Lean Management Model for Construction of High-Rise Apartment Buildings

Execution of the finishing works in high-rise apartment buildings is made complex by the need to customize apartments to the varying requirements and designs of individual clients. The conventional construction planning practice of progressing upward from floor to floor breaks down in the face of the arbitrary sequence in which clients finalize their decisions. The results are long cycle times for delivery of completed apartments and corollary high levels of work in progress, budget and schedule overruns, and general dissatisfaction with the process on the part of the developer, contractor, subcontractors, and the clients. Application of lean construction principles to this problem has led to development of a management model that adopts pull scheduling, reduced batch sizes, and a degree of multiskilling. The main benefits expected are an enhanced ability to provide customized apartments, improved cash flow, and reduced apartment delivery cycle times. The model was first formulated in theory, then tested using a management simulation game and computer simulation, and subsequently, developed for practical application. This paper presents an analysis of conventional practice, the theoretical background to the lean approach, and the specific management changes proposed.     

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.     

Height and Construction Costs of Residential High-Rise Buildings in Shanghai

A widely recognized theme of construction economics suggests that the cost of construction per square meter increases as building height rises. However, over a number of years, research conducted regarding the height and cost issue has established a classic relationship between the two factors which can be represented by a U-shaped curve. This paper describes the study of the height-cost relationship of high-rise residential buildings in Shanghai in terms of the total construction cost and elemental costs while considering the context and commonality of buildings. This research was developed as an extension of the previous work, which examined data for buildings in Hong Kong. Initial findings indicate that the curves illustrating the relationships between height and cost of residential buildings in Shanghai and Hong Kong exhibit different profiles. The dissimilarities indicate that different sets of criteria should be applied in the judgment of height that affects cost in different locations. In terms of elemental costs, the findings suggest that there are differences in the way these costs react to changes in the building height.     

Feasibility Study of Rotorcraft Fire Fighting for High-Rise Buildings

Fire risk in high-rise buildings is of special concern to the fire community, since it is crucial but still technically extremely challenging to significantly improve the current fire fighting capabilities when a calamity happens above the “seven story limit.” In fact, at the moment, there is a lack of effective means for fire fighting in this rare but potentially deadly and costly accidents. To address this problem, in this work we provide a preliminary exploration of a new concept for fire suppression: the use of rotorcraft vehicles for aerial fire fighting in high-rise buildings. If available, such system could effectively support fire fighting efforts conducted with conventional means; moreover, it could provide for one of the very few alternatives to classic systems in certain critical cases such as postearthquake fires. At first, we analyze the operative context with the help of a few reference realistic scenarios which allow for the estimation of some key physical parameters. Next, we evaluate two alternative fire extinguishing technologies, and we identify in the water impulse cannon the solution which seems to be the most effective and compatible with the use on-board a rotorcraft for the scopes considered in this work. The analysis leads us to the identification of a target vehicle as a possible candidate platform for the development of a fire fighting helicopter. Finally, we propose a preliminary design of the fire fighting kit, and we evaluate the handling qualities of the vehicle during operations with reference to the ADS-33 normative.     

Probabilistic Forecasting of Project Duration Using Bayesian Inference and the Beta Distribution

Reliable forecasting is instrumental in successful project management. In order to ensure the successful completion of a project, the project manager constantly monitors actual performance and updates the current predictions of project duration and cost at completion. This study introduces a new probabilistic forecasting method for schedule performance control and risk management of on-going projects. The Bayesian betaS-curve method (BBM) is based on Bayesian inference and the beta distribution. The BBM provides confidence bounds on predictions, which can be used to determine the range of potential outcomes and the probability of success. Furthermore, it can be applied from the outset of a project by integrating prior performance information (i.e., the original estimate of project duration) with observations of new actual performance. A comparative study reveals that the BBM provides, early in the project, much more accurate forecasts than the earned value method or the earned schedule method and as accurate forecasts as the critical path method without analyzing activity-level technical data.     

Probabilistic Forecasting of Project Duration Using Kalman Filter and the Earned Value Method

The earned value method (EVM) is recognized as a viable method for evaluating and forecasting project cost performance. However, its application to schedule performance forecasting has been limited due to poor accuracy in predicting project durations. Recently, several EVM-based schedule forecasting methods were introduced. However, these are still deterministic and have large prediction errors early in the project due to small sample size. In this paper, a new forecasting method is developed based on Kalman filter and the earned schedule method. The Kalman filter forecasting method (KFFM) provides probabilistic predictions of project duration at completion and can be used from the beginning of a project without significant loss of accuracy. KFFM has been programmed in an add-in for Microsoft Excel and it can be implemented on all kinds of projects monitored by EVM or any other S-curve approach. Applications on two real projects are presented here to demonstrate the advantages of KFFM in extracting additional information from data about the status, trend, and future project schedule performance and associated risks.     

Proposed Fire Safety Ranking System EB-FSRS for Existing High-Rise Nonresidential Buildings in Hong Kong

A Fire Safety Ranking System (EB-FSRS) is proposed for assessing the fire safety provisions in existing high-rise nonresidential buildings in Hong Kong. The objective is to investigate how far the fire safety provisions in those existing buildings deviate from the expectation of new codes. Suitable fire safety management can then be worked out in the transition period, based on the scores. Local fire codes were reviewed first to decide what should be the attributes and their weightings. From the reviewing results, three groups of attributes were proposed in the EB-FSRS. These are the passive building construction, active fire protection systems (fire services installation), and key risk parameters, all following the local fire safety requirements. The concept is similar to those equivalent concepts on fire safety parameters of the National Fire Protection Association–Fire Safety Evaluation System (NFPA-FSES). But the EB-FSRS is not a “trade-off” exercise. Thirty-seven old high-rise buildings were rated by studying their architectural features, interior details, and fire safety provisions. Scores under EB-FSES and NFPA-FSES are also compared.     

LEAPCON: Simulation of Lean Construction of High-Rise Apartment Buildings

A lean model has been proposed for the construction management of high-rise apartment buildings with customized apartment designs. It incorporates a number of changes to traditional management practice, including single-piece flow with pull scheduling, work restructuring, and multiskilling. A simulated construction process scenario was devised for experimental evaluation of the model. The simulation was first implemented as a live management game, in which participants played the roles of the clients, general contractor, and subcontractors. Eleven runs with different teams indicated that the lean model increased throughput, improved cash flow, and reduced apartment delivery cycle time. However, the limitations of the live simulation led the writers to implement a discrete event computer simulation of the same process. The computer simulation reinforced the findings of the live simulation and emphasized the specific beneficial effect of single-piece flow under pull scheduling. The lean model may be of immediate interest to construction planners and managers because it enables full customization with minimal waste and no additional resources. The demonstrative clarity of the lean model simulation, both live and computerized, makes it a powerful tool for education and research.     

Probabilistic Control of Project Performance Using Control Limit Curves

This study introduces a new probabilistic project control concept to assure an acceptable forecast of final project performance, in terms of not exceeding planned budget and schedule risk levels. This concept consists in the implementation of performance control limit curves for both actual cost and elapsed time, obtained with a probabilistic approach and a graphical representation referred to as Stochastic S curves (SS curves). In order to facilitate the project control process, control limit curves can be used to display and evaluate actual project performance status without the need of actualizing at completion performance forecasts. Three different approaches (quality, benchmarking, and incremental variance) are proposed in this paper for obtaining the project performance control limit curves. In order to find the control limit curve definition with more conservative acceptable performance variations, these approaches are tested in an example project. A further managerial advantage is found in the recommended approach, as it allows monitoring the use of both cost and scheduling contingencies, along the project execution.     

RFID+4D CAD for Progress Management of Structural Steel Works in High-Rise Buildings

This research presents a strategy and information system to manage the logistics and progress control of structural steel works under the integrated environment of radio frequency identification and four-dimensional computer-aided design (4D CAD). Considering the characteristics of the manufacturing and erection processes of structural steel works in high-rise building construction from a practical point of view, this research has developed a strategy to support successful application of these two state-of-the-art technologies and has developed an information system to support the logistics and progress management based on this strategy. The results of this research have been validated and verified through real-world applications in two high-rise building construction projects considering realistic constraints. Time study has been conducted to verify the efficiency of the proposed information system. In addition, lessons learned and issues identified through these real-world applications are described and discussed in this paper.     

Describing a Beta Probability Distribution Function for Construction Simulation

A typical proposed application for a construction simulation model is to assess the productivity of a future operation. This type of application inherently presents the modeler with a situation where there is only a limited amount of data available for choosing an underlying probability distribution function (PDF). This paper presents a formulation for developing a Beta PDF for use in construction simulation modeling. The hypothesis of this paper is that there is a ratio that relates the 75th percentile to the mode of the activity duration. The research demonstrates that using such ratios, along with the minimum, mode, and maximum activity durations, results in estimates of a beta PDF that accurately describes the underlying duration distribution of construction activities. In the methodology proposed here the minimum and maximum activity durations are predicted using deterministic methods based on the physical characteristics of the job and equipment employed. The beta-shaped parameters a and b are estimated using a procedure for fitting beta distributions to activity times when sample data are not available.     

Empire State Building Project: Archetype of “Mass Construction”

Analysis of historical projects, with the dual benefits of hindsight and modern concepts of construction systems, can help fill the gaps in our theoretical understanding of production in construction, which have increasingly been identified as a barrier to progress in improving construction project management. The richness of the historical record describing construction of the Empire State Building provides a unique opportunity to analyze and compare it with the paradigms of craft, industrialized, and lean construction. Its size and its record rate of construction, which has not been broken since for tall buildings, make it of prime interest. The project progress was reconstructed using line-of-balance software and its different flows were assessed. The results lead to the conclusion that it is an archetypal example of what we propose be called “mass construction.” This enables a richer understanding of the taxonomy of production systems in construction, and should aid theoreticians and practitioners alike to devise better production systems for construction projects.     

Labor Performance Analysis for Microtunneling Projects

Microtunneling projects have special process characteristics. The production time of microtunneling projects is needed for project estimating and scheduling. The production time has three basic components: (1) preparation times for pipe segments; (2) preparation times; and (3) delay times. Real project data were collected from 35 projects to predict the time needed for pipe segment preparation. A probabilistic distribution technique was used to predict the preparation times for pipe segments. Various numbers of probabilistic distributions were tested against the data. A log-logistic distribution was selected to represent the preparation time’s probability for a pipe in microtunneling projects. Preparation times for high, medium, and low performance contractors were predicted. By enhancing the estimation process of the microtunneling projects, contractors can use this paper in predicting the preparation time for pipe segments, which represents the crew (or crew’s) productivity.     

Considerations of Multimode Structural Response for Near-Field Earthquakes

This paper presents an investigation of multimode effects of tall buildings idealized as a continuous shear-beam model subjected to near-field pulse-like ground motion. The investigation is based on three analytical approaches: a damped wave solution approach, a fundamental-mode approach, and a modal summation approach. In the modal summation approach, all modal damping ratios are assumed to be equal and a set of Green’s functions for the shear strain response is explicitly derived. The multimode effects on the base-level shear strain/force demands are compared by using an effective response spectrum for shear-beam systems. The study results show that the occurrence of major spectral differences is conditioned on the ratio of the fundamental structural period to the duration of the predominant excitation pulse. Seismic analyses for a set of recorded near-field earthquake data indicate a strong correlation between the characteristics of effective response spectra and the ground pulse parameters.     

Implications of Even Flow Production Methodology for U.S. Housing Industry

Production building in the residential sector is often described as the portion of the construction industry that is most like the manufacturing sector. In modern tract construction in the United States, a small number of models are generally repeated several times in a relatively confined area, using specialized trade contractors to complete each phase of each home. Management of the handoffs between predecessor and successor trade contractors is therefore a critical component in the successful completion of a residential project. In order to bring more reliable planning to this process, a workflow-leveling strategy known as even flow production has come into use in the industry in recent years. Even flow production is a strategy intended to reduce the variability in the workflow for trade contractors in the process, thereby gaining production efficiencies. In practice, different operational definitions are in use. This paper describes a series of simulation experiments to identify the management implications of two common strategies (activity-based versus start-based). A special-purpose simulation template was built for the Simphony environment for this purpose. The pace chosen for the flow of activities was found to significantly affect the speed at which the subdivision was completed. The even flow strategy was found to affect the subdivision completion time only slightly, but to have a significant impact on workflow variability and management effort. Control of the pace of starts of only the first activity exhibited nearly the same degree of variability as if the pace of starts were matched to a sales pace.     

Simulation-Based Schedule Estimation Model for ACS-Based Core Wall Construction of High-Rise Building

Many existing studies about construction schedule management focus on the planning phase of a project, particularly on schedule estimation based on the labor resources involved in the project. However, equipment resources, which are another crucial factor in the productivity of a construction project, have not been considered in existing research. Therefore, this study aimed to develop a schedule estimation model considering both labor and equipment resources. For the purpose of this study, core wall construction was selected because it is a very important construction activity in terms of schedule estimation for high-rise building construction. To develop a schedule estimation model for core wall construction, an in-depth case study was conducted. On the basis of the results of the case study, a simulation model was developed using the CYCLONE method. Finally, by using the results of the simulation, a schedule estimation model for core wall construction was developed by conducting multiple-regression analysis. By using the developed model, a project manager can easily, quickly, and accurately perform schedule estimation when there are problems that may cause construction schedule delays during the construction phase.     

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.     

Probabilistic Approach for Budgeting in Portfolio of Projects

This paper presents a mathematical model for calculating the budgetary impact of increasing the required confidence level in a probabilistic risk assessment for a portfolio of projects. The model provides a rational approach for establishing a probabilistic budget for an individual project in such a way that the budget for a portfolio of projects will meet a required confidence level. The use of probabilistic risk assessment in major infrastructure projects is increasing to cope with major cost overruns and schedule delays. The outcome of the probabilistic risk assessment is often a distribution for project costs. The question is at what level of confidence (i.e., the probability that budget would be sufficient given the cost distribution) should be used for establishing the budget. The proposed method looks at a portfolio of such projects being funded by the same owner. The owner can establish a target probability with respect to its annual budget. The model can help the owner establish confidence level for individual projects and also examine the effect of changing the confidence level of the portfolio budget on the budget and the confidence level of individual projects. The paper is relevant to practitioners because it provides a methodology for establishing confidence levels by the owner agencies in the emerging field of cost risk assessment for infrastructure projects. A numerical example is provided using actual transit project data to demonstrate the model application.     

Multiple Simulation Analysis for Probabilistic Cost and Schedule Integration

One of the major goals of the construction industry today is the quantification and minimization of the risk associated with construction engineering performance. When specifically considering the planning of construction projects, one way to control risk is through the development of reliable project cost estimates and schedules. Two techniques available for achieving this goal are range estimating and probabilistic scheduling. This paper looks at the integration of these techniques as a means of further controlling the risk inherent in the undertaking of construction projects. Least-squares linear regression is first considered as a means of relating the data obtained from the application of these techniques. However, because of various limitations, the application of linear regression was not considered the most appropriate means of relating the results of range estimating and probabilistic scheduling. Integration of these techniques was, therefore, achieved through the development of a new procedure called the multiple simulation analysis technique. This new procedure combines the results of range estimating and probabilistic scheduling in order to quantify the relationship existing between them. Having the ability to accurately quantify this relationship enables the selection of high percentile level values for the project cost estimate and schedule simultaneously.     

Integrating Neurofuzzy System with Conceptual Cost Estimation to Discover Cost-Related Knowledge from Residential Construction Projects

Cost estimation during early stage of a building construction project plays an important role for feasibility analysis in the planning and design phase. Traditional knowledge-based approaches suffer an essential difficulty due to resource price fluctuation in the market. This paper presents a hybrid method that integrates the principal items ratio estimation method with the adaptive neurofuzzy inference system for mining of cost estimation data. The proposed method provides exceptional capability for mining estimation knowledge that is difficult to be discovered by traditional knowledge-based approaches. A case study of residential building projects in China is conducted to demonstrate the proposed method. The testing results show that the proposed method does not only achieve high estimation accuracy, but also provide desirable features for estimators, such as explicit fuzzy decision rules and graphical presentations.