction for loose volume to bank
volume

27
The main factors affect on excavators selection are (1) the cost per cubic meter of
material excavated and (2) the job conditions under which the excavator will
operate [33].
Unless the application calls for a lot of travel to, from, and around the job sites, a
track-type excavator could be the better choice. Track-type excavators provide good
traction and flotation in almost all kinds of underfoot conditions. Consistently good
drawbar power provides excellent maneuverability. The tracked undercarriage also
provides good overall stability. If the job calls for frequent machine repositioning, a
track-type excavator will provide better operating efficiency where raising and
lowering outriggers would take extra time (see Figure 3.1) [1].
A Wheel Excavator (see Figure 3.2) combines traditional excavator features such as
360° swing, long reach, deep digging depth, high loading height, high digging
forces and high lift capacities, with the mobility of a wheeled undercarriage. The
rubber tires allow the excavator to travel paved roads, work in shopping malls,
squares, parking lots and other paved areas without damaging the pavement. Its
mobility allows fast independent travel between jobsites as well as on the jobsite
giving you more job planning flexibility [1].
Excavator buckets are rated to conform to both PCSA standard No. 3 (Power Crane
and Shovel Association - Mobile Hydraulic Excavator Standards) and SAE standard
J-296 (Society of Automotive Engineers, Inc. - Excavator, Mini-Excavator, and
Backhoe Hoe Bucket Volumetric Rating) where the buckets are rated on both their
struck and heaped capacities as follows [1]:
Struck Capacity: Volume actually enclosed inside the outline of the side plates and
rear and front bucket enclosures without any consideration for any material
supported or carried by the spill plate or bucket teeth [1]. Heaped Capacity: Volume
in the bucket under the strike off plane plus the volume of the heaped material
above the strike off plane, having an angle of repose of 1:1 without any
consideration for any material supported or carried by the bucket teeth (see Figure
3.3 and Figure 3.4) [1].

28
Figure 3.1 Hydraulic hoe loading
a truck.
Figure 3.2 Wheel-mounted hydraulic hoe.
Figure 3.3 Basic parts of a hydraulic hoe
Figure 3.4 Hydraulic hoe
bucket capacity rating
dimensions.
To maximize production of the earthmoving system, do the following:
Ideal Bench Height and Truck Distance: For stable or consolidated materials, bench
height should be about equal to stick length. For unstable materials it should be less.
The most useful truck position is when the inside truck body rail is below the boom
stick hinge pin [1].
Optimum Work Zone and Swing Angle: For maximum production, the work zone
should be limited to 15° either side of machine center or about equal to

29
undercarriage width. Trucks should be positioned as close as possible to machine
centerline [1].Best Distance from the Edge; the machine should be positioned so
that the stick is vertical when the bucket reaches full load. If the unit is farther back,
breakout force is reduced. If it is closer to the edge, undercutting may occur and
time is wasted bringing the stick back out (see Figure 3.5) [1].
Figure 3.5 Maximize production of the earthmoving system

30
33..44 TTRRUUCCKKSS AANNDD HHAAUULLIINNGG OOPPEERRAATTIIOONNSS
Since the 1930s most of the material moved out of open cut mines/quarries has been
hauled by motorized trucks [33]. Whereas in underground mines material moved
along the haulage drives has been in rail mounted trucks pushed or pulled by
locomotives, and in recent times motorized truck haulage has been introduced
underground. Trucks are hauling units that provide relatively low hauling costs
because of their high travel speeds. The weight capacity of a truck may limit the
volume of the load that a unit may haul. The productive capacity of a truck depends
on the size of its load and the number of trips it can make in an hour.
In transporting excavated material, processed aggregates, and construction
materials, and for moving other pieces of construction equipment (see Figure3.6),
trucks serve one purpose: they are hauling units that, because of their high travel
speeds, provide relatively low hauling costs. The use of trucks as the primary
hauling unit provides a high degree of flexibility, as the number in service can
usually be increased or decreased easily to permit modifications in the total hauling
capacity of a fleet. Most trucks may be operated over any haul road for which the
surface is sufficiently firm and smooth, and on which the grades are not excessively
steep. Some units are designated as off-highway trucks because their size and
weight are greater than that permitted on public highways (see Figure3.7). Off-
highway trucks are used for hauling materials in quarries and on large projects
involving the movement of substantial amounts of earth and rock. On such projects,
the size and costs of these large trucks is easily justified because of the increased
production capability they provide [33].
Trucks can be classified by many factors, including [33]
1. The method of dumping the load rear-dump, bottom-dump, or side-dump.
2. The type of frame rigid-frame or articulated.
3. The size and type of engine gasoline, diesel, butane, or propane.
4. The kind of drive, for example two wheel
5. The number of wheels and axles

31
6. The class of material hauled, for example rock material
7. The capacity
8. The type of work
Trucks are classified under the type of work [1]:
 Rigid Frame Trucks: for use in hauling many types of materials
(see Figure3.8). The shape as the extent of sharp angles and
corners.
 Articulated Trucks: specifically designed to operate over rough
soft ground, and in confined working locations where a rigid-
frame truck would have problems (see Figure3.9, Figure 3.10)
 Off-highway dump truck: the body floor slopes forward at a slight
angle, typically less than 15° (see Figure3.11, Figure 3.12).
Some of the current day manufacturers include: Komatsu, Terex, Unit Rig, Pay-
hauler, Caterpillar, Euclid, Wabco, Bell, Liebherr, Tamrock [Toro], Atlas Copco-
Wagner, Elphinstone and many others that have developed units for specific
markets eg. The ―Kiruna‖ underground electric truck.
Figure 3.6 Truck tractor unit towing Figure 3.7 Off-highway truck

32
Figure 3.8 Highway rigid-frame rear-
dump truck
Figure 3.9 An articulated dump truck
Figure 3.10 An articulated dump truck
moving through soft ground
Figure 3.11 Off-highway tractor
towing a loaded bottom-dump
trailer
Figure 3.12 Highway bottom-dump

33
There are at least three methods of rating the capacities of trucks and wagons: [33]
1. Gravimetric: the load that it will carry, expressed as a weight.
2. Struck volume: the volumetric amount it will carry, if the load was water
level in the body (see Figure3.13).
3. Heaped volume: the volumetric amount it will carry, if the load was heaped
on a 2:1 slope above the body (see Figure3.13).
Figure 3.13 Measurement of volumetric capacity
The productive capacity of a truck depends on the size of its load and the number of
trips it can make in an hour. The number of trips completed per hour is a function of
cycle time. Truck cycle time has four components: (1) load time, (2) haul time, (3)
dump time, and (4) return time. Examining a match between truck body size and
excavator bucket size yields the size of the load and the load time. The haul and
return cycle times will depend on the weight of the vehicle, the horsepower of the
engine, the haul and return distance, and the condition of the roads traversed. Dump
time is a function of the type of equipment and conditions in the dump area [33].

CCHHAAPPTTEERR FFOOUURR
EESSTTIIMMAATTIINNGG TTEECCHHNNIIQQUUEESS

35
CCHHAAPPTTEERR 44
EESSTTIIMMAATTIINNGG TTEECCHHNNIIQQUUEESS
Earthmoving is the removal of existing material, which includes excavating or
loading, transporting, grading and unloading materials. The productivity, or output,
of earthmoving equipment can be defined as the total amount of material handled by
a machine in a certain time [7]. In estimating productivity, the basic element needed
to be analyzed is the productivity rate which is the amount of material a machine
can handle in a unit time such as a minute or an hour. In this chapter, significant
productivity factors common to different types of machines are first discussed.
Following this, the factors influencing the productivity rates of specific types of
machines are discussed. Problems in estimating machine productivity are
determined and a model for adjusting productivity estimates is also proposed.
There are two aspects to be considered in judging the appropriateness of a machine
for a particular job. One is its technical applicability, including productive capacity;
and the other is its economic feasibility [34]. In order to select appropriate
machines, machine performance is usually used as a criterion and judged by
estimating the unit costs which are costs spent on handling materials per unit
volume. Estimating costs is a difficult task in earthmoving planning, and in reality
construction organizations use different approaches to classify and calculate costs.
This chapter discusses the productivity and cost estimating of earthmoving
equipment and factors influencing productivity. The main elements of the costs are
analyzed and methods for calculating the costs are presented.

36
44..22 PPRROODDUUCCTTIIVVIITTYY EESSTTIIMMAATTIINNGG
The most convenient and useful unit of work done and unit of time to use in
calculating productivity for a particular piece of equipment or a particular job is a
function of the specific work-task being analyzed. To make accurate and
meaningful comparisons and conclusions about production, it is best to use
standardized terms [33].
Depending on where a material is considered in the construction process, during
excavation versus after compaction, the same material weight will occupy different
volumes (Figure 4.1). Material volume can be measured in one of three states:
 Bank cubic meter (BCM): A BCM is 1 cubic meter of material as it lies in
its natural/undisturbed state.
 Loose cubic meter (LCM): A LCM is 1 cubic meter of material after it has
been disturbed by an excavation process.
 Compacted cubic meter (CCM): A CCM is 1 cubic meter of material after
compaction.
Figure 4.1 Material-Volume Changes Caused by Construction Processes
When manipulating the material in the construction process, its volume changes.
(Tables 4.1, gives material-volume conversion and load factors [7]) The prime
question for an earthmover is about the nature of the material‘s physical properties;
for example, how easy is it to move? For earthmoving operations, material is placed
in three categories—rock, soil (common earth), and unclassified.

37
Table 4.1 Material Volume Conversion Factors
Most earth and rock materials swell when removed from their natural resting place.
The volume expands because of voids created during the excavation process. After
establishing the general classification of a soil, estimate the percentage of swell.
The quantity of material to be handled in an operation generally does not have a
direct influence on the productivity rates of individual machines. When the duration
of an operation has been set, however, it is a factor that should obviously be
considered in determining the size and number of machines for the overall
productivity of a fleet. In relation to the quantity, the physical state of the material is
important for estimates. When material is in its undisturbed normal state, it is
referred to as in situ, or bank, material, and usually occupies a fixed volume known
as the in situ volume or bank volume. After king excavated from its original
location, the volume of material expands due to the breakup of its naturally
compressed part. The material is then in a loose state and its volume is known as the
loose volume. The volume of a material varies from one state to the other, and has
great impact on the productivity rates. Therefore, the system requires users to input
what type of measure they take in estimating quantities. When users estimate the
volume of a soil to be handled in the bank state, the system converts it into the loose

38
volume since earthmoving machines actually handle mils in the loose state. When
calculating productivity, it should always be tried to get an accurate measure of
actual material weights and swell factor. Any companies or contractors which move
material will usually calculate productivity in ton per cubic meter. Earthmoving
contractors will usually get paid by the moved number of cuyd bank or m3 bank.
During the productivity estimating, some factors should considered such Fill Factor
Ratio between nominal volume and actual volume of a bucket or the body of a
dump truck, given as percentage of nominal volumeand Load Factor: Converts the
nominal payload volume of a dump truck (in loose cuyd or m3) into the effective
loaded volume in bank cuyd or m3. Most material codes define the load factor LF
as LF = Swell Factor SF x Fill Factor FF. Depending on the digging action of the
equipment and the operational conditions, a excavator may under-fill or over-fill its
bucket. This condition is measured by the bucket fill factor (ff) [34].
Bucket fill
factor (ff)
=
loose vol. of material excavated in an average load
nominal bucket capacity, Bc
(4.1)
Typical ff‘s for digging condition [34]: Easy: 1.0-1.2 or Medium:0.8-1.0 or Hard:
0.6-0.9. The bucket factor is a combination of swell factor and (ff). It enables the
bucket capacity in terms of volume of material in BCM to be readily calculated.
Bucket factor, Bf 
bucket fill factor
swell factor
(4.2)
So that:
Bucket capacity (BCM) = nominal bucket capacity (Bc) x bucket factor
(Bf)
(4.3)
The cycle time of excavator is the time taken to fill the bucket, swing the boom
round to the dump position, dump the bucket-load into the truck or hopper and
swing back to the digging position. For planning purposes, cycle times can be
estimated from manufacturer‘s literature or time studies. Operator skill is an
important factor. Table 4.2 lists a range of excavator cycle times [33].

39
Table 4.2: Loading excavator cycle times for a 90o
swing (seconds)
Digging Conditions
Capacity
(Bm3
)
Easy Medium Medium-
Hard
Hard
3
3
5
5.5
6
8
9
11.5
15
19
35
18
20
21
21
22
23
24
26
27
29
30
23
25
26
26
27
28
28
30
32
34
36
28
29
30
30
31
32
32
33
35
37
40
32
33
34
34
35
36
37
38
40
42
45
Where easy digging - loose material e.g., sand, small gravel. Medium digging,
partially consolidated materials e.g., clayey gravel, packed earth, anthracite.
Medium-Hard - well blasted lime-stones, heavy & wet clays, weaker ores, gravel
with large boulders. Hard - materials that require heavy blasting and tough plastic
clays, eg, granite, strong limestone, taconite, strong ores [33].
Excavator cycle times are normally based on a 90o
swing (S = 1). Obviously as the
swing angle increases, the cycle time will increase. The cycle time can be modified
accordingly by including a swing factor and typical values are listed in Table 4.3
[33].
Express swell as a percentage increase in volume (Table 4.4). For example, the
swell of dry clay is 35 percent, which means that 1 cubic meter of clay in the bank

40
state will fill a space of 1.35 cubic meters in a loosened state. Estimate the swell of
a soil by referring to a table of material properties such as Table 4.4.
In earthmoving work, it is common to compact soil to a higher density than it was in
its natural state. This is because there is a correlation between higher density and
increased strength, reduced settlement, improved bearing capacity, and lower
permeability. The project specifications will state the density requirements.
Soil weight affects the performance of the equipment. To estimate the equipment
requirements of a job accurately, the unit weight of the material being moved must
be known. Soil weight affects how dozers push, excavator load and truck load the
material. Assume that the volumetric capacity of a truck is 14 cubic meters and that
it has a rated load capacity of 20,000kgs. If the material being carried is relatively
light (such as cinder), the load will exceed the volumetric capacity of the truck
before reaching the gravimetric capacity. Conversely, if the load is gravel (which
may weigh more than 3,000 kgs per cubic meter), it will exceed the gravimetric
capacity before reaching the volumetric capacity [7].
NOTE: The same material weight will occupy different volumes in BCM,
LCM, and CCM. In an earthmoving operation, the basic unit of comparison is
usually BCM. Also, consider the material in its loose state (the volume of the
load). Table 4.4 gives average material conversion factors for earth-volume
changes.
Use a load factor (see Table 4.4) to convert the volume of LCM measured to BCM
measured (LCM x load factor = BCM). Use similar factors when converting
material to a compacted state. The factors depend on the degree of compaction.
Compute the load factor as follows:
If 1 cubic meter of clay (bank state) = 1.35 cubic meters of clay (loose state), then 1
cubic meter of clay (loose state) = 0.74 cubic meter of clay (bank state).
In this case, the load factor for dry clay is 0.74. This means that if a scraper is
carrying 25 LCM of dry clay, it is carrying 18 BCM (25 x 0.74).

41
Table 4.3: Excavator swing factors
Angleof swing 45 60 75 90 120 150 180
Swing factor 1.20 1.10 1.05 1.00 0.91 0.84 0.77
Table 4.4: Weight of Materials according to German Norm DIN/VOB
Weight of materials *
bank
lb/cuyd/kg/m3
swell in %
swell
factor
loose
lb/cuyd/kg/m3
Clay - natural bed 3400/2020 22 0.82 2800/1660
dry 3100/1840 24 0.80 2500/1480
wet 3500/2080 24 0.80 2800/1660
Clay with gravel - dry 2800/1660 17 0.86 2400/1420
wet 3100/1840 19 0.84 2600/1540
Decomposed rock 75% rock, 25% earth 4700/2790 42 0.70 3300/1960
50% rock, 50% earth 3850/2280 33 0.75 2900/1720
25% rock. 75% earth 3300/1960 24 0.80 2650/1570
Earth - dry packed 3200/1900 26 0.79 2550/1510
wet excavated 3400/2020 26 0.79 2700/1600
loam 2600/1540 23 0.81 2100/1250
Granite - broken 4600/2730 64 0.61 2800/1660
Gravel - pitrun 3650/2170 12 0.89 3260/1930
dry 2850/1690 12 0.89 2550/1510
Limestone - broken 4400/2610 69 0.59 2600/1540
crushed ----- ----- ----- 2600/1540
Sand - dry, loose 2700/1600 12 0.89 2400/1420
damp 3200/1900 12 0.89 2850/1690
wet 3500/2080 13 0.88 3100/1840
Sand with clay - loose 3400/2020 26 0.79 2700/1600
compacted ----- ----- ----- 4050/2400
Excavator productivity [7]
Qs = Bc Bf C Sf A O (PTF) (4.4)
Where: Qs=excavator productivity (Bm3
/hr), Bc =nominal bucket capacity (m3
),
Bf=bucket factor, C=theoretical cycles/hr for a 90o
swing = 60/tc, tc=excavator cycle
time for a 90o
swing (mins), Sf=swing factor, A=mechanical availability during
scheduled hours of work, O=job operational factor and PTF=propel time factor.
Note: actual bucket capacity (B) = nominal bucket capacity (Bc) * bucket factor (Bf)
(Bm3
)

42
Truck Productivity [7]
Let: Rated truck load, = Lt tons
Average material density =  t/m3
Excavator bucket capacity = B m3
1. Number of passes required to load the truck =
L
x B
t

(4.5)
2. Multiply by the excavator cycle time to obtain the time required to load the truck,
tL
3. Estimate the haul distances within the pit and from the top of the pit to the
ore/waste dumps.
4. Select suitable truck speeds for travelling up-grade loaded, on a level grade
loaded and empty and down-grade, empty. These speeds may be obtained from
charts and tables provided by the manufacturer; tup, tlevel1, tlevel2, tdown.
5. Estimate the time required to spot a truck at a shovel, ts.
6. Sum the above times to obtain the total truck cycle time, Tct
Tct = tL + tup + tlevel1 + tlevel2 + tdown + ts mins (4.6)
Number of truck cycles per hour =
60
Tct
(4.7)
Truck productivity, Qt = L x
Tt
ct
60
(4.8)

43
The haul distance is a major determinant of productivity rates for the simple reason
that with the increase of the length of haul distance, the time a machine spends on
the haul and return route generally increases, and its productivity rate decreases.
The total resistance is a major factor influencing productivity rates, since it could
slow down the travel speed of a machine [7]. We can describe the total resistance as
a summation of the grade and running resistance; Grade Resistance is a measure of
the force that must be overcome to move a machine over unfavourable grades
(uphill), grade assistance is a measure of the force that assists machine movement
on favourable grades (downhill), grades are generally measured in percent slope,
which is the ratio between vertical rise or fall and the horizontal distance in which
the rise or fall occurs [7]. For example, a 1% grade is equivalent to a 1 m rise or fall
for every 100 m of horizontal distance; a rise of 4.6 m in 50 m equals a 9.2% grade.
Rolling Resistance (RR) is a measure of the force that must be overcome to roll or
pull a wheel over the ground. It is affected by ground conditions and load, the
deeper a wheel sinks into the ground, the higher the rolling resistance, Internal
friction and tire flexing also contribute to rolling resistance, Experience has shown
that minimum resistance is approximately 2% (1.5% for radial tyres or dual tyred
trucks) of the gross machine weight (on tyres) or Resistance due to tire penetration
is approximately 0.6% for each cm of tire penetration [7].Thus rolling resistance
can be calculated using these relationships in the following manner: RR equal two
percent of GMW plus 0.6 percent of GMW per cm tire penetration [7]. In terms of
newtons it‘s a resistance per hundred kilograms of gross weight – from table of
rolling resistance in newtons per thousand kilograms of gross weight of various
road surfaces (Table 4.5) -. Other methods are derived from this basic expression.
Total resistance can also be represented as consisting completely of grade resistance
expressed in percent grade. In other words, the rolling resistance component is
viewed as a corresponding quantity of additional adverse grade resistance. This can
be done by converting the contribution of rolling resistance into a corresponding
percentage of grade resistance. Since 1% of adverse grade offers a resistance of 10

44
kg for each metric ton of machine weight, then each 10 kg resistance per ton of
machine weight can be represented as an additional 1% of adverse grade.
Table 4.5: ROLLING RESISTANCE FACTORS
Under-footing
Rolling Resistance Percent
Tyres
Bias Radial
Track Track+
Tyres
Very hard, smooth roadway, concrete, cold
asphalt, no penetration or flexing
1.5% 1.2% 0% 1.0%
Hard, smooth stabilised surfaced roadway no
penetration under load, watered, maintained
2.0% 1.7% 0% 1.2%
Dirtroadway, rutted under load, little
maintenance, no watering,25mm tyre
penetration
4.0% 4.0% 0% 2.4%
Rutted dirt roadway, soft under travel, no
maintenance, no stabilization, 100mm tyre
penetration or flexing
8.0% 8.0% 0% 4.8%
Very soft, muddy, rutted roadway 300mm tyre
penetration, no flexing
20% 20% 8% 15%
Various tyre sizes and inflation pressures will greatly reduce or increase the rolling
resistance. The values in this table are approximate, particularly for the track and
track + tyre machines. These value scan be used for estimating purposes when
specific performance information on particular equipment and given soil conditions
is not available [7].
By operating a machine skill-fully, a better operator usually spends less time on
activities and this yields higher production. The production correction factor due to
theski11 level of an operator can approximately be given as in Table 4.6 [1].
In routine operations, there is a certain amount of time spent on non-productive
activities. To estimate the actual output produced in the productive time, job

45
efficiency is often used to indicate the productive time as a fraction of the total time
spent. The job efficiency is usually expressed as a percentage of productive time in
minutes per hour (Table 4.7 and 4.8) [34]. In this research, it is assumed that the job
efficiency covers al1 minor idle or delay times, and other miscellaneous times, etc.
Table 4.6: Operator Skill Factor, FO
Table 4.7: Job Efficiency Factor, Fe
Table 4.8: Excavator operating efficiency
Management Conditions
Job
conditions
Excellent Good Fair Poor
Excellent
Good
Fair
Poor
0.83
0.76
0.72
0.63
0.80
0.73
0.69
0.61
0.77
0.70
0.66
0.59
0.70
0.64
0.60
0.54

46
From all the previous data, we can calculate the truck productivity as the following:
Step 1: Number of Bucket Loads: The first step in analyzing truck production is to
determine the number of excavator bucket loads it takes to load the truck [33].
Balanced number of bucket loads = (Truck capacity (Lcm)) /
(Bucket capacity (Lcm))
(4.9)
Step 2: Load Time: The actual number of bucket loads placed on the truck should
be an integer number. If one less bucket load is placed on the truck, the loading time
will be reduced; but the truckload is also reduced. Sometimes job conditions will
dictate that a fewer number of bucket loads be placed on the truck, i.e., the load size
is adjusted if haul roads are in poor condition or if the trucks must traverse steep
grades [33]:
Load time = Number of bucket swings X bucket cycle time (4.10)
Truckload (volumetric) = Number of bucket swings * volume of the
bucket
(4.11)
If the division of truck body volume by the bucket volume is rounded to the next
higher integer and that higher number of bucket swings is used to load the truck,
excess material will spill off the truck. In such a case, the loading duration the
bucket cycle time multiplied by the number of bucket swings. But the volume of the
load on the truck equals the truck capacity, not the number of bucket swings
multiplied by the bucket volume [33]:
Truckload (gravimetric) = Volumetric (Lcm) * unit weight (loose vol.
kg/Lcm)
(4.12)
Check: Truckload gravimetric < Rated gravimetric payload
Step 3: Haul Time: Hauling should be at the highest safe speed and in the proper
gear. To increase efficiency, use one-way traffic patterns. Based on the gross weight
of the truck with the load, and considering the rolling and grade resistance from the

47
loading area to the dump point, haul speeds can be determined using the truck
manufacturer‘s performance chart (see Figure 4.2) [1]
Haul time (min) = (Haul distance (m)) / (60 * 1000 * Haul speed
(km/hr))
(4.13)
Figure 4.2 Performance chart for Caterpillar 793C Truck
The chart should be used to determine the maximum speed for each section of a
haul road having a significant difference in grade or rolling resistance. While a
performance chart indicates the maximum speed at which a vehicle can travel, the
vehicle will not necessarily travel at this speed. Before using a performance chart
speed in an analysis, always consider such factors as congestion, narrow roads, or
traffic signals, when hauling on public roads, because these can limit the speed to
less than the value given in the chart [33].
Step 4: Return Time: Based on the empty vehicle weight, rolling and grade
resistance from the dump point to the loading area, return speeds can be determined
using the truck manufacturer's performance chart:

48
Return time (min) = (Return distance (m)) / (60 * 1000 * Return
speed (km/hr))
(4.14)
Step 5: Dump Time: Dump time will depend on the type of hauling unit and
congestion in the dump area. Consider that the dumping area is usually crowded
with support equipment. Total dumping time in such cases can exceed 2 min. After
dumping, the truck normally turns and returns to the loading area. Under favorable
conditions, a rear-dump can dump and turn in 0.7 min but an average unfavorable
time is about 1.5 min. Bottom-dumps can dump in 0.3 min under favorable
conditions, but they too may average 1.5 min when conditions are unfavorable [33].
Step 6: Truck Cycle Time: The cycle time of a truck is the sum of the load time,
the haul time, the dump time, and the return time (Table 4.3):
Truck cycle time = Load time + Haul time + Dump time + Return time (4.15)
Figure 4.3 Basic truck load cycle.

49
Step 7: Number of Trucks Required: The number of trucks required to keep the
loading equipment working at capacity:
Number of trucks = (Truck cycle time (min)) / (Load time (min)) (4.16)
Step 8: Productivity: The number of trucks must be an integer number, so if an
integer number of trucks lower than the result of Eq. (4.16) is chosen then the trucks
will control production
Productivity (Lcm/hr) = Truck load (Lcm) * Number trucks * (60 min
/ Truck cycle time (min))
(4.17)
When an integer number of trucks greater than the result of Eq. (4.16) is selected,
production is controlled by the loading equipment.
Productivity (Lcm/hr) = Truck load (Lcm) * (60 / Load time) (4.18)
Step 9: Efficiency: The productivity calculated with either Eq. (4.17) or (4.18) is
based on a 60 min working hour. That productivity should be adjusted by an
efficiency factor. Longer hauling distances usually result in better driver efficiency.
Driver efficiency increases as haul distances increase out to about 3,000 m, after
which efficiency remains constant [33].
Adjusted productivity (Lcm/hr) = Productivity (Lcm) * (Working
time (min/hr)) / 60 min
(4.19)

50
44..33 CCOOSSTT EESSTTIIMMAATTIINNGG
There are two aspects to be considered in judging the appropriateness of a machine
for a particular job. One is its technical applicability, including productive capacity;
and the other is its economic feasibility. In order to select appropriate machines,
machine performance is usually used as a criterion and judged by estimating the
unit costs which are costs spent on handling materials per unit volume. Estimating
costs is a difficult task in earthmoving planning, and in reality construction
organizations use different approaches to classify and calculate costs. This part
discusses cost elements which are significant in methods for calculating
earthmoving equipment costs. These methods are used to estimate costs in the
computer modeling if the user has no readily established hourly costs available
The unit cost of earthmoving works is essentially derived by dividing cost by
production. In its simplest case, if you rented an excavator with operator for $60 per
hour - including all fuel and other costs - and you excavated 100 cubic meters per
hour, your unit cost for excavation would be $0.60 per cubic meter. The hourly cost
of the excavator with operator is called the machine rate. In cases where the
machine and the elements of production are not rented, a calculation of the owning
and operating costs is necessary to derive the machine rate. The objective in
developing a machine rate should be to arrive at a figure that, as nearly as possible,
represents the cost of the work done under the operating conditions encountered and
the accounting system in use. Most manufacturers of machinery supply data for the
cost of owning and operating their equipment that will serve as the basis of machine
rates. However, such data usually need modification to meet specific conditions of
operation, and many owners of equipment will prefer to prepare their own rates
[36].
The machine rate is usually, but not always, divided into fixed costs, operating
costs, and labor costs. For certain cash flow analyses only items which represent a
cash flow are included. Certain fixed costs, including depreciation and sometimes
interest charges, are omitted if they do not represent a cash payment. In this

51
research, all fixed costs discussed below are included. For some analyses, labor
costs are not included in the machine rate. Instead, fixed and operating costs are
calculated. Labor costs are then added separately. This is sometimes done in
situations where the labor associated with the equipment works a different number
of hours from the equipment. In this research, labor is included in the calculation of
the machine rate. Fixed costs are those which can be predetermined as accumulating
with the passage of time, rather than with the rate of work (Figure 4.4). They do not
stop when the work stops and must be spread over the hours of work during the
year. Commonly included in fixed costs are equipment depreciation, interest on
investment, taxes, and storage, and insurance [36].
Figure 4.4 Equipment Cost Model.
Operating costs vary directly with the rate of work (Figure 4.4). These costs include
the costs of fuel, lubricants, tires, equipment maintenance and repairs.
Labor costs are those costs associated with employing labor including direct wages,
food contributions, transport, and social costs, including payments for health and

52
retirement. The cost of supervision may also be spread over the labor costs. The
machine rate is the sum of the fixed plus operating plus labor costs. The division of
costs in these classifications is arbitrary although accounting rules suggest a rigid
classification. The key point is to separate the costs in such a way as to make the
most sense in explaining the cost of operating the men and equipment [36].
44..33..11 FFiixxeedd CCoossttss
Depreciation
The objective of the depreciation charge is to recognize the decline of value of the
machine as it is working at a specific task. This may differ from the accountant's
depreciation schedule-which is chosen to maximize profit through the advantages of
various types of tax laws and follows accounting convention.
Depreciation schedules vary from the simplest approach, which is a straight line
decline in value, to more sophisticated techniques which recognize the changing
rate of value loss over time. The formula for the annual depreciation charge using
the assumption of straight line decline in value is: [36]
D = (P' - S)/N (4.20)
where P' is the initial purchase price less the cost of tires, wire rope, or other parts
which are subjected to the greatest rate of wear and can be easily replaced without
effect upon the general mechanical condition of the machine. S is Salvage value
which defined as the price that equipment can be sold for at the time of its disposal.
N is Economic life which defined as the period over which the equipment can
operate at an acceptable operating cost and productivity. Examples of ownership
periods for some types of road construction equipment, based upon application and
operating conditions, are shown in Table 4.9 [1].

Thesis_3_10

Recomendados

Recomendados

Más contenido relacionado

La actualidad más candente

La actualidad más candente (20)

Destacado

Destacado (8)

Similar a Thesis_3_10

Similar a Thesis_3_10 (20)

Thesis_3_10