A Computer Model for Selecting Equipment for Earthmoving Operations Using Simulation paper
1. Ain Shams University, Faculty of Engineering
Ain Shams Journal of Civil Engineering
(ASJCE)
Vol. 1.No.1, March, 2009, pp.203-214
A Computer Model for Selecting Equipment for Earthmoving
Operations Using Simulation
K.M.Shawki*; A.M.Ragb** ,H.K.Eliwah***
*Assistant prof., College of Engineering and Technology, AASTMT, Alexandria, Egypt.
** Associate prof., College of Engineering and Technology, AASTMT, Alexandria, Egypt.
***M.Sc. College of Engineering and Technology, AASTMT, Alexandria, Egypt.
ARTICLE HISTORY
Received:
Accepted
ABSTRACT
Earthmoving is often one of the most important operations in many
construction projects in terms of its great effect on costs and
productivity. In this paper we propose a simulation decision
supporting model using PROEQUIP to assist engineers and decision
makers to select the appropriate earthmoving operation and to control
and record earthmoving productivity and cost. For this purpose, a
graphic and analytic model that represents the earthmoving
productivity was idealized. Data were collected concerning a real
case, followed by several simulations aiming at the identified
operational scenarios. As a conclusion of the study, PROEQUIP
model provide an important instrument for decision makers when
managing earthmoving planning and execution .
Keywords
Construction ,equipment, production , simulation
Earthmoving refers to all the operations
involving the cut, loading, haulage,
unloading, grading and compaction of
materials in a civil engineering projects. To
improve earthmoving planning, a variety of
methods and techniques has been tried.
Planners have relied upon three methods to
estimate productivity: historical data;
references, such as equipment handbooks;
particular methods such as construction
simulation or statistic analysis.
In 1968 the Caterpillar Tractor Company
developed a graphical model for solving the
machine matching problem by analyzing
machine output. Also the Queue theory will
be used as the controlling tool for checking
the accuracy of number of allocated
equipment and the effect of any changes in
number of equipment on the project duration.
The history of Queue theory goes back to
1909. In this year A. K.Erlang, a Danish
engineer, studied the Queue systems and
waiting time in telecommunication systems.
In 1953 David G. Kendall formulated the
Queue theory to the form known today and
showed the empirical applications of this
theory for different problems. The first book
discussing the basis and applications of
Queue theory issued in 1958 by Philip M.
Morse. The main components of Queue
system are interiors (customers) and service
suppliers. In the truck
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filling and refilling problem, the trucks are
assumed as the customers of Queue system.
Hoes are known as service providers in this
system. One hoe along with specified number
of trucks is known as a Queue system. The
objective of solving this problem is to
determine the number of trucks that serve one
hoe.
Applications of simulation techniques to
earthmoving operations were made in the
1960s. Willenbrock (1972) developed a
model using a computer simulation language,
GPSS (General Purpose Simulation System),
to estimate cost for earthworks.
Simulation has been used extensively in many
areas of Construction Engineering starting
with the introduction of CYCLONE by
Halpin (1977). This methodology has been
considered as the basis for a number of
construction simulation systems. AbouRizk
and Shi (1994) developed an optimization
model that considers only the quantities of
resources being used along with their
respective user-specified boundaries. Special
purpose simulation (SPS) was proposed by
AbouRizk and Hajjar (1997) to address the
stated issues. The idea is to develop user
friendly simulation tools native to the
application domain itself. In (2007) Bruno,
Ernesto and Giovanni propose a model using
Stochastic Colored Petri Nets to represent the
operational dynamics of earth moving work.
Finally in (2008) Raj Kapur, Nashwan and
Serafim Castro presented a new method for
integration of ((variable productivity)) data
with a visualization model of earthwork
operations.
1. EART MOVING
FUNDAMENTALS
In order to understand the true benefits of an
automated earthmoving simulation system
such as PROEQUIP, it’s important to present
some background information about the
processes involved and the traditional method
of preparing project estimates. Earthmoving is
a specialized construction field where large
quantities of earth are moved from one
location to another location. Earthmoving
projects consist of many interacting processes
including preparation, loading, hauling and
dumping. Loading is the process of
transporting earth from the prepared earth pile
into incoming trucks. This is done using
hauling equipment such as hoes. Hauling
involves trucks traveling through roads with
varying slopes and ground conditions in order
to transport earth and return. Dumping is the
transfer of earth from the trucks into a
spreading pile. The travel velocity of trucks is
dependent on the grade and rolling resistances
of a given road segment. Grade resistance is a
measure of the force that must be overcome to
move trucks over uphill slopes. Rolling
resistance is a measure of the force that must
be overcome to roll or pull a wheel off the
ground.
2. SYSTEM DESIGN
The input data are one of the most important
aspects in the implementation of any
modeling and simulation study. In order to
calculate and compare production and cost
rates between several different models, a great
deal of time could be spent on the necessary
calculations. The computer modeling and
simulation system was designed to facilitate
this process. Microsoft Visual Basic.Net was
chosen as main programming language to
develop the main system PROEQUIP.
Microsoft Excel – powered by crystal ball
tool - was chosen for simulation calculation
by integration with the main system. The User
Interface is divided into seven sections. In the
first section the user may insert the data about
studied project. In second section (see Figure
(1)) the user may insert the data about
excavation job. Third section required user to
insert the data about the hauling road surface.
In section four (see Figure (2)) the user may
choose a single model from the database of all
available trucks. This section also allows user
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3. A Computer Model for Selecting Equipment for Earthmoving Operations Using Simulation
ability to add, edit or delete models to/from
database. In section five and section six the
user may insert the data about the equipment
costs. Section seven (see Figure (3)) is for the
simulation, the user may choose a model from
the database of all available trucks for
simulation calculation. The User interface
contains links to the traditional and simulation
results.
The software rolling resistance has been
integrated with a Microsoft Access database
of soil properties, road condition and trucks to
facilitate calculation using equation during
programming. The Soil Properties database
contains the table of available types of earth
to be moved – 23 types of materials are listed
-. This database lists the weight per BCM
(Bank cubic meter) and per LCM (Loose
cubic meter), bucket fill factor and the
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excavator cycle time for each type. The Road
Conditions database contains a table which
lists the types of haul roads from which the
user can choose – 21 types of roads surface
are listed -. The table also lists the rolling
resistances for these road types.
Finally there is a database contains a list of
trucks. Each record in this database consists
of the model, horse power, empty weight,
payload, top speed at loaded and heaped
capacity. There are also a database tables for
job efficiency factors.
The users can add new truck from the main
interface (see Figure (2)). This option
facilitates addition of a new truck into the
database.
The output section contains three parts:
deterministic performance result, simulation
result and recommendations page. The output
of the first part - by clicking on the
“RESULTS” button – may use as a
productivity monitor and control. It show the
production by LCM (Loose cubic meter) per
hour, BCM (Bank cubic meter) per hour or
LCY (Loose cubic yard) per hour, BCY
(Bank cubic yard) per hour, cost per hour,
cost per LCM … etc, number of buckets,
number of trucks need to result the maximum
production, maximum truck speed loaded and
empty (starting speed) at haul travel and (end
speed) at return travel, project duration per
hour and per day and expected finish date.
This section is shown in Figure (4).
3. THE SIMULATION
Simulation has been utilized to capture the
dynamic behavior and the characteristics of
the process being modeled. It is a proven
technique for the planning of construction
projects. Construction operations are
frequently impacted by uncertainties and
characterized by dynamically shared
resources. Accordingly, simulation is
considered a potent modeling technique to
capture their essential characteristics.
Considerable efforts have been made to
develop general simulation languages to
model these operations. In this paper during
simulation process, when a truck enters a road
segment, it is randomly assigned a travel
speed based on the speed study data to find a
travel time by equations. The input data to be
used in the simulation program have been
taken from literature values that are most
commonly used and from site researches. The
parameters which had been used for the
random variables are arbitrarily assumed and
are given in Table (1). The truck and
excavator unit cost random range variables
have been selected to be inserted by the
software user because the natural of the unit
cost and its changes according to variable
conditions.
The following basic modeling assumptions
are made in the proposed simulation program
are as follows:.
1. All trucks in the project are identical – for
each case - (i.e. their capacities, horse power,
speed, etc are the same).
2. To use the results for more than one
excavator in the project, all excavators in the
project should be identical in terms of their
loading capabilities – for each case - (i.e. they
have the same probability distribution types
and same parameters for loading process).
3.The project haul roads are designed to
provide two-way traffic for the trucks.
4. The excavator must complete loading for
the truck before start loading another truck
5. Single material type is assumed for the
simulation program and all trucks in the
project dump their loads at the same dumping
site.
6. All trucks start operation at the parking
area near the hauling point at the start of the
shift and park there at the end of each shift.
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5. A Computer Model for Selecting Equipment for Earthmoving Operations Using Simulation
7. During a simulation run, the haulage
system is performing without any rest (i.e.
eight hours per shift).
8. Up to five earthmoving cases can be
compared during simulation.
Because the random variables may change
every trip during the job, all simulation trials
just simulate project job until it finish for one
time then it record productivity, unit cost and
duration, those trials have been repeated x
times. The user can select the proper number
of trials according to the required accuracy of
the results. The trip trials has been designed
for 1,000 m3
excavation quantities jobs, but
the results will be fit for more than 1,000 m3
quantities jobs. To facilitate the mathematical
logic which has been used in the simulation,
see the proposed flowchart that included in
Figure (5).
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6. Shawki K.M, et.al,
4. PROEQUIP VERIFICATION
To verify PROEQUIP model, a solved
example is performed. The problem data are
as shown in Table (2) and data used for
estimating equipment cost are as shown in
Table (3).
Table (4) shows the comparison between
output data from the solved example and
resulting from PROEQIP model. One can see
that the output data from PRTOEQUIP and
the solved example are identical.
The results of the two cases of study are
shown in Figures (6, 7, 8 and 9). Figures (6
and 7) show the maximum production for
each of the proposed scenario. Form this
figures we can obtain the scenario which
gives the maximum production. Figures (8
and 9) shows the cost of each of the propose
scenario which we can get the case that gives
minimum cost
5. IMPLEMENTATION
In order to demonstrate PROEQUIP
capabilities, two case studies of projects will
be performed using particular project
conditions.
5.1 CASES FOR STUDY
The description of the first case study is
shown in Table (5). The available company
trucks are as shown in Table (6). Also the
equipment available trucks for renting are as
Table (7). The available company excavators
are as shown in Table (8). Also the excavators
available for renting are as Table (9).
The description of the second case study is
shown in Table (10). The available company
trucks are as shown in Table (11). Also the
equipment available trucks for renting are as
Table (12).
From Figures (6 and 7) we can recognize that
case 4 in first case of study gives maximum
production and minimum cost for
earthmoving. The fleet configuration consists
of Kumatsu PC210 LC crawler excavator and
Scania 113H trucks as hauling units. The
same for second case of study shown in
Figures (8 and 9).
6. CONCLUSIONS
This paper presents a computer model
“PROEQUIP” for equipment fleet selection
for earthmoving operations using
simulation. The developed system is
designed to assist engineers, owners, and
contractors for earthmoving projects in
selecting the best equipment fleet that can
complete the task in maximum production
and minimum cost. It also provides fleet
production rates, cost for each fleet, number
of buckets, number of trucks, maximum
speed of trucks for hauling and return,
project duration and project expected finish
date.
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14. Bruno, Ernesto and Giovanni Cordeiro “A
Stochastic Colored Petri Net Model To Allocate
Equipments For Earth Moving Operations”,
ITcon Vol. 13 (2008), Prata et al, pg. 490
15. Frank Harris "Modern Construction and Ground
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Longman Group, United Kingdom, 1994.
16. FAO Co., “Cost Control in Forest Harvesting and
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8
15. Figure (6) The simulation overlay charts for all study cases
16. Figure (7) The simulation overlay charts for all study cases
16
17. Figure (8) The simulation overlay charts for all study cases
18. Figure (9) The simulation overlay charts for all study cases
18
19. Table (1) Parameters for the Random Variables Used in the Models
Random Variables
Min.
Value
Max.
value
mean
standard
deviation
Type of
distribution
(Figure 8)
Notes
Excavator cycle time
(Sec.)
10 40 25 9.49 Normal
Truck speed loaded
(km/hr)
10 By user
auto
Beta
Alpha = 3
Beta = 1Truck speed empty
(km/hr)
20 By user Beta
Dump time (min.) 0.30 2.50 1.40 0.68 Normal
Unit cost By user auto Normal
Table (2) Articulated Truck and road configurations for example 1
• Truck Gross power = 309 hp
• Truck Net empty weight = 22,260 kg
• Truck Payload = 23,590 kg
• Truck Top speed loaded = 56.8 km/hr
• Truck heaped capacity = 14.4 m3
• Excavator heaped capacity = 1.9 m3, and its cycle time = 23 seconds
• Quantity of excavation material = 20000 m3
• Project work 8 hours per day and 6 days per week
• Road (smooth roadway - rolling resistance = 1.5%) with 90 km/hr legal speed
• Haul material (dry clay - loose material weight = 1480 kg/m3),
• The haul road from the borrow site to the dump is 4 km uphill grade of 2%
• Job efficiency = 50 minutes per hour = 0.83
• Excavator engine power = 115 hp
20. Table (3) Cost data for example 1
• Truck purchase price = 850,000 LE
• Truck Salvage price = 200,000 LE
• Excavator purchase price = 450,000 LE
• Excavator salvage price = 90,000 LE
• Interest rate = 5%
• Taxes rate = 9%
• Insurance rate = 6%
• Operator cost = 6 LE/hr
• Helper cost = 4 LE/hr
• There are 3 helpers
• Cost of fuel per liter = 1 LE
• Truck tire cost = 1000
• Engine type is diesel
• Site condition: shallow depth excavation, high safety and good management at
site (ownership period = 25,000 hrs for truck & 12,000 hrs for excavator (ZONE
A))
Table (4 ) Results of model testing
Parameters
SOLVED
EXAMPLE
PROEQUIP
Actual Production (LCM/hr) 211.02 LCM/hr 211.044 LCM/hr
Truck speed loaded (km/hr) 55.52 km/hr 55.52 km/hr
Truck speed empty (km/hr) 90 km/hr 90 km/hr
No. of required trucks 4 trucks 4 trucks
No. of buckets per truck 8 buckets 8 buckets
Earthmoving system unit cost
(LE/hr)
683.44 683.47
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21. Table (5) The description of the first case study
Project name: GAZADCO SHRIMP FARM EXPANSION
Project location: Jizan, Kingdom of Saudi Arabia
Excavation material type: Wet clay
Project Area: 910,000 m2
Area of the study part of the project: 75,000 m2
Quantity of excavation for project: 1,816,331 m3
Quantity of excavation for the study
part of the project:
150,000 m3
Distance from site to dump: 9000 m
Number of simulation trials: 5000 trials
Table (6) Available company trucks
S.N Type (Model)
Payload
(ton)
Heaped
capacity (m3)
Number
available
Equipment cost (SR)
T1 Mercedes Benz 3328K (1987) 18.5 16 8
P = 419,000
S = 65,000
(62.58 +- 10% SR/hr)
T2 Mercedes Benz 2638 (1993) 19 13 6
P = 280,000
S = 50,000
(50.20 +- 10% SR/hr)
T3 Mercedes Benz 2635 (1991) 20 14 8
P = 297,000
S = 50,000
(51.89 +- 10% SR/hr)
T4 Volvo – FM12.420 (2004) 19.2 14 13
P = 507,000
S = 45,000
(73.37 +- 10% SR/hr)
22. T5 Mercedes Benz 2628(1983) 18.96 15 14
P = 318,000
S = 45,000
(54.57 +- 10% SR/hr)
Table (7) Equipment available for renting (Trucks)
S.N Type (Model)
Payload
(ton)
Heaped
capacity
(m3)
Number
available
Equipment
unit cost
(SR/day)
RT1 Mercedes Benz 4143 (2003) 19 13 8 600 - 680
RT2 Mercedes Benz 4037 (1997) 19 12 4 560 - 620
Table (8) Available company excavators
S.N Type (Model)
Heaped
capacity (m3)
Number
available
Equipment cost (SR)
E1 Hyundai R140 LC – 7 1.5 1
P = 310,000
S = 90,000
(96.46 +- 10% SR/hr)
E2 Caterpillar 325 DL 1.9 1
P = 390,000
S = 100,000
(110.40 +- 10% SR/hr)
Table (9) Equipment available for renting (Excavators)
S.N Type (Model)
Heaped
capacity (m3)
Number
available
Equipment unit cost
(SR/day)
RE1 Kumatsu PC240 LC 1.5 1 680
RE2 Caterpillar 225 1.3 1 680
Table (10) The description of the second study case
22
23. Project name: Increase (Kabary/Matrooh) railway efficiency
Project location: Marsa Matrooh - Egypt
Excavation material type: Sand
Project Area: 28 km'
Area of the study part of the project: 5 km'
Quantity of excavation for project: 25000 m3
Quantity of excavation for the study
part of the project:
4000 m3
Distance from site to dump: 4000 m
Number of simulation trials: 5000 trials
Table (11) Company Equipment (Trucks)
S.N Type (Model) Payload
(ton)
Heaped
capacity
(m3)
Number
available
Equipment cost (EGP)
T1 Mercedes Benz 3331 19 12 11 P = 520,000
S = 100,000
(98.80 +- 10% EGP/hr)
T2 Scania 113H 14 10 5 P = 400,000
S = 100,000
(84.75 +- 10% EGP/hr)
Table (12) Equipment available for renting (Excavators)
S.N Type (Model)
Heaped
capacity
(m3)
Number
available
Equipment unit cost
(EGP/day)
RE1 Kumatsu PW160-7 wheeled 1.0 1 700
RE2 Kumatsu PC210 LC crawler 1.3 1 800
