Journal of Construction Engineering and Management

Quantifying lost labor productivity on construction projects is difficult and sometimes subjective. A widely accepted way to quantify losses is the “measured mile” approach. It compares periods of a project that have been impacted by change to those that have not been impacted. As currently practiced the measured mile relies on subjectively identifying that reference period. In this paper the measured mile and a variant, the baseline method, are analyzed and compared to a new, proposed statistical clustering method. This new approach is advocated because it determines its reference period using objective criteria. A case study is included to show how the three methods work, and advantages and disadvantages of each method are presented in this paper.

Large amounts of money are lost each year in the construction industry because of poor schedule and cost control. Few contractors specify and follow systematic schedule monitoring practices. Traditionally, the earned value method (EVM) is used to control and monitor schedule performance using the schedule and cost performance indices which compare the budgeted cost of work performed to what was originally scheduled or what is actually expended. This paper presents a statistical approach, namely Weibull analysis, to evaluate stochastically the schedule performance of construction or design projects. The approach can be used in conjunction with the EVM to enhance the evaluation and control of schedule performance. Weibull analysis is a common method for failure analysis and reliability engineering used in a wide range of applications. In this paper, the applicability of Weibull analysis for evaluating and comparing the reliability of the schedule performance of multiple projects is presented. The various steps in the analysis are discussed along with an example in which two projects are analyzed and compared. The authors conclude that Weibull analysis has several advantages and provides a relatively robust and effective method for construction managers to better control and monitor their projects.

Selection of equipment for construction projects, a key factor in the success of the project, is a complex process. Current models offered by the literature fail to provide adequate solutions for two major issues: the systematic evaluation of soft factors, and the weighting of soft benefits in comparison with costs. This paper presents a selection model based on analytic hierarchy process (AHP), a multiattribute decision analysis method, with a view to providing solutions for these two issues. The model has the capacity to handle a great number of different criteria in a way that truly reflects the complex reality, to incorporate the context and unique conditions of the project, and to allow for manifestation of user experience and subjective perception. The model was implemented in an in-house developed system that was improved and validated through testing by senior professionals. The main academic contribution of the study is in the modification of AHP to correspond with the nature of equipment selection and in its utilization as an effective means for the formalization of knowledge possessed by competent, experienced practitioners. On the practical side, the proposed model offers an efficient, convenient tool that forces the users into orderly, methodical thinking, guides them in making logical, consistent decisions, and provides a facility for all necessary computations.

The demand for sustainable buildings is an important emerging trend in the building industry. However, the task of delivering these facilities is more difficult than for traditional projects and existing project management techniques struggle to handle the high levels of complexity present. A process-based model, called the continuous value enhancement process (CVEP), was developed to systematically generate and evaluate project alternatives leading to high performance solutions that improve project performance and increase levels of sustainability. Developed specifically to address the challenges facing the Pentagon renovation—which will become the world’s largest green office renovation—CVEP is tested to research its ability to support project management decision making in ways that elevate sustainability and project performance. The key contributions of this model include the integration of sustainable objectives into project management practices, and the development of a metric for measuring the quality and focus of project team decisions.

The California Department of Transportation is rehabilitating or reconstructing deteriorated urban freeways using long-life (30+ years) strategies. These pavements were constructed between 1955 and 1970 with design lives of 20 years. This paper summarizes preconstruction analysis of the fast-track pavement reconstruction on Interstate-15 (I-15) at Devore which used two one-roadbed continuous (about 210 h) closures with round-the-clock $(24∕7)$ operations. The integrated analysis concluded that the one-roadbed continuous closures are the most economical scenario when compared to traditional nighttime or weekend closures from the perspective of schedule, delay, and costs. The preconstruction was validated with as-built construction and traffic performances monitored during construction. The construction management plan—including contingency, incentives, and critical path method schedule—was developed utilizing the Construction Analysis for Pavement Rehabilitation Strategies (CA4PRS) computer model. The results of this planning study are useful for transportation agencies in developing highway rehabilitation strategies that balance the maximization of construction productivity with a minimization of traffic delay.

This paper presents a decision support system for optimizing temporary lighting arrangements in nighttime highway construction projects. The system is developed as a multiobjective genetic algorithm that is capable of: (1) maximizing average illuminance on construction sites; (2) maximizing lighting uniformity in the work zone; (3) minimizing glare to workers and road users; and (4) minimizing lighting costs. The system is designed to support decision makers in their search for practical lighting arrangements that provide various tradeoffs among these four conflicting objectives. Five decision variables are optimized in the present system, namely: number of lighting equipment, equipment positioning, mounting height, aiming angle, and rotation angle. The system is also designed to consider and satisfy all practical constraints that can be encountered in this lighting design problem. An application example is analyzed to illustrate the use of the system and demonstrate its capabilities in generating near optimal and practical lighting arrangements for nighttime highway construction projects.

Varied computing devices and automated sensors will enable new human-computer interface paradigms for interacting with digitally managed project information. The writers therefore propose the development of Mixed Reality (MR)-based computer interfaces, and especially Augmented Reality systems, for the architecture, engineering, and construction industry and describe the technologies and principles for applying such computer interfaces to support all phases of the constructed facility project life cycle. An Augmented Reality computer-aided drawing prototype is described as an experimental platform to study the human factors issues in interacting with Augmented Reality three-dimensional digital design models. Two critical research needs are cited for realizing effective Augmented Reality systems: (1) human factors research for development of visualization tools to enhance design comprehension and support collaborative work, and (2) the development of a technology infrastructure for “augmented” control and inspection interfaces to directly access digital project plan and site information that may be spatially referenced and displayed in the field. Research should be geared to advance knowledge regarding spatial cognition, human–computer interfaces, and computer-mediated human-to-human interactions, and it should address application of MR to all phases of the project life cycle.

In spite of the efforts by government agencies, labor organizations, and researchers in the field of health and safety, injuries and fatalities continue to affect the construction industry. In 2002 the construction industry had the undesirable distinction of having two of the most dangerous occupations in the United States, with fatalities among structural steel workers at 58.2 per 100,000 workers (fourth highest rate) and among construction laborers at 27.7 per 100,000 workers (ninth highest rate). Costs associated with construction accidents, such as increased insurance premiums and medical expenses, and loss of productivity are also concerns in the industry. It has not been demonstrated how unsafe working conditions affect worker performance, and the impact of unsafe work practices on worker performance has not been quantified. This paper describes a methodology that included direct observation of steel erection activities and statistical analysis of task duration data. The data collected at steel erection sites included safety conditions such as the use of personal protective equipment (PPE), elevation of the work area, environmental conditions such as temperature and humidity, and worker performance in the form of task durations. Analysis of variance (ANOVA) analysis of 186 of steel erection task durations collected over a six-month period showed that the use of personal protective equipment (PPE), the time of day during which the operation was being performed, the elevation at which the work was being performed, and the presence of decking below the work area had statistically significant effects on the durations of steel erection tasks.

Construction apprentices in a Midwestern city were surveyed to find out their perceptions on their foremen. Based on the analysis of our data, seven foreman factor scales were identified. These scales are: Performance Improvement, Work Facilitation, Achievement Orientation, Support, Work Participation, Bias, and Recognition. These dimensions have varying relationships with motivation and performance of the construction apprentice. These dimensions provide important issues that need to be addressed in developing foremen training programs and in particular how they affect apprentice. Further research may encompass various segments of the construction industry to analyze motivation of craft workers.

Materials resources constitute a large portion of a project’s total cost and this makes them an important and attractive subject to control. Proper control and management of materials can meaningfully increase productivity by 6%, or more. A model based on automatic, or semiautomatic, data collection for materials management and control was developed. Based on project plans, the model initiates and manages the ordering of materials automatically and monitors both the actual flow of materials and the current stock at the construction site. The model permits real-time control, enabling corrective actions to be taken. In this manner, costs and unnecessary handling of materials are reduced. In addition, up-to-date information regarding materials flow is available and different statistical analyses are enabled: materials acquired from a specific supplier; materials used for a specific activity; and materials used during a specific month, etc. The information generated by the model enables the updating of a historical database to be used for planning of future projects.