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ASC Proceedings of the 42nd Annual Conference
Colorado State University Fort Collins, Colorado
April 20 - 22, 2006                 


 Use of Real Life Construction Projects as an Effective Tool for Teaching Construction Simulation


Hassan, M. M., Ph.D.

Bradley university

Peoria, IL


Construction simulation can significantly improve the efficiency and productivity of construction operations. However, simulation is rarely used in construction sites due to the level of expertise needed by the user and the lack of credibility that this technique has among contractors.  Therefore, construction programs need to educate future generations in this area.  Many construction programs around the US have responded to this need by adding a construction simulation course, at the senior or the Masters level, to their curriculum.  Although such a course familiarizes the students with the available simulation tools, it still does not improve the credibility of simulation techniques among contractors.  This paper proposes integrating a real life project simulation experience within the teaching of any construction simulation course.  Results of a questionnaire that presents the student’s opinions on the importance and benefits of adding a project to the simulation course are summarized.  In addition, some of the projects that were developed by the Bradley student simulation class are presented and the benefits the students gained by simulating a real time project are discussed in depth.


Keywords: Construction simulation, Project, learning by doing.





Computer simulation is a process of modeling a real world situation and developing a framework within which the system can be analyzed.  Better decisions can be taken based on the developed system analysis.  The importance of computer simulation is highlighted in the construction industry because of the complex interactions among various units on the jobsite. It is often necessary to make on-site decisions regarding the on-going daily operations. These decisions have a direct impact on cost, time and productivity.  Construction simulation can be an effective tool that provides systematic approach to the development of these decisions.


It is widely recognized that the construction industry suffers continuing losses due to daily planning errors or lack of consideration for all contributing factors that highly impacts cost, material flow, utilization of manpower, equipment handling, inventory control, and transportation of goods. To improve the efficiencies of on-site operations, detailed planning that takes into consideration the impact of all contributing factors on construction productivity is needed.  This need resulted in the development of a systematic approach to managing the construction operations using simulation tools (Halpin 1992).  These tools are currently being taught in graduate construction programs all over the US.  Among the programs that teach construction simulation in the US is the Department of Construction at Bradley University.  The construction simulation course at Bradley University aims to prepare the graduate construction students to use simulation tools to model construction operations.  It also teaches them how to improve the construction process using, what-if analysis.  In addition, it teaches the students how to systematically make better planning decisions. Finally, that class details the role of simulation and decision-making in planning and scheduling the different phases of construction.


There are two main problems facing the introduction of simulation techniques to manage construction operations: gaining credibility in practice among contractors, and achieve the level of expertise required from the user.  Although, research is currently being undertaken to simplify the tools for ease of use on sites, little is being done to increase the credibility of simulation tools within different contracting companies.  It is the author’s belief that the most effective way of gaining construction simulation credibility starts within our curriculum.  We need to integrate a construction simulation curriculum that shows the students how effective and valuable construction simulation can be. 


To accomplish this objective, a project was incorporated within the teaching of the construction simulation class at Bradley University.  Students were required to work in groups of 2-3 students.  Each group was required to select an on-going construction operation, taking place in a nearby site, and to develop a construction simulation model for the selected activity using Stroboscope software (Martinez 1996). The students compared the productivity resulting from the model with the real-time field productivity then redesigned the operation so as to improve the productivity while maintaining pre-assigned cost and project constraints.


After the semester ended, the students were asked to fill a questionnaire that captured their learning experience as well as the benefits of adding a project to the teaching of the construction simulation class.  The students were also asked to fill a questionnaire on the lessons learned so that better student simulation models can be formulated in future teachings of similar courses.


This paper provides an overview of the different construction projects that were produced by the student groups.  It also presents the added benefits that resulted from introducing a real life construction simulation project to both the students and the industry. Finally, it documents the lessons learned by the students that can be used to improve the construction project experience for future students.





Computer simulation is one of the most useful techniques that can be used to measure performance of construction operations. Other techniques like real system experimentation or application of mathematical models including queuing theory, Line of Balance (LOB), are either too expensive, time consuming or contain many assumptions that limit their use in the construction site.  Construction simulation is usually favored with the availability of modern computers that may simulate the operations realistically.  It is also inexpensive, flexible, and requires less computational time. In addition, it provides a wide range of applications including selection of equipments, allocating the best resource combination and assessing the construction under constraints like labor, time and weather factors (AbouRizk et. al. 1994).


Construction simulation has been applied as an academic tool for nearly five decades. Since then, many researchers have developed computer software that can be applied to all construction operations to measure performance index. CYCLONE was the earliest simulation program developed to measure performance of construction activities (Halpin 1977). Many repetitive construction operations have been studied using CYCLONE yet the method is not able to address the properties of resources and consumes significant time to maximize productivity. Thus, it is very difficult to model processes at a detailed level. RESQUE is a methodology developed with resource handling capabilities (Chang 1987). The methodology is an improvement to CYCLONE since it defines resource distinction and enhances simulation control. CIPROS characterizes resources by representing activities through a common resource pool. It also allows real properties for resources presented at the pool (Odeh 1992). RIsim simplifies the construction modeling method by considering resources as modeling elements and focuses on their interaction (Chau et. al. 2002). It simulates the interaction as operation logic and categorizes resources depending upon their inherent function.


More recent enhancements in the applications of construction simulation like STROBOSCOPE have considered diversity of resources and model resource selection schemes that resemble actual construction operations (Martinez and Ioannou, 1999). SIMPHONY is an advanced simulation tool that provides an intelligent environment through the utilization of construction Special Purpose Simulation (SPS) tools (AbouRizk and Hajjar 1999). It has also facilitated the construction simulation process by creating standard templates that can be directly used. Tommelein (1998) has shown the application of construction simulation in lean construction incorporating concepts like workflow variability and supply chain management.


Traditionally, simulation has helped the researchers and practitioners to estimate productivity and suggest alternatives to improve them by performing sensitivity analysis. These advantages have been enhanced by integrating construction simulation with optimizing tools like genetic algorithms (GA). A hybrid structure that assimilates simulation with GA to find the best resource combination for a construction operation was presented by Cheng (2003). In this system, the strings represent the set of resources and potential solutions to the problem and the one with better fitness value are more likely to produce better result in terms of system performance.


Although the construction operations are characteristically unique to one another, all operations constitute major activities that are similar to some extent and are repetitive in nature so that the application of construction simulation can be easily justified.



Simulation Project


Simulation steps


Simulation studies consist of steps that are commonly followed in developing and using simulation models. These steps consist of set of processes or a general sequence. Even though the virtue of construction process requires every activity to be performed in a different way, the general sequence will work as a guide for simulation modeling. These processes can be divided into a general sequence of steps:



Problem Formulation, in this step the modeler identifies the objectives and relates them to a performance index. This is also known as conceptualizing the model and helps in setting priorities within the developed model.


Data Collection, Data are collected to measure the performance of the system. These data can be also measured from real field observations, still pictures and movie camera. The quality of the collected data can easily affect what a model can address.


Validation, Validation creates credibility for the model.  This step starts very early in the model’s life and extends until the end.  In this step, the model developer examines the validity of the data collected as well as the assumptions made through statistical analysis methods and discussions with subject matter experts (SMEs) including informal validation like audit, documentation checking, inspection, reviews, static validation like cause effect graphing, control analysis, data analysis and dynamic validation techniques like acceptance testing, beta testing, statistical testing, visualization, and animation.


Model building, Building a model starts with focusing on a problem. The built model should be simple and easily understandable. The model should not be so sophisticated that it exceeds the client’s ability to understand and implement the solution.  Finally, the model needs to fulfill the simulation’s objective and be able to evaluate the system’s performance.


Verification, Verification consists of mainly testing the model. Entities flow and data input are examined in this part. Verification like validation must be performed through the entire simulation study. They are both continuous processes and the outcome of the simulation model should be considered for credibility.  The main benefit of verification is to control change and be able to correct mistakes the client perceives.


Data Analysis, Experiments need to be conducted with the simulation model to draw conclusion. Design of experiments and variance reduction technique are applied as analytical technique.  In analyzing the model the first step is working on the model, questioning the output, deciding and understanding what the model limits are and finally presenting a choice for the solution. Statistical techniques are used to analyze the output data from the production run.


Simulation model results are divided into three main categories: resource output measures displayed per queue; activity output measures displayed for each activity, and cost and performance measures calculated within the model output table.  For each queue, the following information can be calculated:



Content at end of simulation


Total amount of resource


Average waiting time


Minimum content


Maximum content


As for each activity, the following is calculated:



Number of times the activity was performed


Total number of times it has started


The time at which the first instance started


The time at which the last instance started


The average, maximum, and minimum durations


Finally, for cost and performance measure, the following can be calculated:



Total operation time


Hourly cost


Production rate


Unit cost


The modeler varies the input parameters to test how they affect the output measure – duration, cost, and productivity.  Then, recommendations can be made to redesign and improve the construction operation.  These recommendations can be modeled and tested to quantify their effect on the output.  The aforementioned steps allow the modeler to iterate for better model development. 


Project Description


In the Bradley simulation class, students were requested to work in groups of 2-3.  Each group chose a nearby on-going construction operation.  Each group studied their chosen operation through observation, video taping, and data recordings. They also communicated with the project engineer or the project superintendent to understand their constraints with respect to time, cost, and weather.  This communication helped them identify the operations bottle neck as well as determine the objective of their simulation.


Each group collected a minimum of 50 points for each activity duration, delivery times, and in queue waiting times.  The students then used statistical analysis to fit the collected data to probability distribution using manual methods as well as STATFIT software for verification.  Then, they drew the activity cycle diagram for their operation and modeled that operation using stroboscope simulation software (Martinez 1996).


After building the model, the students used experimental design (factorial or partial factorial design) to decide, before the runs are made, which particular configurations to simulate so that the desired objectives can be reached with the least amount of computation.  Based on the results of the experimental design, the students decided which variables to vary in order to maximize output performance measures - including cost, duration, and overall productivity.  Finally, the students executed the desired number of runs then performed statistical output analysis, which was used to draw conclusions on how to improve the simulation objectives (performance measures).


The students then used their conclusions to build a second and a third model to evaluate alternative methods for conducting that operation. The aforementioned steps were repeated to prove their conclusions do improve performance measures while maintaining the operations constraints.  The students were asked to submit a report and a presentation as well as share their findings with the contractors running their selected operations.  


Summary of the projects conducted in class


Each group in the class simulated a different construction operation.  This section provides a quick overview of the different simulations.  One of the groups modeled a brick laying operation as part of the Methodist hospital renovation project in Peoria, IL.  The cost of brickwork was approximately $750,000.  It consisted of an adjustable scaffold spanning across a wall 60ft across and 55ft high.  A single boom-lift lifted mortar, piles of bricks and insulation boards required from the scaffold point on-site to the scaffold. A laborer on the scaffold supplied the boards, mortar and bricks to the individual brick layers. Eventually the brick layers laid the insulation boards and the bricks. 


A second group simulated a bridge abutment concreting as part of an international construction project. The operation placed 664m3 of concrete using concrete pumps. The total operation time was 10hr and 17min.  The contractor used 32 trucks with a loading capacity of 6, 7, 7.5 and 8m3 and 2 concrete pumps.  The operation was performed in 89 trips.  There were two placing/vibrating crews serving the operation. 


Another group simulated a bridge deck concreting as part of the I-74 renovation project. The location of this operation is the Murray Baker Bridge in East Peoria and the project was being run by United Contractors-Midwest.  Ready mix concrete trucks are batched at a concrete plant in East Peoria which is about seven miles away from the job site.  Once the truck arrives at the job site, the inspector takes concrete samples for the slump test and air content test.  Concrete samples were taken directly from the ready-mix trucks’ dis­charge system and out of the middle portion of the load.  After the samples are collected, the trucks proceed to the pump to unload. The truck then returns to the plant for washing and batching again. The concrete flow from the pumping truck must be continuous to keep up with the concrete paver without any stoppage. The concrete is spread using a concrete paver (Bidwell), whose function is to receive freshly mixed concrete and spread it to the required width and thickness.  The next work task is to consolidate the concrete by using two manual vibrators and working closely in front of the paver. The vibration shall be of sufficient duration and intensity to thoroughly compact the concrete, but shall not be continued so as to cause segregation.  Finally, four concrete labors start the finishing phase by pushing a transverse ironing screed behind the Bidwell to give the top surface its shape.


The last group, interested in environmental engineering, simulated a pipe laying operation as part of the renovation of aeration basins for the treatment of wastewater.  The site is located at the greater Peoria district-sanitary and water treatment plant. The operation consists of replacing concrete pipes by PVC pipes, which have higher performance and better weathering resistance.  PVC pipes are shipped from the manufacturer and stacked in plies.  Section of each pipe is 12in and pipes are interconnected using bolts and screws.  Adequate aeration is also an important element in keeping the wastewater treatment basin content mixed and in suspension.  With adequate mixing, incoming pollutants and wastewater are better distributed throughout the entire basin. This results in more uniform and efficient treatment.


Each of the four groups had performed the required studies as outlined in the project description section above.  As an illustrative example, the following section will present a model that was built by the students for the brick laying operation.


Sample Model – a brick laying operation Model


The modeled brick laying operation was part of the Methodist hospital renovation project located in Peoria, IL.  The operation consisted of an adjustable scaffold spanning across the wall 60ft across and 55ft high. A single crane lifts mortar, bricks and insulation board required from the scaffold point onsite to the scaffold. A laborer on the scaffold carries the mortar and supplies the bricks to the brick layers. Eventually, the brick layers install the insulation boards and lay the bricks. 


The goal of the project was to perform a structured walk through the steps of the simulation study, adequately simulate a real time model of the actual field operations and suggest improvement measures.  The main objective of the modeling process was to improve the productivity while maintaining the current project budget.  Secondary objectives were to check the adequacy of the current conditions to perform the operation and to check the restraints caused by weather condition and suggest improvement measures.

Data were collected to measure the performance of the system. The collected data were measured from the real field scenario using still pictures and movie camera as well as manual recordings from observations.  Data were collected on a daily basis for a month.  A sample data of the collected data for the supply of mortar activity is shown in Table 1.  The mean of the duration of this activity was 12.06 seconds and the standard deviation was 9.05 seconds.  Data were collected for the remaining activities in the same way.  The mean and standard deviation were calculated for all activities. The shape functions were also calculated for every activity to fit it to a distribution.  STATFIT software was used to verify the choice of the fitted distributions. 


The collected data and distributions were then used to draw the activity cycle diagrams.  The main components of an activity cycle diagram, shown in Figure 1, are:



A queue that contains a resource that will be used.


A combi that represents a constrained activity. A queue has to precede a combi


A normal activity that is not constrained


A link that joins different activities an resources


Table 1  


Sample of collected data for supply of mortar (first 7 out of 500 points)


Supply mortar to the Mason

Record Number

Time in seconds


















Figure 1.  Activity Cycle Diagram Components


The brick laying operation’s activity cycle diagram is shown in Figures 2 and 3.  Each resource is placed in a queue with the initial content defined. For example, the initial content of the bricks was 15,040.  The distribution that each normal or combi activity follows based on the results of the statistical analysis is shown below that activity.  Finally, the link defines how many resources are drawn or released each time the activity is performed.  


Figure 2 shows the boom lift cycle.  As shown in Figure 2, the boom lift performs three main functions, delivery of insulation board, delivery of mortar and delivery of bricks to the masonry crew.  This type of activity cycle diagram is known as a butterfly diagram as the resource “the boomlift” alternates between the three cycles to transport the needed insulation board, mortar and bricks.  Figure 3 shows how the bricks are constructed once they arrive to the masonry crew.






Figure 2. Activity cycle diagram of a brick laying operation – Boom lift cycle



Figure 3. Activity cycle diagram of a brick laying operation – Brick installation


Benefits of a simulation project


The students completed a questionnaire that captures their learning experience as well as the benefits of adding a project to the teaching of the construction simulation class after the semester ended.  This section summarizes the results of this questionnaire.


The students agreed that adding a real time project was a useful learning tool.  Ninety percent of the students cited real life project experience as a major advantage.  Student also learned how to identify real life problems in the field and areas that can be improved and re-engineered via simulation.  They realized the benefits of detailed on-site planning and gained a sense of the level of complexity of coordinating different trades and other daily on-site activities.  They also realized the importance of simulation as a cost effective alternative to learning by experience on the construction site. 


Students also cited how this experience helped them to believe in simulation as an effective tool to enhance construction operations. Currently, wide spread use of simulation needs industry acceptance and the industry needs to utilize simulation to improve its performance. The students will act as a link that brings simulation to the industry.  The students realized this fact and cited how this experience will help them to gain industry acceptance because today’s construction student is tomorrow’s construction manager.  Some of them were quoted saying that this experience will help them persuade senior management to adopt simulation as a tool by presenting to them valid results and potential benefits. 


Students used the project as a learning tool to be able to visualize how theoretical simulation methods can be implemented in practice in the correct sequence.  The students also realized the importance and difficulty of collecting data.  They were given inaccurate data from the company records and spent month collecting the needed model data.  Thus, when they start their practical careers, they will enforce accurate data collection providing their companies superior historical data.  They also gained experience with different output analysis skills, statistical analysis, and optimization methods.


Some groups discovered that sometimes the real constraints facing the construction process are not even considered by the contractors.  This was the case in the Methodist hospital where the major cause of the operation delay was weather conditions that the contractor had failed to anticipate.  Instead, the contractor shut down the operation on daily basis to accommodate for unfavorable weather conditions.  Weather conditions were accounted for in their alternative methodology model and better performance measures were reached.  All the students agreed that they would use construction simulation tools on their projects after graduation.





This paper recommends that a real life on-going project be used as a core curriculum within the teaching of construction simulation.  This recommendation has been implemented within the teaching of a construction simulation class at Bradley University.  The result of this recommendation was very positive as it helped in building credibility for construction simulation with the students and the contractors they interacted with.  A questionnaire was prepared by the author and distributed to the students after the semester ended to quantify the benefits of adding a construction project.  This paper summarizes the results of this questionnaire.





The authors would like to acknowledge the assistance of the CE537 students, who participated in the survey and helped the author with their feedback and comments.






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Construction Simulation Project Evaluation Questionnaire