Generic Process Mapping and Simulation Methodology for Integrating Site Layout and Operations Planning in Construction

The present research is intended to address dynamic construction-process simulation methods, with a focus on how to effectively model resource transit among various activity locations in the site system. Following a review of basic simulation paradigms and recent research developments, we propose a new process mapping and simulation methodology for modeling construction operations. The simulation algorithm is presented and the process mapping procedure is illustrated step by step using an earth-moving example featuring technology and resource constraints. It is straightforward to convert the resultant process mapping model describing workflows and resource flows over site locations into a simulation model. A STROBOSCOPE model is formed for the same problem definition to contrast and cross-validate our methodology with the established activity cycle diagram-based modeling approach. One additional case of modeling the concreting site operations by the hoist and barrow method is also given to demonstrate the application of the proposed methodology in practical settings.     

Simplified Discrete-Event Simulation Approach for Construction Simulation

The methodology of discrete-event simulation provides a promising alternative solution to designing and analyzing dynamic, complicated, and interactive construction systems. In this paper, an attempt is made to extend the previous work of simplifying construction simulation by delving into the fundamental approaches for discrete-event simulation. A new simplified discrete-event simulation approach (SDESA) is presented through extracting the constructive features from the existing event/activity-based simulation methods; both the algorithm and the model structure of simulation are streamlined such that simulating construction systems is made as easy as applying the critical path method (CPM). Two applications based on real road construction projects in Hong Kong serve as case studies to illustrate the methodology of simulation modeling with SDESA and reveal the simplicity and effectiveness of SDESA in modeling complex construction systems and achieving the preset objectives of such modeling. They are a granular base-course construction system featuring both cyclic and linear processes and an asphalt paving construction system with complicated technological/logical constraints. As a general-purpose method for construction planning, SDESA enables practitioners to deal with what the CPM-based network analysis method fails to solve by offering discrete-event simulation capabilities. Furthermore, the SDESA can potentially be adapted to special-purpose simulation tools to tackle large and complicated construction systems of practical size that have yet to find convenient solutions with existing simulation methods.     

Integrating Construction Operation and Context in Large-Scale Construction Using Hybrid Computer Simulation

This research proposes a hybrid simulation approach based upon the principles of system dynamics (SD) and discrete event simulation (DES), which facilitates a better understanding of complex interactions among various processes in large-scale construction. The significance of the construction context that interacts with construction operations is highlighted, and a hybrid SD-DES approach is proposed as a means to capture the feedback between the two. In particular, this paper focuses on how to seamlessly integrate SD and DES within the framework of a modeling perspective. For the purpose of substantiating the discussion, a pipeline installation process is modeled using the proposed hybrid approach, with specific consideration given to how the approach can serve to address complex interactions between operation and context.     

Simulation Model to Forecast Project Completion Time

Project cost is most sensitive to its schedule. The construction project environment comprising dynamic, uncertain, but predictable, variables such as weather, space congestion, workmen absenteeism, etc., is changing continuously, affecting activity durations. The reliability of project duration forecast can be enhanced by an explicit analysis to determine the variation in activity durations caused by the dynamic variables. A computer model is used to simulate the expected occurrence of the uncertainty variables. From the information that is collected normally for a progress update of the tactical plan and by simulating the project environment, the combined impact of the uncertainty variables is predicted for each progress period. By incorporating the combined impact in the duration estimates of each activity, the new activity duration distribution is generated. From these activity duration distributions, the probability of achieving the original project completion time and of completing the project at any other time is computed.     

General-Purpose Situational Simulation Environment for Construction Education

The traditional construction education model based on precise well-defined problems and formal definitions is not satisfactorily fulfilling its mission of educating the decision makers of tomorrow. This realization has moved several researchers to explore alternatives where problem solving is carried out in conjunction with the environment, and concepts are embedded in the context promoting learning within the nexus of the activity. Several efforts have been undertaken to develop these environments resulting in a variety of special-purpose situational simulations. However, special-purpose situational simulations exhibit inherent limitations related to their application breadth, flexibility, and promotion of collaborations. These limitations cannot be resolved within the framework of special-purpose learning environments. A general-purpose environment is required to overcome these shortcomings and take full advantage of the situational learning paradigm. This paper describes the conceptual framework and pilot implementation of such an environment called the Virtual Coach.     

Framework for Building Intelligent Simulation Models of Construction Operations

Modeling and analyzing construction operations using simulation techniques allows researchers to capture the uncertainty and randomness usually associated with these operations and can thus be an effective tool for analysis and improvement. However, the effort and knowledge required to build simulation models and experiment with them tend to limit the use of simulation in construction. A common recommendation for removing this obstacle found in the literature leans towards developing simulation tools that reduce model development and experimentation time on the construction engineer’s side by packaging most of the knowledge required into the tool itself. Such “intelligent” simulation modeling tools may significantly impact the way construction engineers use simulation techniques in day-to-day decision?making. This paper presents a framework that extends and formalizes this recommendation by providing the foundation for building intelligence into simulation objects. The proposed framework provides the structure necessary for building intelligence and autonomy into simulation objects and permits a further reduction in the knowledge required to experiment with simulation models. This approach also automates model modification, not only through changes in numeric parameters, but through topological model changes as well, which may assist the model user in making many decisions throughout the different phases of simulation experimentation.     

RISim: Resource-Interacted Simulation Modeling in Construction

Discrete-event simulation is an effective approach to analyze construction operations. However, it is usually time-consuming and knowledge demanding to develop a practical simulation model, and thus not cost-effective due to the uniqueness and relatively short life of construction projects. The capability of discrete-event simulation modeling has not been popularly recognized by site managers until recently. A clear and explicit solution is to simplify and speed up the model development cycle, so as to enable users without much knowledge of simulation technology to easily generate a model in a relatively short period of time. In this paper, a resource-interacted simulation (RISim) modeling approach is presented, which adopts a resource oriented methodology to promote an intuitive feel to simulation modeling. In RISim, an operation is modeled in two abstraction levels—namely, the resource level and process level. An operation is viewed as a collection of resources and their interactions. Complex resources and simple resources are used to respectively represent resources with or without their own processes. The operation logic is mainly represented with internal complex resource flows, which are integrated by simple resource flows between complex resources. Resource flows can be easily conceived by site managers, enabling them to build up the logic naturally and simply. A resource library is used to implement resource reusability. Finally, an example in concrete delivery operation illustrates the methodology of resource-interacted simulation modeling and its potential for “plug-in and simulate.”     

Computer Simulation Model: Construction Analysis for Pavement Rehabilitation Strategies

Most state highways in the United States were built during the 1960s and 1970s with an infrastructure investment of more than $1 trillion. They now exceed their 20?year design lives and are seriously deteriorated. The consequences are high maintenance and road user costs because of degraded road surfaces and construction work zone delays. Efficient planning of highway rehabilitation closures is critical. This paper presents a simulation model, Construction Analysis for Pavement Rehabilitation Strategies (CA4PRS), which estimates the maximum amount of highway rehabilitation/reconstruction during various closure timeframes. The model balances project constraints such as scheduling interfaces, pavement materials and design, contractor logistics and resources, and traffic operations. It has been successfully used on several urban freeway rehabilitation projects with high traffic volume, including projects on I-10 and I-710. The CA4PRS helps agencies and contractors plan highway rehabilitation strategies by taking into account long-life pavement performance, construction productivity, traffic delay, and total cost.     

Automated Statistical Analysis in Stochastic Project Scheduling Simulation

This paper describes a stochastic simulation-based scheduling system (S3) that: (1) integrates the deterministic critical path method (CPM), the probabilistic program evaluation and review technique (PERT), and the stochastic discrete event simulation (DES) approaches into a single system and lets the scheduler make an informed decision as to which method is better suited to the company’s risk-taking culture; (2) automatically determines the minimum number of simulation runs in DES mode and therefore optimizes the simulation process; and (3) provides a terminal method that tests the statistical significance of the differences between simulations, hence eliminating outliers and therefore increasing the accuracy of the DES process. The system is based on an earlier version of the system called stochastic project scheduling simulation and makes use of all the capabilities of this system. The study is of value to practitioners because S3 produces a realistic prediction of the probability of completing a project in a specified time. The study is also of relevance to researchers in that it allows researchers to compare the outcome of CPM, PERT, and DES under different conditions such as different variability or skewness in the activity duration data, the configuration of the network, or the distribution of the activity durations.     

Iconic Animation for Activity-based Construction Simulation

This paper discusses the development of an animation tool for the activity-based construction (ABC) modeling and simulation system. The tool uses an activity-based network diagram, i.e., ABC simulation model, as the animation background image, and uses precreated two-dimensional (2D) iconic images for simulation entities (e.g., resources). The animation process displays the queuing status and dynamic movements of 2D iconic images on the background. It also distinguishes active and idle states of resources and activities. Dynamic reports are available for selected activities with graphs including the production rate and utilization of involved resources. From visualizing the change of status of a simulation process and dynamic interaction between simulation entities in the process, the user can better understand the dynamic nature of the construction process. Animation provides an avenue to demonstrate how dynamic operations are simulated. It also provides an effective tool for the user to verify a simulation model and to validate the obtained simulation results. Compared to other systems, the ABC animation does not require any extra effort in addition to the ABC simulation model constructed for simulation purposes. Therefore, the presented technology greatly reduces the time and cost for achieving animation. A variety of useful information can be observed through animation, and is illustrated using two construction examples.     

Application Framework for Mapping and Simulation of Waste Handling Processes in Construction

This research is focused on modeling waste-handling processes in construction, with particular emphasis on how to map out and simulate on-site waste sorting processes. The research proposes an application framework for (1) guiding the development of process mapping models and simulation models; and (2) further assessing the cost effectiveness of on-site waste sorting efforts under practical site constraints (such as labor resource availability, time control on refuse chute usage, and limited working area space in a building site). The connection has been established between the mapping and simulation techniques in the context of modeling waste handling processes in construction sites, such that the process flowchart resulting from the mapping technique can serve as convenient model input to facilitate the creation of a “dynamic” operations simulation model. A case study of the on-site waste sorting method with one refuse chute for waste classification is presented to demonstrate the complete application framework spanning (1) process mapping; (2) mapping-to-simulation model conversion; and (3) method optimization based on valid simulations.     

Network Scheduling Variations for Repetitive Work

Observant CPM schedulers in the early years of CPM application, the 1960s, noted that there were often familiar steps inherent in scheduling similar projects. This similarity occurred in the development of housing neighborhoods, such as New Town of Columbia, Maryland; schools, as in the Philadelphia School District Program involving 200 schools; and in the review process for projects during the preconstruction phase in large cities, namely Philadelphia and New York. In these situations, the development of a prototypical network provided a cost‐effective method of applying network scheduling to major programs. These applications are described in the form of case studies, and a recent application to the King Khalid Military City Housing Program is noted. An alternate manual approach to repetitive scheduling in highrise construction, the vertical production method developed in the 1970s, is also described.     

Resource Management in Construction

Resource plannirtg and management is one of the most important ingredients for competitiveness and profitability in today's construction industry. In order to control costs, equipment and labor should be utilized in the most efficient way possible. This can be achieved by minimizing the total cost of leased resources under the constraint of maximum and most efficient use of owned equipment and contracted labor force. This paper presents a mixed‐integer linear programming model for the management of resources throughout the project life. Based on the Critical Path Method time analysis, the model derives the schedule for equipment rentals and transient resources, as well as the utilization scheme for owned equipment and other available resources. The model can be used as an estimating tool for multi‐project resource planning and sharing, and as a means to implement the most efficient utilization of resources throughout the duration of the whole project.     

Stochastic Network Model for Planning Scheduling

A stochastic network model consisting of dependent and independent random variables is developed for construction scheduling. The network model is based on Monte‐Carlo simulation. Data for each network activity consist of a time distribution for the activity under optimal conditions and a series of time distributions for various problems that may lengthen the activity completion time. Dependencies between network activities may be modelled; also, time dependencies for a network activity may be modelled. The implementation of the model is discussed.     

Materials Handling System Simulation in Precast Viaduct Construction: Modeling, Analysis, and Implementation

The interactive, complicated system environment of a construction site renders conventional site layout planning and scheduling techniques to be inadequate in coping with materials handling system design in construction. In this paper, we present a university-industry joint endeavor for improving the effectiveness of the materials handling system on a precast viaduct construction project in Hong Kong by implementing the simplified discrete-event simulation approach (SDESA) along with its computer platform resulting from recent research. How to apply the simulation methodology of SDESA is elaborated step by step. Particular emphasis is placed on procedures of establishing a simulation model, validation of the simulation model, design of simulation experiments, and analysis of simulation results. With process flowchart, site layout plan, and process animation produced in a view-centric simulation environment, it is straightforward to establish, validate, and communicate the operations simulation. The research team convinced the project director, as well as field managers, of the functionality and effectiveness of operations simulation. The knowledge derived from simulation added to experiences of site managers in materials handling system design. With the aid of simulation, even junior engineers would be capable and confident to draw up an actionable construction plan that would lead to enhancement of cost effectiveness and productivity in the field.     

Efficient Repetitive Scheduling for High-Rise Construction

A new scheduling and cost optimization model for high-rise construction is presented in this paper. The model has been formulated with a unique representation of the activities that form the building’s structural core, which need to be dealt with carefully to avoid scheduling errors. In addition, the model has been formulated incorporating: (1) the logical relationships within each floor and among floors of varying sizes; (2) work continuity and crew synchronization; (3) optional estimates and seasonal productivity factors; (4) prespecified deadline, work interruptions, and resource constraints; and (5) a genetic algorithms-based cost optimization that determines the combination of construction methods, number of crews, and work interruptions that meet schedule constraints. A computer prototype was then developed to demonstrate the model’s usefulness on a case study high-rise project. The model is useful to both researchers and practitioners as it better suits the environment of high-rise construction, avoids scheduling errors, optimizes cost, and provides a legible presentation of resource assignments and progress data.     

Probability of Project Completion Using Stochastic Project Scheduling Simulation

This paper introduces a software, Stochastic Project Scheduling Simulation (SPSS), developed to measure the probability to complete a project in a certain time specified by the user. To deliver a project by a completion date committed to in a contract, a number of activities need to be carried out. The time that an entire project takes to complete and the activities that determine total project duration are always questionable because of the randomness and stochastic nature of the activities’ durations. Predicting a project completion probability is valuable, particularly at the time of bidding. The SPSS finds the longest path in a network and runs the network a number of times specified by the user and calculates the stochastic probability to complete the project in the specified time. The SPSS can be used by a contractor: (1) to predict the probability to deliver the project in a given time frame and (2) to assess its capabilities to meet the contractual requirement before bidding. The SPSS can also be used by a construction owner to quantify and analyze the risks involved in the schedule. The benefits of the tool to researchers are: (1) to solve program evaluation and review technique problems; (2) to complement Monte Carlo simulation by applying the concept of project network modeling and scheduling with probabilistic and stochastic activities via a web based Java Simulation which is operateable over the Internet, and (3) to open a way to compare a project network having different distribution functions.     

Optimal Planning and Scheduling for Repetitive Construction Projects

This paper presents a multiobjective optimization model for the planning and scheduling of repetitive construction projects. The model enables construction planners to generate and evaluate optimal construction plans that minimize project duration and maximize crew work continuity, simultaneously. The computations in the present model are organized in three major modules: scheduling, optimization, and ranking modules. First, the scheduling module uses a resource-driven scheduling algorithm to develop practical schedules for repetitive construction projects. Second, the optimization module utilizes multiobjective genetic algorithms to search for and identify feasible construction plans that establish optimal tradeoffs between project duration and crew work continuity. Third, the ranking module uses multiattribute utility theory to rank the generated plans in order to facilitate the selection and execution of the best overall plan for the project being considered. An application example is analyzed to illustrate the use of the model demonstrate its new capabilities in optimizing the planning and scheduling of repetitive construction projects.     

Automated Generation of Operations Level Construction Animations in Outdoor Augmented Reality

Three-dimensional (3D) visualization is an effective tool for communicating, verifying, and validating the results of a simulated operation. Traditional visualization tools used for this purpose are typically based on the paradigm of virtual reality. Augmented reality (AR) is a relatively newer visualization paradigm whose engineering applications have been explored by a limited number of researchers. In this paper, the problem of generating smooth and continuous AR animations from the results of running discrete event simulation models and a general purpose methodology to overcome this challenge are discussed. The structure of an AR animation authoring language developed by the writers to create a logical link between a running simulation model and its corresponding 3D visualization in AR is described. In order to validate the functionality and effectiveness of the designed methods and animation language, an AR-based visualization application was developed and the designed algorithms were successfully tested using different simulation scenarios of varying visual and operational complexity.     

Flexible Model for Time/Cost Tradeoff Problem

This paper presents a flexible mixed integer-programming model for the solution of the time/cost tradeoff problem encountered in project management. Whereas it is commonly assumed that the time/cost function is linear, the model presented in this paper makes minimal assumptions and accommodates any type of cost function that is linear, piecewise linear or discrete. The model can be used for answering various “what if” questions that may be very helpful to a project manager in making rational decisions. The basic model minimizes the total cost which is the sum of direct and indirect costs, subject to a project deadline constraint. A simple modification in the model changes the focus from minimizing total cost to minimizing project completion time subject to a resource constraint. The models of this paper can be set up and run very easily on commercially available optimization packages with an integer-programming module. These models provide a viable alternative to more specialized algorithms developed for the time/cost tradeoff problem simply because a typical project manager may not have the necessary skills or resources to implement specialized algorithms.