Journal of Construction Engineering and Management

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.

Daily recording of the actions done by all parties on a construction site is necessary, not only for confirming that work is done according to specifications, but also for analyzing any claims for additional time/cost. Site records, however, are often incomplete and inaccurate, and commercial scheduling software provides little support in this regard. In this paper, a simplified approach for site-data recording and constructing “as-built” schedules is introduced through the use of intelligent bar charts. The proposed bar chart guides the user through progress reporting by observing any conflict with the planned logic of the work. It automatically recognizes the occurrence of delays and asks the user to record the responsible party and the reasons. Based on percent completes and recorded delays, the bar chart recognizes the progress status of activities as being slow, suspended, or accelerated. The paper starts with a description of the types of data that need to be recorded on site. It then provides a description of the automated guidance mechanism of the proposed bar chart, along with details on schedule integration and applicability for claim analysis.

This study evaluates the resource-constrained critical path method (RCPM), which the writers have recently proposed. RCPM establishes a critical path method (CPM)-like, resource-constrained schedule by resource-dependent activity relationships (or resource links) that the five-step RCPM technique identifies. With its CPM-like feature, RCPM provides the critical path and float data that are not available in traditional resource-constrained scheduling techniques. In addition, RCPM provides more flexibility to the schedule through identified alternative schedules, which allow certain activities to be executed beyond their late finish times without delaying the project completion. This paper evaluates the RCPM’s performance by comparing it with five related previous studies. A brief review of each study is also included in this paper. This comparison shows that RCPM performs well in identifying resource links and alternative schedules, compared to other methods. This study is of interest to academics because it highlights the advantages and disadvantages of different algorithms that have attempted to overcome present problems in traditional resource-constrained scheduling techniques.

In 2001, a survey found that 87% of engineering professors in the United States spend the entire class time lecturing to a passive group of students material that is copied down and never looked at again. This paper presents the results of scientific inquiry and keen observations all leading to the same conclusion: engineering education has to reform itself. Presently, almost all engineering students learn best doing lots of homework $(\sim 50\%)$ and theoretical study (25%) are accommodated by lectures, homework, and rote-problem tests. Regrettably, an overwhelming number of the creative students do not learn this way and fail. Learning as a process needs to be put at the heart of education moving us away from the traditional educational enterprise. The presented data benefits researchers and practitioners in that they highlight the urgency of the issue and show how the proposed paradigm shift is underpinned by our understanding of how people learn.

Damage resulting from directionally drilled crossings has become a concern for municipalities and contractors due to the increased popularity of this trenchless installation method. Surface heave is one mechanism through which directionally drilled installations may damage existing surface structures such as pavements and foundations. Several factors contribute to the development of surface heave including backream rate, borehole pressure, downhole tooling, depth of cover, annular space size, and geotechnical properties. This paper presents and discusses results of a detailed field experiment which monitored surface heave under various installation characteristics. Four borepaths were designed to implement a full factorial examination to determine the interaction of backream rate, depth of cover, drill mud flow, and reamer type have on the development of surface heave. With greater understanding of how drilling practices affect the development of surface heave, practitioners of this technology may better plan installations to minimize the impact of their operation.

Engineering and design professionals constitute a major driving force for a successful project undertaking. Although the industry has been active in addressing the performance of construction labor and methods to estimate or predict such performance, relatively fewer efforts have been conducted for the engineering profession. In an attempt to fill out this gap, the paper presents a study to utilize neurofuzzy intelligent systems for predicting the engineering performance in a construction project. First, neurofuzzy systems are introduced as integrated schemes of artificial neural networks and fuzzy control systems. The use of these neurofuzzy intelligent systems, particularly fuzzy neural networks, in predicting engineering performance is then demonstrated in the industrial construction sector. The development of the system is based on actual project data that was collected through questionnaire surveys. Statistical variable reduction techniques are further employed to develop linear regression models of the same engineering performance prediction scheme, and results are being compared between both techniques.

Engineering and design activities constitute a critical link in a project’s life cycle. Thus, an efficient project control system requires an instrument to measure and assess engineering performance among different projects. In conventional industry practices, the measurement of engineering performance is usually tied to the production of design documents during the detailed design phase of the project. Realizing the far-reaching impacts of engineering activities, researchers in the past have investigated other comprehensive measures of engineering performance that address the entire project life cycle. As part of a study for the Construction Industry Institute, this particular research employs a multiple attribute utility function method for the collective assessment of engineering performance in construction projects. The paper begins with a summary of previous studies in the area of engineering performance measurement and assessment. Afterwards, the concept of engineering performance is thoroughly explained. The paper then reviews the background and basic theories of using utility functions in assessing engineering performance, along with an illustrative example of the functionality of this approach. The paper goes on to show the development of the utility function model for the industrial construction sector through expert opinion and real project data. The use of the model is further illustrated in the assessment of total and relative engineering performance. Lastly, conclusions of this study are drawn and potential future work is pointed out.

Although guidance is available for state transportation agencies to establish constructability review processes (CRPs), nationwide implementation has been slow due, in part, to a lack of clarity regarding related costs and benefits and a perception that CRPs are resource intensive. This study funded by the National Cooperative Highway Research Program reveals that while numerous states have attempted implementation in various forms, obstacles have frequently either hindered or halted progress. Four elements appear to be essential for the successful implementation and continuance of a CRP: (1) institutionalization of the CRP Champion, (2) an emphasis on a quality-driven as opposed to a schedule-driven design process, (3) clear yet flexible guidelines for executing constructability reviews across the broad range of project types and sizes, and (4) a vehicle for meaningful expert input from construction contracting professionals. A benefit-cost model, founded on the proposition that CRP implementation provides efficiencies that result in significant cost and schedule reductions, is demonstrated using case studies. A need for more precise identification of costs and quantification of benefits is noted.

Mobile crane manufacturers provide operators and practitioners with tabulated lift-capacity charts. These charts are structured based on predetermined crane configurations, which consist of boom/jib length, lifting radius, lifting height, main boom angles to ground, and jib angle to ground or its offset to its main boom centerline. Practitioners, however, are often required to lift on a partially extended hydraulic section and/or lifting radius other than those listed in the manufacturers’ lift-capacity charts. This paper presents a newly developed optimization algorithm (referred to in this paper as Algorithm-2) for selecting and locating mobile cranes on construction sites based on their minimum boom length and/or minimum radius, accordingly higher lifting capacities. Algorithm-2 includes an optimization procedure that avoids lifting capacity violations. In addition to the practical use of Algorithm 2, the mathematical representations of the crane’s geometry are also useful for research in the automation and robotic field of operations involving cranes. The algorithm is incorporated into a computer system that integrates a selection module and a database. Data pertinent to crane lift configurations are retrieved from the database and are then processed to determine the optimum, geometrical selection of the crane configuration. A case example is described in order to demonstrate the use of the developed algorithm and to illustrate its essential features.

The ongoing plethora of rehabilitation in the infrastructure domain requires more planning and integration during design and construction. To achieve this, there is a need for developing and using semantic (ontology-based) mechanisms for the exchange of development knowledge among all project stakeholders. This paper presents a distributed ontology architecture for knowledge management in highway construction. With every other utility tied to the highway geometry, the architecture is intended to be the base for a cross-discipline knowledge exchange in the infrastructure domain. The architecture presents highway knowledge on three levels: domain knowledge (an umbrella for infrastructure shared knowledge), application knowledge (representation of highway-specific knowledge), and user knowledge (an enterprise-specific representation of highway knowledge). The proposed architecture models highway concepts using six major root concepts: project, process, product, actor, resources, and technical topics (attributes and constraints). The architecture was developed using rigorous knowledge acquisition and ontology development techniques. It was developed as an extension for the e-COGNOS ontology. The architecture was validated through input from domain experts.

One of the differences between industrial manufacturing or processing plants and construction sites is the temporary nature of the construction site, which has traditionally precluded installation of sophisticated production monitoring systems. Monitoring of production progress, cost, and quality is performed almost exclusively manually, with the result that it is expensive and approximate, and is commonly delivered with a time lag that does not allow for an effectively closed control loop. Automated monitoring of construction lifting equipment to provide useful feedback information for project management is a strong potential candidate; almost all components and materials must be transported by machines, and monitoring of machines is relatively straightforward. A system concept, employing a “black box” monitor and an electronic building information model, was developed. A field study was conducted to test the feasibility of the concept. The results indicate that the system is technically feasible, and offers the potential to deliver real-time, accurate project control information at very low cost.