Journal of Construction Engineering and Management

The condition and performance of bridges vary widely across North America. The large amount of expenditures on bridges needs significant efforts to optimize budget and resource allocation and to select the best rehabilitation or replacement method, which reduces project cost and duration. Simulation has been widely used in the construction area to optimize productivity and resource allocation. Current research optimizes resource combination for bridge deck rehabilitation projects using discrete event simulation. The Jacques Cartier Bridge redecking project is selected as a case study. Data related to productivity and duration of different activities were collected from the project. Probability distributions are fitted, which show the robustness of normal distribution to fit most variables. A simulation model is developed for this project in order to experiment with and perform sensitivity analysis. Based on the simulation results, an optimum resource combination of deck rehabilitation is obtained, which is [five teams, two saws, three old section trucks, and five new panel trucks] TSON 5235 with the unit (panel) cost of $\$747∕\mathrm{h}$ (direct cost only). The model developed is tested against real productivity where it shows reasonable results. The present research is relevant to both researchers and practitioners. It provides bridge redecking researchers with a real case study, a simulation model, and an approach to analyze projects. It also provides practitioners with an approach to optimize the usage of their resources considering direct project cost.

Operators of tower cranes enjoy a bird’s eye view of the site, which undeniably contributes to work safety and efficiency. Yet their work often involves blind lifts, as well as other viewing difficulties, that impede full utilization of the potential inherent in the operator’s location atop the crane. This paper reports on a tower-crane-mounted live video system that offers a solution for such difficulties, and consequently, enhances safety, improves productivity, and brings about direct and indirect cost savings. The development and implementation of the vision system are described as a successful academia–industry research and development joint effort. Work studies of numerous craning cycles resulted in considerable time savings, depending on the nature of the lift, lighting conditions, and viewing obstructions. In addition, a detailed list of benefits drawn on the basis of feedback received from the field is presented. The paper is aimed, first and foremost, at project managers as well as construction equipment and safety practitioners, who daily experience those situations that have prompted the development of the system. Researchers may benefit mainly from the lessons learned with respect to the role of academia–industry cooperation in the introduction of innovative systems in construction.

A construction project is mostly initiated by the needs of the client. In order to satisfy the client’s requirements in terms of time, cost, and quality, various procurement methods are recommended for selection to increase the chance of success for the complex sequence of activities. Design-build (D&B) integrates design and construction to overcome some of the hurdles inherent in the traditional design-bid-build method. It has been extensively used worldwide and its distinctive features are claimed to deal with the problems of the traditional design-bid-build method. An investigation into the determinants of successful D&B projects can therefore help set a benchmark study for industry practitioners to compare their project performance. To better indicate the success level of D&B projects, the writers developed a project success index for D&B projects in the Hong Kong context, which is assessed by the key project performance indicators of time, cost, quality, and functionality. Multiple regression analysis is then applied to show that the project nature, the effective project management action, and the adoption of innovative management approaches are the critical success factors for D&B projects. The identification of success criteria can furnish project participants with indicators to attain success for their D&B projects for benchmarking and control purposes. The predictors for D&B project success were also determined to enrich the knowledge base for the D&B procurement system.

The aging infrastructure in North America and worldwide mandates large investments in repair and improvement (R&I) activities. For organizations that own many assets, managing a large number of R&I activities is not a simple task and requires accurate estimating and scheduling so that proper budgeting and resource allocation decisions can be made. To support these decisions, this paper introduces a Web-based system that estimates the cost and duration of a user-requested R&I activity and provides alternative schedules based on resource availability. For estimating, the Web-based system hosts 32 artificial neural networks (ANNs), trained on actual historical data, for 32 common R&I activities in building projects. Each ANN incorporates a sensitivity analysis to consider the uncertainty in the input parameters on the estimate, and is linked to a central scheduling algorithm for resource allocation based on a first-come first-serve basis. The automated system helps practitioners in planning numerous R&I requests with least time, cost, and paper work. Details on system development are provided in this paper along with perceived benefits and the opinion of users on its performance.

From cost estimation to reliability analysis, Monte Carlo simulation has found its niche in a wide variety of applications in civil engineering. With recognition of correlations among variables, recent efforts have been devoted to model the correlations more accurately and with no restriction on the form of marginal distributions, i.e., being distribution free. Yet, the conventional method introduced by Iman and Conover, although widely accepted, is bound to have errors: The generated correlation matrix may bear no resemblance to the desired correlation matrix. The purposes of this study are to shed light on the underlying premises of the conventional method and to refine the method by reducing the errors to an acceptable level automatically. A particle swarm optimization algorithm is proposed to repair invalid (nonpositive definite) correlation matrices and to bring the generated correlation matrix into conformity with the desired target. The effectiveness of the proposed algorithm has been verified in estimating cost of electrical services based on historical data.

Joint ventures have become popular because of their importance as a strategic alternative in global competition. One of the reasons why international joint ventures (IJVs) are difficult to manage is because the cultural distance between IJV partners has significant impact on alliance performance. Since construction projects are highly sensitive to external risks, the effect of the culture in the location in which the IJV operates is also significant. In this study, the effect of cultural similarity/difference relative to the national and organizational characteristics of partner companies on IJV performance is examined through a questionnaire survey. The impact of the cultural similarity/difference between an IJV partner and the host country is also assessed. The results of the study suggest that differences in organizational culture have a greater impact on IJV performance than differences in national and host country culture. The findings also reveal that similarity between the national cultures of IJV partners has a negative effect on IJV performance. The analysis of the data failed to provide evidence that IJV performance is affected by differences between the culture of the host country and the culture of an IJV partner.

A construction process reengineering framework and its corresponding methodologies have been developed by integrating lean principles and computer simulation techniques. Instead of classifying activities into value-adding and non-value-adding activities, or into conversion and flow activities as is common in lean production practices, this framework classifies activities into main and supportive activities and/or into normal and interactive activities. This classification makes it more effective in modeling the construction workflow and reengineering the construction process. It also avoids the confusion of the classification of activities into value-adding and non-value-adding activities encountered in the construction industry. In addition, computer simulation techniques are incorporated into the framework to virtually simulate and assess the efficiency and effectiveness of the reengineered construction process that is achieved based on lean principles. Simulation makes it easier to quantify and assess the effectiveness and efficiency of the reengineered construction process.