Impact of Change Orders on Small Labor-Intensive Projects

In today’s construction, small projects can be just as important if not more important than the larger projects. However, small projects are usually fast track projects, which often involve overlapping design and construction time. Subsequent modifications may be required for the sections that are already under construction. These disruptions to the ongoing project are labeled as change orders. The impact due to changes has been described as the adverse effect upon the unchanged work due to changes in the contract. For this study, 34 projects were selected to develop a statistical model that estimates the amount of labor efficiency lost due to change orders for small projects. The variables in the final model are percent design related changes, percent owner initiated changes, the ratio of actual peak labor to estimated peak labor, the ratio of actual project duration to estimated project duration, and project manager’s percent time on the project. The results of this paper are of value to owners, electrical and mechanical contractors, and construction managers. The model quantifies the impact of change orders by introducing the most important variables that bring the largest disruptions.     

Impact of Overmanning on Mechanical and Sheet Metal Labor Productivity

This paper details the impacts of overmanning on labor productivity for labor-intensive trades, namely mechanical and sheet metal contractors. Overmanning, as used in the following research, is defined as an increase of the peak number of workers of the same trade over the actual average manpower used throughout the project. The paper begins by reviewing literature on the effects of overmanning on labor productivity. Via a survey to various contractors, data were collected from 54 mechanical and sheet metal projects located across the United States. Various statistical analysis techniques are then performed to determine quantitative relationship between overmanning and labor productivity. These techniques include the stepwise method, T-test, P-value tests, analysis of variance, and multiple regression analysis. The results indicate a 0–41% loss of productivity depending on the level of overmanning and the peak project manpower. Cross-validation is performed to validate the final model. Finally, a case study is provided to demonstrate the application of the model.     

Estimating Project S-Curves Using Polynomial Function and Neural Networks

The S-curve is a graphical representation of a construction project’s cumulative progress from start to finish. While S-curves for project control during construction should be estimated analytically based on a schedule of activity times, empirical estimation methods using various mathematical S-curve formulas have been developed for initial planning at predesign stages, with the mean for past similar projects often used as the basis of prediction. In an attempt to make an improvement, a succinct cubic polynomial function for generalizing S-curves is proposed and a comparison with existing formulas shows its advantages of accuracy and simplicity. Based on an analysis of the attributes and actual progress of 101 projects, four factors, i.e., contract amount, duration, type of work, and location, are then used as the inputs of a model developed for estimating S-curves as represented by the polynomial parameters. For model development, it is proposed to use neural networks for their ability to perform complex nonlinear mapping. The neural network model is compared with statistical models with respect to modeling and testing accuracy. The results show that the presented methodology can achieve error reduction consistently, thereby being potentially useful for owners and contractors in early financial planning and checking schedule-based estimates.     

One Company's Experience with Design∕Build: Labor Cost Risk and Profit Potential

This paper offers the data from one construction company's experiences with design∕build. Specifically, the paper presents an analysis of the company's labor cost risk based on a case study of two similar projects. One project was a typical design∕bid∕build job and the other was a design∕build job. The design∕build project experienced consistently greater fluctuations in the labor cost. These fluctuations seem to indicate that it is very difficult to accurately estimate labor costs for design∕build projects, thus adding to the risk of such projects. The second half of the paper presents an account of this same company's overall profit experience with design∕build work. Profit margins were analyzed using three categories—design∕build versus non-design∕build, client-specific design∕build, and design∕build construction types. The design∕build projects' average profit margin was 3.5 percentage points greater than that for the non-design∕build work.     

Probabilistic Monitoring of Project Performance Using SS-Curves

The purpose of this study was to develop a new concept of project control. This new concept uses stochastic S-curves (SS-Curves) as an alternative to using the deterministic S-curve technique commonly employed in professional practice. SS-curves are developed by determining the activity level variability in cost and duration. Simulation is the recommended approach for obtaining SS-curves, similar to the way that stochastic schedules are currently developed. SS-curves provide probability distributions for expected cost and duration for a given percentage of work completed. Monitoring project performance is performed by comparing the most likely budget and duration values, obtained from respective probability distributions for actual progress, with the project's actual data and cumulative cost. By using this method, an evaluation of actual project performance can be developed that appropriately considers the natural variability of construction costs and duration, rather than utilizing only one possible deterministic outcome. Given the probabilistic characteristics of SS-curves, additional benefits are presented that enable a more comprehensive project control methodology.     

Using Benchmarks and Metrics to Evaluate Project Delivery of Environmental Restoration Programs

The United States is in the middle of a large environmental restoration effort that is hampered by a lack of knowledge on how to measure the performance of the project delivery process. This study evaluates one environmental restoration program’s ability to deliver projects: the Environmental Management Program (EMP), a federally sponsored program managed by the U.S. Army Corps of Engineers. Project performance metrics are compiled and used to measure two types of program improvements made in project delivery: trend improvements over time, and the ability to reach established benchmarks. The benchmarks come from both agency guidance and construction industry benchmarks. The metrics measure the program’s ability to accurately estimate the required resources (time and money) to accomplish the project, estimate the cost to operate and maintain the project, and meet the customers’ design requirements. To build the metrics, estimates from the project planning documents are compared against the actual results. Currently, the Corps of Engineers has established some benchmarks and does evaluate projects for design success, but the benchmarks do not include all aspects of project delivery and are not universally applied. Analysis of the metrics shows that the Corps has made improvements in the delivery of projects, but some major components of the process should be improved. Establishing benchmarks would provide the Corps with information to improve the project delivery of the EMP and other environmental restoration programs across the country. This study provides an example of applying business principles to a governmental program.     

Quantitative Definition of Projects Impacted by Change Orders

Change, defined as any event that results in a modification of the original scope, execution time, or cost of work, is inevitable on most construction projects due to the uniqueness of each project and the limited resources of time and money available for planning. Change may occur on a project for a number of reasons, such as design errors, design changes, additions to the scope, or unknown conditions. For each change, contractors are entitled to an equitable adjustment to the base contract price and schedule for all productivity impacts associated with the change. Changes may or may not have an impact on labor productivity. Existing literature uses subjective evaluation to determine whether the project is impacted. Projects impacted by change cause the contractor to achieve a lower productivity level than planned. The focus of this paper is to quantify whether an electrical or mechanical project is impacted by a change order. Through statistical hypothesis testing, groups of factors that correlate with whether a project is impacted by change orders were identified and used to develop a quantitative definition of impact. Logistic regression techniques were used to develop models that predict the probability of a project being impacted. The results of this research show that percent change, type of trade, estimated and actual peak manpower, processing time of change, overtime, overmanning, and percent change related to design issues are the main factors contributing to the project impact.     

Ontology for Relating Risk and Vulnerability to Cost Overrun in International Projects

Risk management is about identifying risks, assessing their impacts, and developing mitigation strategies to ensure project success. The difference between the expected and actual project outcomes is usually attributed to risk events and how they are managed throughout the project. Although there are several reference frameworks that explain how risks can be managed in construction projects, a major bottleneck is the lack of a common vocabulary for risk-related concepts. Poor definition of risk and patterns of risk propagation in a project decrease the reliability of risk models that are constructed to simulate project outcomes under different risk occurrence scenarios. This study aims to extend previous studies in risk management by presenting an ontology for relating risk-related concepts to cost overrun. The major idea is that cost overrun depends on causal relations between various risk sources (namely, risk paths) and sources of vulnerability that interfere with these paths. Ontology is used to develop a database system that represents risk event histories of international construction projects and to construct a model for estimation of cost overrun. It will form the basis of a multiagent system that can be used to simulate the negotiation process among project participants about sharing of costs considering the risk allocation clauses in the contract, sources of vulnerability, and causal relations between risk events and their impacts. The ontology is constructed by interaction with Turkish contractors working in international markets and extensive literature review on risk-related concepts. The validation test results provide evidence that the ontology is fairly effective to help Turkish contractors to assess cost overrun by considering sources of vulnerability and risk in international construction projects.     

Impact of Change Orders on Labor Efficiency for Electrical Construction

Change orders are a source of many disputes in today's construction industry. The issue at hand is whether or not the execution of change orders work has a negative impact on overall labor efficiency on a construction project. Previous literature demonstrates evidence that change orders affect labor efficiency. Attempts have been made to quantify these impacts by many researchers, with limited success. Using the electrical construction industry, a research study has been conducted to quantify the impacts of change orders on labor efficiency. In this paper, results of hypothesis testing and regression analysis are presented. A linear regression model that estimates the loss of efficiency, based on a number of independent variables, is also presented. The independent variables used in this model are (1) qualitative and quantitative criteria used to determine whether projects are impacted by changes or not; (2) the estimate of change order hours for the project as a percentage of the original estimate of work hours; (3) the estimate of change order hours for the project; and (4) the total number of years that the project manager had worked in the construction industry. Additional projects were used to validate the model, with an average error rate of 5%. The results of this research study are useful for owners, construction managers, general contractors, and electrical specialty contractors, because they provide a means to estimate the impact of a change order under certain project conditions. This research also identifies factors, which, when understood and effectively managed, may be used to mitigate the impact of a change order on project costs and efficiency.     

Relationship between Automation and Integration of Construction Information Systems and Labor Productivity

Information technology (IT) has been used to increase automation and integration of information systems on construction projects for over two decades. However, evidence that overall costs have been reduced or project performance has been improved with IT in construction is limited and mostly focused on application specific studies. A comprehensive understanding of the relationship between IT and project performance helps industry practitioners better understand the likely outcomes of implementation of IT application and likewise benefits researchers in improving the effectiveness in their IT development efforts. An opportunity to examine new evidence exists with the emergence of the Construction Industry Institute’s Benchmarking and Metrics database on construction productivity and practices. This article presents an analysis of that data to determine if there is a relationship between labor productivity and level of IT implementation and integration. Data from industrial construction projects are used to measure the relationships between the automation and integration of construction information systems with productivity. Using the independent sample t-test, the relationship was examined between jobsite productivity across four trades (concrete, structural steel, electrical, and piping) and the automation and integration of various work functions on the sampled projects. The results showed that construction labor productivity was positively related to the use of automation and integration on the sampled projects.     

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.     

Role of Inventory Buffers in Construction Labor Performance

Buffers of material stockpile (inventory) are formed at the work level in construction to help manage production. The size of material stockpiles often has an important bearing on construction project performance. In construction projects, where conditions are often uncertain and variable, some have suggested that buffers be sized and located according to the conditions. New management thinking like lean construction and theory of constraints suggests that the size of buffers needs to be managed carefully, because when oversized, buffers are wasteful, impede workflow, and hinder performance. Research has shown that project variability can be affected with the careful deployment of buffers but has not really evaluated the impact on construction labor performance. This paper reports an exploratory analysis of the relationship between inventory (buffers) and construction labor performance with data collected from three commercial projects in Brazil. In this study, the size of the buffer between rebar fabrication and installation in the construction of a structural system is compared to the labor performance of the fabrication and installation crews. The results show that some buffer helps achieve the best labor performance in the construction operations studied.     

Physical Risk Factors and Controls for Musculoskeletal Disorders in Construction Trades

Adoption of the Washington State Ergonomics Rule in 2000 initiated seven different demonstration projects in nine high-risk construction trades. The Ergonomics Rule was repealed in 2003, however valuable cooperative field research was conducted in construction prior to rule dissolution. This paper presents summaries and results of each project with the aim of providing the results to construction professionals and researchers seeking to identify and reduce injury risks and building costs. The projects were organized independently but each with the specific aims of conducting work in conjunction with industry, identifying “hazard zone” risk factors as defined by the rule, and identifying feasible solutions in agreement with company partners to mitigate these risk factors. Musculoskeletal injury risk factors were evaluated by ergonomist field observation and working group analysis. Solutions were developed through field work and consensus agreement with industry and labor representatives. Identified injury risk factors and technically feasible interventions are presented for the following trades: Roofing, residential framing, residential carpet and floor installation, commercial carpentry, commercial laborers, commercial concrete reinforcement, commercial concrete finishing, drywalling, and masonry.     

Impact of Change Orders on Labor Efficiency for Mechanical Construction

Change orders have become an everyday occurrence in construction. It is widely accepted by both owners and contractors that change orders have an effect on the labor efficiency, but these effects are difficult to quantify and frequently lead to disputes. Data from 61 mechanical construction projects were collected to develop a statistical model that estimates the actual amount of labor efficiency lost due to the change orders. The input variables needed in the model are as follows: (1) The original estimated labor hours; (2) impact classification; (3) total estimated change hours; (4) number of change orders; and (5) the timing of changes. The results of this study show that impacted projects have a larger decrease in labor efficiency than unimpacted projects. Additionally, the later a change order occurs in the life of a project the more impact it will have on the labor efficiency. The results appear to be consistent with the intuition of experienced professionals. Although each project has unique characteristics, the resultant model provides owners and contractors with a baseline measure of lost labor efficiency.     

Developing a Traffic Closure Integrated Linear Schedule for Highway Rehabilitation Projects

In recent years, the state departments of transportation have implemented a number of highway rehabilitation projects across the country. These projects differ fundamentally from new highway projects in that they require an uninterrupted flow of traffic throughout both the duration and geometric length of the project. Synchronization of traffic closure with the construction activities is crucial in such projects to avoid the traffic conflicts and prevent idle time for equipment and labor. Although most highway rehabilitation projects involve predominantly linear activities, the techniques of linear scheduling are not readily applicable to highway rehabilitation projects due to the conflict between the workzone and traffic flow. This paper documents the development of a traffic closure integrated linear schedule (TCILS) that addresses both traffic closure and work progress issues. The TCILS generates a single schedule for both the construction activities and the associated traffic closures. Visual and graphical features are also applied in the system, which makes it particularly applicable for highway rehabilitation projects. An actual concrete pavement rehabilitation project using the TCILS is presented as a sample of application. The findings from the sample project, although they are limited, show that the TCILS can be applied to an actual project. With recommended future development, the system is believed to be beneficial for both construction practitioners and academics.     

Optimizing Cash Flows for Linear Schedules Modeled with Singularity Functions by Simulated Annealing

The ability of construction contractors to plan and manage cash flow is critical for their economic success. The cumulative interaction of outflows (labor, materials, and equipment costs) and inflows (progress payments less retainage) creates a profile with a complex zigzag shape. This could only be modeled by simplification, e.g., as values tabulated at discrete times; averaged S-curves without peaks; or envelopes of all possible constellations. Neither is suited for a fully integrated model that dynamically links schedules with their cash flows for optimization. Therefore, singularity functions, whose components define ranges of behavior between cutoffs, are used to flexibly yet accurately model cash flow profiles and their various payment terms. The new approach augments construction project management toward an integrated planning model and is validated with an example from the literature. Optimization with a simulated annealing algorithm shifts activity positions in a randomized but directed search for maximizing profits.     

“Lean” Comparison Using Process Charts of Complex Seismic Retrofit Projects

This paper compares the delivery of two retrofit projects where seismic isolation bearings were installed. The comparison is retrospective. The design teams on these projects did not implement “lean” thinking to develop their approach, nevertheless, observed process differences are characterized using a “lean” process evaluation and optimization tool, and then gauged and rationalized from that perspective. Cross-functional process charts identify functional parties with interrelated material or information handoffs. They help to identify (un)necessary steps or complexity as measured by number of handoffs and interacting parties. Analysis of these charts shows that project value may stem from the owner integrating design development with product procurement and construction method selection. On one project, integration was made possible by structural engineers evaluating the impacts of product procurement on overall project performance, expert consultants providing construction process reviews, and experienced contractors participating in installation sequence development. This paper illustrates the value of developing a symbiotic relationship between designers and suppliers in a niche market. It stresses the need for work structuring early on in the delivery process, integrating process with product development, to improve project delivery.     

Statistical Analysis on the Cost and Duration of Public Building Projects

A probabilistic model is proposed to predict the risk effects on time and cost of public building projects. The research goal is to utilize a real history data in estimating project cost and duration. The model results can be used to adjust floats and budgets of the planning schedule before project commencement. Statistical regression models and sample tests are developed using real data of 113 public projects. The model outputs can be used by project managers in the planning phase to validate the schedule critical path time and project budget. The comparison of means analysis for project cost and time performance indicated that the sample projects tend to finish over budget and almost on schedule. Regression models were developed to model project cost and time. The regression analysis showed that the project budgeted cost and planned project duration provide a good basis for estimating the cost and duration. The regression model results were validated by estimating the prediction error in percent and through conducting out-of-sample tests. In conclusion, the models were validated at a probability of 95%, at which the proposed models predict the project cost and duration at an error margin of ±0.035% of the actual cost and time.     

NPV-at-Risk Method in Infrastructure Project Investment Evaluation

Strategic capital investment decisions are crucial to a business firm. The decision to invest in privately financed infrastructure projects requires careful consideration, because they are exposed to high levels of financial, political, and market risks. The project appraisal methods should incorporate analysis of these risks. A number of capital-investment decision methods can take risks into account, but each of them focuses on different factors and has its limitations. Thus, a more vigorous method is needed. A systematic classification of existing evaluation methods shows that it is possible to develop a new method—the net-present-value-at-risk (NPV-at-risk) method—by combining the weighted average cost of capital and dual risk-return methods. The evaluation of two hypothetical power projects shows that the NPV-at-risk method can provide a better decision for risk evaluation of, and investment in, privately financed infrastructure projects.     

工程项目管理中的成本管理

工程项目成本管理是为保障项目实际发生的成本不超过项目预算而开展的项目资源计划、项目成本估算、项目预算编制和项目预算控制等方面的管理活动。是保证施工企业正常经营的重要的基础管理工作。