Baseline Determination in Construction Labor Productivity-Loss Claims

Various ways of quantifying damages have been applied to productivity loss claims in construction. All of the ways attempt to be as objective as possible based on the extent of information available in a particular case. The measured mile, a widely accepted method, is employed when an unimpacted baseline period of production can be identified. Although that approach is considered to be the most objective method available in such cases, the method is limited and does not directly account for variation in individual productivity values about a normal or natural level of productivity. A gap exists between the use of existing methods and the availability of an appropriate methodology that specifically addresses variation in productivity. The key lies in the way baseline productivity is measured, which is inherently statistical, yet no truly statistical methods are used to establish such a baseline. Using the measured mile as a backdrop, this article provides an objective, measurement-based approach that can be used to establish a productivity baseline applied to construction productivity loss claims, based on the application of statistical methods aided by a process control chart. The focus is on providing the basic principles and concepts underlying the approach presented.     

Quantification of Losses of Labor Efficiencies: Innovations in and Improvements to the Measured Mile

This paper describes a rigorous procedure for quantifying damages arising from loss of labor inefficiency. Throughout, deficiencies with the measured mile concept are cited. Perhaps one of the least recognized deficiencies is that the measured mile is a concept, not a procedure. Thus, every analyst is left to conduct the study as he/she pleases. This paper defines a step-by-step process for doing a damage study, and cites rules to follow when performing the study. Following the procedure and rules will lead to more rigorous and defensible analyses. A baseline analysis is described and presented as a way of adhering to the measured mile concept. The principle difference is in how best performance is defined. In a baseline study, the focus is on periods of high output (production), not good productivity. The baseline periods need not be continuous. Also, the analysis is performed on combined data (one account), not many accounts. The calculations used to perform a baseline study are illustrated using a simple case study project. Reasons for recovering damages because of losses of labor efficiency are also cited.     

Case Law and Variations in Cumulative Impact Productivity Claims

Proving and quantifying lost productivity due to cumulative impacts of multiple changes are difficult tasks. This paper presents the most acceptable methods from case law and demonstrates their applications for analyzing the loss of productivity. These methods include earned value analysis, measured mile analysis, and combinations of these two. They are either well established or drawn from recent court and board decisions. A case study is used to illustrate and compare the use of these methods. These methods result in considerably different loss of productivity values though the actual amount (i.e., inefficiency in labor hours) is unique for a particular case and though these methods are often thought to be similar or even the same. How a measured mile analysis and its variants are employed affects the amount of lost productivity estimated. The variants can avoid some drawbacks of measured mile and earned value studies. Nevertheless, which method is more accurate and reliable is difficult to provide for a particular claim. Practitioners should choose between them based on the availability of project records and the nature of changes and cumulative impacts. Practitioners may also employ two or more methods to perform a “sensitivity analysis” of the chosen methods and persuade the other party and/or the jury that their estimate of lost productivity is sufficiently certain.     

Using Bargaining-Game Theory for Negotiating Concession Period for BOT-Type Contract

This paper extends the build-operate-transfer (BOT) concession model (BOTCcM) to a new method for identifying a concession period by using bargaining-game theory. Concession period is one of the most important decision variables in arranging a BOT-type contract, and there are few methodologies available for helping to determine the value of this variable. The BOTCcM presents an alternative method by which a group of concession period solutions are produced. Nevertheless, a typical weakness in using BOTCcM is that the model cannot recommend a specific time span for concessionary. This paper introduces a new method called BOT bargaining concession model (BOTBaC) to enable the identification of a specific concession period, which takes into account the bargaining behavior of the two parties concerned in engaging a BOT contract, namely, the investor and the government concerned. The application of BOTBaC is demonstrated through using an example case.     

Daily Windows Delay Analysis

Critical path method delay analysis techniques are widely applied in the construction industry, with the windows method being regarded as technologically advantageous. The approach looks at different schedule snapshots (windows) throughout the project and analyzes the contractor versus owner responsibility for delaying the critical paths. Accordingly, decisions regarding time and/or cost compensation could be made. While the technique is beneficial, it is computationally intensive and produces different results with different window sizes. Commercial software provide little support in this regard and the analysis is usually done manually. In this paper, a modified windows approach is introduced with computerized daily analysis of delays so that accurate and repeatable results are produced. The new approach is coupled with a new representation of progress information and is readily usable by professionals and researchers to evaluate project delays. Details of the daily analysis are introduced along with two case studies that demonstrate its advantages over the traditional windows approach. A downloadable version is made available for experimental use by researchers and professionals.     

3D/4D CAD Applicability for Life-Cycle Facility Management

A range of studies have shown that three-dimensional (3D)/four-dimensional (4D) computer-aided design (CAD) has positively impacted the productivity and safety of construction processes. However, its potential impact on the entire life cycle of construction projects has not yet been fully investigated. The opinions of construction professionals have generally been reported on the basis of one-time interviews during several case studies. No statistical approach has yet been adopted to examine the whole spectrum of views about 3D/4D CAD use in construction projects. This study presents a comprehensive statistical analysis about how construction engineers perceive the effectiveness of 3D/4D CAD during various tasks of the construction project life cycle. A focus group interview and a review of the literature produced a total of 35?application areas in which 3D/4D CAD can possibly improve existing construction processes. We identified the areas in which 3D/4D CAD has a high potential to significantly enhance project results by using an importance-performance analysis (IPA) and a questionnaire-based survey involving 165?respondents. These study results are expected to provide new business strategies for 3D/4D CAD by broadening its traditional application realm.     

Staircase Model for New Practice Implementation

Implementation of new ideas and new practices are essential for an organization to remain competitive in a changing business environment. The absence of these new ideas will eventually lead to stagnation, but the challenge to organizations remains how to overcome the many barriers that appear during an implementation process and successfully convert these ideas into sustainable practices. Within the capital facility industry, this challenge is amplified based on long-held industry practices, corporate culture, and a necessary focus on minimizing risk. However, even the capital facility industry is being forced to recognize the need to adapt to changing business conditions through the implementation of best practices. Specifically, organizations require an implementation plan that provides enough detail that all parties impacted by the process understand the process (roadmap) that is going to be followed during implementation. This paper introduces the development of the staircase implementation model and how it addresses the need for an implementation roadmap that is applicable to all implementation initiatives. The paper introduces the model components, the proposed application of the model, and the initial testing of the model that led to specific implementation considerations. This paper has significant relevance to industry as it gives a practical introduction to the important focus of implementing new practices.     

Automated Generation of Customized Field Data Collection Templates to Support Information Needs of Cost Estimators

While estimating activity production rates, cost estimators rely on historical production rates. To have realistic and useful cost estimates based on historical production rates, such production rate data should be augmented with historical contextual information that depict conditions under which activity production rates were achieved in past projects. This information is needed in determining which production rate to use among alternates for a similar activity existing in a new bid. Estimators need contextual information especially when they are unfamiliar with the work being estimated. Hence, such information items need to be identified, collected, and stored for estimators’ use in new projects. This paper details a construction-method specific and an extensible approach that is developed for enabling cost estimators to define contextual information items that need to be collected on job sites and stored as part of project histories. Based on this approach, the writers implemented a prototype system, called as ContextGen, and performed user-tests with estimators with different experience levels. Results showed that the developed approach captures method-specific information needs of estimators and is extensible to incorporate new contextual information items that can have different data representations. The developed approach is also precise in retrieving contextual information items specific to a construction method from a set of predefined contextual information items available in a library.     

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.     

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.     

Bayesian Model Updating Using Hybrid Monte Carlo Simulation with Application to Structural Dynamic Models with Many Uncertain Parameters

In recent years, Bayesian model updating techniques based on measured data have been applied to system identification of structures and to structural health monitoring. A fully probabilistic Bayesian model updating approach provides a robust and rigorous framework for these applications due to its ability to characterize modeling uncertainties associated with the underlying structural system and to its exclusive foundation on the probability axioms. The plausibility of each structural model within a set of possible models, given the measured data, is quantified by the joint posterior probability density function of the model parameters. This Bayesian approach requires the evaluation of multidimensional integrals, and this usually cannot be done analytically. Recently, some Markov chain Monte Carlo simulation methods have been developed to solve the Bayesian model updating problem. However, in general, the efficiency of these proposed approaches is adversely affected by the dimension of the model parameter space. In this paper, the Hybrid Monte Carlo method is investigated (also known as Hamiltonian Markov chain method), and we show how it can be used to solve higher-dimensional Bayesian model updating problems. Practical issues for the feasibility of the Hybrid Monte Carlo method to such problems are addressed, and improvements are proposed to make it more effective and efficient for solving such model updating problems. New formulae for Markov chain convergence assessment are derived. The effectiveness of the proposed approach for Bayesian model updating of structural dynamic models with many uncertain parameters is illustrated with a simulated data example involving a ten-story building that has 31 model parameters to be updated.     

Ontology-Based Approach to Context Representation and Reasoning for Managing Context-Sensitive Construction Information

The construction industry is an information-intensive industry and heavily relies on documents, including physical and virtual documentation and models, to exchange context-sensitive information among different project participants. Many research efforts have been made to help manage construction information; however, few of them considered the context-sensitive nature of the information. In this paper, the writers propose a new approach to facilitate the management of context-sensitive construction information that is stored in different textual documents. The approach addresses the context-sensitive nature of construction information by representing contexts in ontologies and by using contexts as indices of the information. The approach also presents a reasoning mechanism that leverages the semantically rich features of ontologies to reason about contexts to evaluate their applicabilities. Two case studies were conducted, and the results showed the proposed approach can effectively retrieve, classify, and manage construction information. Finally, the writers discuss the limitations of the proposed approach and future research directions.     

Extrapolation for Future Maximum Load Statistics

The use of short-term load data to extrapolate or project remote future maximum load has been practiced in structural design code development and/or calibration. However, this approach has not been adequately evaluated or validated because of the absence of long-term data, which is important for the structures’ safety governed by these codes. In this paper, the application of such extrapolations to highway bridge design is studied by taking advantage of available long-term truck weight data obtained from the weigh-in-motion technique. A new extrapolation method is proposed from the understanding of the importance of the load probability distribution’s high tail. This approach significantly reduces the mathematical length of the extrapolation/projection and thus increases its reliability. Also presented in this paper are application examples. In addition, the extrapolation process proposed is evaluated with quantitative indexes. The application of a temporal extrapolation/projection can now be evaluated by using these indexes for its reliability and appropriateness.     

Win–Win Concession Period Determination Methodology

In infrastructure development through public-private partnerships (PPPs), governments worldwide often preset the concession period to a fixed length and then invite the private sector to bid on other aspects of the project. This practice has potential economic, financial, and social problems as shown in a case study of Hong Kong tunnel projects. To overcome these problems, this paper has proposed a win–win concession period determination methodology, in which PPPs are addressed as a principal-agent maximization problem. Both deterministic and simulation-based methods are provided to determine the concession period, with detailed step-by-step procedures. These methods take into consideration the financial characteristics of PPPs and the construction and operation requirements. In particular, the simulation-based approach combines the critical path method and Monte Carlo simulation technique in an effort to quantify construction and market risks for informed decision making. Furthermore, some issues related to the proposed methodology also have been discussed. These issues include (1) factors in determining a reasonable rate of return to the concessionaire’s equity investment; (2) advantages and disadvantages of rate of return regulation; (3) concession period as a tender evaluation criterion; (4) efficiency check of the concessionaire’s cost performance; (5) workable pricing mechanism; and (6) a practical approach to establishing statistical construction cost/duration distributions.     

Detecting Sensor Failure via Decoupled Error Function and Inverse Input–Output Model

A novel sensor failure detection method is developed in this paper. Sensor failure considered in this paper can be any type of measurement error that is different from the true structural response. The sensors are divided into two groups; sensors that correctly measure the structural responses are termed “reference sensors” and sensors that may fail to correctly measure the structural responses are termed “uncertain sensors” henceforth. A sensor error function is formulated to detect the instants of failure of the corresponding uncertain sensor, using the measurements from reference sensors and the uncertain sensor examined. The sensor error function is derived using indirect and direct approaches. In the indirect approach, the error function is obtained from the state space model in combination with the inverse model and interaction matrix formulation. The input term is eliminated from the error function by applying the inverse model and the interaction matrix is applied to eliminate the state and all unexamined uncertain sensors except for the one examined from the error function. The direct approach uses the singular value decomposition method to establish the coefficients of the error function from the healthy measured data. The sensor failure detection formulation is investigated numerically using a four degree-of-freedom spring-mass-damper system and experimentally using a 4-m-long NASA eight-bay truss structure. It is shown by means of numerical and experimental results that the sensor failure formulation developed correctly detects and isolates the instants of sensor failure and can be implemented in real structural systems for sensor failure detection.     

Formalism for Detecting Version Differences in Data Models

In the architecture/engineering/construction (AEC) industry, a large number of data models (e.g., data exchange standards and task-specific data models) have been created and utilized to represent and exchange data in software packages. To meet the ever-expanding requirements for modeling real world information, the data models need to be updated frequently. Accordingly, those who need to implement these data models in their AEC-related software which often requires that they possess civil engineering domain knowledge, have to change their existing implementations for compliance with these models to account for the latest update. Before adopting changes of such data models, those developers working at AEC-related software companies must precisely identify which parts of the data models have been modified in a new release. Given the growing scale and complexity of today’s data models involved in the AEC domain, identification of differences in two versions of a data model is a time-consuming and error-prone process, when performed manually. A semiautomated approach that identifies the differences in two versions of a data model could enable a rapid update of existing implementations of the model in AEC-related software. Due to the likelihood of having some commonality between the two versions of a model, it is possible to automatically identify version differences accurately. In this paper, we present an approach for detecting the differences between two releases of the same data model accurately and efficiently. This approach incorporates taxonomy for describing possible differences between two versions of a data model and provides a way to classify these differences. A prototype is implemented and used to validate the approach with the recent releases of some real world data models. The approach developed in this paper can help AEC-related software developers adopt and implement data models in their software systems.     

Differentiation between glomerular and non-glomerular erythrocyturia: what is the value of differential microhematuria diagnosis?

A few years ago, a new and simple method has been proposed to help guiding the investigation of microhematuria. This method which consists in quantifying the percentage of deformed polymorphous erythrocytes in the urinary sediment using phase contrast microscopy allows to distinguish glomerular from non-glomerular erythrocytes. In this paper, we have reviewed the recent literature concerning this approach and have discussed the conclusions according to our own experience based on the analysis of 147 patients presenting with microhematuria. Our results demonstrate that this technique is still limited by the difficulty to obtain well-defined cut-off values which effectively differentiate renal from urologic diseases. Thus, only extreme results showing either the total absence or the presence of a very high percentage of dismorphic erythrocytes appear to be helpful for the physician. Despite the introduction of this new method, many patients with microhematuria are insufficiently investigated.     

Optimizing Implementation of Value Management Processes for Capital Projects

A variety of innovative management processes are increasingly being introduced into the capital facility projects, thereby causing a great concern about which to implement on a particular project among project stakeholders. It is essential to identify the most effective process because varying circumstances on each project determine the level of suitability. This paper details a new systematic approach to determining the best process from among the 44 value management processes (VMPs) that can proactively achieve the articulated 12 project value objectives (PVOs). Throughout this paper, identifying and quantifying the selection principles (e.g., targeted PVOs, timing of initiation, project characteristics, and relative impact), the detailed research methodology and the findings from industry survey and VMP expert input are also illustrated. A computerized tool, programmed by Visual Basic Application on MS Excel, is described, and its ongoing validation process is also discussed. As a first-ever research, this paper contributes to a growing area of research, not only by providing a comprehensive and structured knowledge on the subject of VMPs, but also by developing a new method to effectively select the most beneficial VMPs. From the industry perspective, the results of this study, specifically the computerized selection tool, facilitate the implementation of the VMPs on the construction industry and maximize the potential benefits to a particular project.     

Multiple primary tumours of the urogenital system: our cases and a review of the literature

The impacted palatal canine requires a combination of both surgical and orthodontic management. Two types of approach are commonly used: simple exposure, or exposure with bracketing at the time of surgery. In this study 104 consecutively treated patients with palatally impacted canines were examined at two centres, one at which the ectopic tooth was surgically exposed alone and the other where an orthodontic bracket was bonded to facilitate early traction, and the flap replaced. The aim was to compare the outcome and complication rate for each type of procedure. In 30.7 per cent of all cases exposed and bracketed a second surgical intervention was required, compared with 15.3 per cent in the simple exposure group. Bracketing, though effective, is a more costly and time-consuming procedure, and it is suggested that simple exposure provides an equally efficient and predictable method of managing the palatally impacted canine with obvious clinical and financial benefits. The long-term periodontal status of the teeth which have been exposed in these two ways, however, needs further investigation.