Selecting an appropriate bridge construction method is essential for the success of bridge construction projects. The Analytical Hierarchy Process (AHP) method has been widely used for solving multi-criteria decision-making problems. However, the conventional AHP method is incapable of handling the uncertainty and vagueness involving the mapping of one's preference to an exact number or ratio. This paper presents a fuzzy AHP model to overcome this problem. The proposed approach employs triangular and trapezoidal fuzzy numbers and the -cut concept to deal with the imprecision inherent to the process of subjective judgment. A case study that evaluates bridge construction methods is presented to illustrate the use of the model and to demonstrate the capability of the model.
This paper presents an extension of the BIM technology that allows to manage information during the entire lifecycle of an AEC project. Usually, AEC projects and facility management are dissociated. Our building information system plays a central role in the improvement of the design and the management process. The building activity generates a great number of data and information of various kinds. The management and the communication of these data by the various participants is complex. Our design and management methods use IFC files to facilitate the sharing process for a better qualification and validation of data.
Progress reporting is an essential management function for successful delivery of construction projects. It relies on tangible data collected from construction job sites, which is then used to compare actual work performed to that planned. One method used to collect actual work data is 3D laser scanning, where the construction site is scanned at different times to generate data, which can then be used to estimate the quantities of work performed within the time interval considered between two successive scans. Photogrammetry is another method for data collection where the geometrical properties of an object on site are generated from its photo image. This paper presents a method, which integrates 3D scanning and photogrammetry in an effort to enhance the speed and accuracy of data collection from construction sites to support progress measurement and project control. The application of the proposed method is demonstrated using a building presently under construction.
The presented research shows how advanced wireless sensor technology can be used by engineers to monitor conditions in and around buildings. The objective is split into three different tasks. First, wireless sensor hardware is programmed to process signals from sensors and transmit the data in a suitable format. This task was accomplished through an open-source operating system and a programming language designed specifically for wireless sensor hardware. The second task involved the processing of signals sent by the wireless sensor nodes. In this application, a Java program was written that deciphered messages transmitted from a wireless receiver over a computer's serial port and then placed the data in a database. The structure of that database is discussed to help identify the key pieces of information that are needed to make use of the data. The third piece of the proposed monitoring system is an interface to review the data. A Web-based system was developed that allows a user to mine the database using parameters such as the type of data, location of sensor, and the time of data acquisition. It is anticipated that this research will demonstrate the potential of using wireless sensor networks for monitoring buildings.
Automated and robust retrieval of three-dimensional (3D) Computer-Aided Design (CAD) objects from laser scanned data would have many potentially valuable applications in construction engineering and management. For example, it would enable automated progress assessment for effortless productivity tracking, automated 3D image database searching for forensic and legal analysis, and real-time local modeling for automated equipment control and safety. After reviewing and analyzing previous research in the field of automated object recognition, this paper presents a new approach for robust automated recognition/retrieval of 3D CAD objects in range point clouds in the Architectural/Engineering/Construction & Facility Management (AEC-FM) context. This approach is validated in laboratory experiments. A first experiment demonstrates that this new approach can efficiently and robustly automatically retrieve 3D CAD model objects in construction laser scanned data. A second experiment demonstrates how this approach can be used for efficiently assessing construction progress. The results presented here are preliminary but conclusive for proof of concept. More extensive field experiments in this and other application areas will follow to characterize performance trade-offs in practice.
Existing methods for tracking and managing the inspection in material test labs utilize manual recording by paper-based documents. However, information collected using such labor-intensive methods is unreliable and ineffective when managing inspection results. Moreover, inputting, retrieving, analyzing and disseminating the result data instantaneously require a significant amount of time and effort. Therefore, an automated and user-friendly quality management system is necessary. This study proposes Radio Frequency Identification (RFID)-based quality management system, which functions as a platform for gathering, filtering, managing, monitoring and sharing quality data. The integration of promising information technologies such as RFID technology, mobile devices (PDAs) and web portals can help enhance the effectiveness and flexibility of information flow in material test management. Radio frequency identification is suited to various construction applications and generates cost savings via increased speed and accuracy of data entry. This study demonstrates the effectiveness of an RFID-based quality management application called the RFID-based Quality Inspection and Management (RFID-QIM) System for concrete specimen inspection and management to enhance automated data collection and information management in a quality test lab. This study focuses mainly on evaluating the potential for utilizing RFID-based techniques to accumulate, manage, monitor and distribute data related to quality. Additionally, the RFID-QIM system is then applied to a case study in a test lab (construction division) in Taiwan to demonstrate the effectiveness of the proposed methodology in information management for concrete specimen quality testing. A generic system architecture is also proposed, and its implementation is described.
Construction projects are information-intensive in nature and require site personnel to have continuous on-demand access to information such as project plans, drawings, schedules, and budgets. Awareness of a user's context (such as user profile, role, preferences, task, and existing project conditions) can enhance the construction project delivery process by providing a mechanism to determine information relevant to a particular context. Context awareness can also be used to improve security, logistics and health and safety practices on construction sites. Location is an important aspect of context awareness. A location aware application can utilize the knowledge of the user/object location to provide relevant information and services. This paper argues that a successful and reliable location tracking system must be able to track a user's spatial context and deliver contextual data continuously in both outdoor and indoor environments to effectively support construction projects. Research describing the use of Wireless Local Area Network (WLAN) for indoor tracking and Global Positioning System (GPS) for outdoor spatial context tracking is presented, and an integrated tracking technique using WLAN and GPS for ubiquitous location sensing is introduced. The key benefits and technical challenges of such an integrated approach are also highlighted. The presented tracking techniques have been validated in both indoor and outdoor environments to ensure their practical implementation on real construction jobsites.
This paper presents an extension of the BIM technology that allows to manage information during the entire lifecycle of an AEC project. Usually, AEC projects and facility management are dissociated. Our building information system plays a central role in the improvement of the design and the management process. The building activity generates a great number of data and information of various kinds. The management and the communication of these data by the various participants is complex. Our design and management methods use IFC files to facilitate the sharing process for a better qualification and validation of data. (C) 2008 Elsevier B.V. All rights reserved.
Owing to the increasing complexity in the construction management, integrating experts' knowledge and experiences to make appropriate decisions is a commonly used method. TOPSIS (technique for order performance by similarity to ideal solution) is a practical and useful technique in dealing with multi-attribute decision making problems, and has been widely employed in the construction management and other fields. The modification and extension of TOPSIS to a group decision environment is investigated in this study. In the proposed group decision making model, we both adopt the Minkowski distance function to solve the over-weighted problem in the original TOPSIS technique, the grey number operations to deal with the problem of uncertain information, and the aggregation approach to integrate experts' evaluations. Finally, an illustrative example of subcontractor selection is used to demonstrate the feasibility and practicability of the proposed model.
Hybrid system, which has been successfully used in vehicles, is introduced to hydraulic excavators nowadays. The primary focus of this study is to investigate the control strategies of hybrid system used in hydraulic excavators. At first, the structure and working conditions of hybrid hydraulic excavators are analyzed. Based on the analyses, a control strategy named the engine constant-work-point is proposed and studied in a simulative experimental system. Then the control strategy named double-work-point is presented to overcome the limitations of the constant-work-point control strategy. The features and experimental results of the double-work-point control strategy show that the engine's efficiency and the capacitor's state of charge (SOC) cannot be optimized simultaneously. Thus a dynamic-work-point control strategy, which regulates the engine's working point dynamically, is developed to make the system work better. Experimental results show that the dynamic-work-point control strategy can improve the distribution of engine's working points, restrain the capacitor's SOC and has little influence on the performance of the system.
Research studies in the application of Augmented Reality (AR) in the Architecture, Engineering, and Construction (AEC) industry have suggested its feasibility. However, realization of the use of AR in AEC requires not only demonstration of feasibility but also validation of its suitability. This paper comprehensively identifies AR application areas in industrial construction based on suitability of AR technologies. In order to successfully explore suitability of AR, this paper assesses work tasks from the viewpoint of human factors regarding visual information requirements to find rationale for the benefits of AR in work tasks. Based on the assessment of work tasks, this paper presents a comprehensive map that identifies AR application areas in industrial construction. The comprehensive map reveals that eight work tasks (layout, excavation, positioning, inspection, coordination, supervision, commenting, and strategizing) out of 17 classified work tasks may potentially benefit from AR support.
Construction Virtual Prototyping (CVP) is the use of integrated product, process and resource models of construction projects to support the construction planning in virtual environment. This paper describes an integrated framework and process for efficient application of CVP to support project teams on construction planning. It includes specific examples of models and objectives as well as detailed suggestions on how to implement CVP in practice.
Adiabatic hydration curves are the most suitable data for temperature calculations in concrete hardening structures. However, it is very difficult to predict the adiabatic hydration curve of an arbitrary concrete mixture. The idea of modeling adiabatic temperature rise during concrete hydration with the use of artificial neural networks was introduced in order to describe the adiabatic hydration of an arbitrary concrete mixture, depending on factors which influence the hydration process of cement in concrete. The influence of these factors was determined by our own experiments. A comparison between experimentally determined adiabatic curves and adiabatic curves, evaluated by proposed numerical model shows that artificial neural networks can be used to predict adiabatic hydration curves effectively. This model can be easily incorporated in the computer programs for prediction of the thermal fields in young concrete structures, implemented in the finite element or finite difference codes. New adiabatic hydration curves with some other initial parameters of the concrete mixture can be easily included in this model in order to expand the range of suitability of artificial neural networks to predict the adiabatic hydration curves.
Regarding project scheduling problems, resource-constrained issue is generally considered essential for contractors as a means. Researchers have thus devoted considerable efforts to investigating this issue over the past decade. Furthermore, since adequate cash flow management benefits cost control and assists profit acquisition for contractors, numerous techniques have recently been developed for project scheduling in situations involving cash flow. However, most of these studies simplified resource utilization, and assumed that cash out flows are directly related to activities without considering resource usage. Fundamentally, resources incur activities' costs, project cash flow, which conforms to resource utilization. It is thus regarded as a main issue in this study. This study establishes a resource-constrained project scheduling model based on constraint programming, whose solution can be found by using combinatorial optimization algorithms. The proposed model integrates the issues involving resource-constrained problems and cash flow, and maximizes net project cash flow to optimize project profit from the perspective of contractors. Model validation and two scenarios, including multi-resource, resource combination selection, and various constraints such as resource limit, are performed to demonstrate the model capability and applications. Contractors thus can evaluate appropriate project schedules under associated constraints, and arrange activities and resources to maximize project profit.
The transition from two-dimensional drafting to three dimensional modeling of building structures is likely to influence structural engineering design practices in numerous ways. The immediate impact in the early stages of adoption in any design practice will be an increase in productivity in design documentation. On the basis of a benchmark of hours for structural engineering design and detailing of reinforced concrete building structures, and two sets of three-dimensional modeling experiments, the potential productivity gain is conservatively estimated to be in the range from 15% and 41% of the hours required for a project due to improvements in drawing production alone. Unlike two dimensional computer-aided drafting, parametric three dimensional modeling is particularly useful at the early stages of design, where engineering skills are required. Both these effects point to an expected decline in the number of drafting staff in proportion to engineering staff. While overall hours expended will decrease, engineers may account for a greater share of the overall workload, or a new professional role – the structural modeler – may emerge.
The absence of a valid resource-constrained critical path method (CPM) not only hampers the widespread use of mainstream project scheduling software in construction management practice, but also destabilizes the very foundation of any sophisticated, CPM-based time or cost analysis in construction scheduling research. This has motivated us into developing an innovative, fully-automated solution to resource-constrained CPM called the system (short as S3). S3 takes advantage of the simplified discrete event simulation approach (SDESA) and the evolutionary optimization technique called particle swarm optimizer (PSO) to automate the formulation of a resource-constrained schedule with the shortest total project duration. We clarify basic issues of resource scheduling, elaborate on the formation of a CPM simulation model by SDESA, present PSO algorithms, and discuss the PSO solution formulation and simulation–optimization interaction in relation to the development of S3 software. In order to introduce S3 to construction schedulers, we also reference the relevant functionalities and features of Primavera Project Planner (P3) and Microsoft Project, which are applied alongside S3 in two case studies. The first case is a classic textbook example while the second case is based on a real drainage project in Hong Kong. In both cases, S3 eclipses the current CPM software with respect of (1) shortening the total project duration; (2) optimizing provisions of resources of various types; and (3) producing valid total float values to guide schedule implementation.
Overseas construction projects tend to have a high possibility of loss/failure compared to domestic projects. For this reason, risk management is becoming more emphasized and systemized in international projects so as to improve the quality of difficult decisions that normally encompass a higher level of risk exposures. Since each phase of an overseas project has different types of risks in the decision-making process, a decision support system should be tailored to satisfy the specific needs of a particular phase. In this way, various risks that arise through the life cycle of a project can be constantly checked and monitored. This study reviews basic decision-making processes in global construction projects, and presents a web-based decision support system that is closely associated with relevant risks and each cycle of sequential decisions. The system allows easier access than those of stand-alone or intranet systems. Through the proposed system, anyone can access the system anywhere in the world, anytime, with any device. Construction firms are expected to make better decision in pursuing international construction projects with a consideration of key risk factors at each stage of a project.
The Analytic Hierarchy Process (AHP) approach is widely used for multiple criteria decision-making in construction management. However, the traditional AHP requires that decision makers remain consistent in making pairwise comparisons among numerous decision criteria. Accurate expression of relative preferences on the criteria is difficult for decision makers due to the limitations of the 9-value scale of Saaty. Although Saaty proposed a method to assess the consistency of pairwise comparisons, no automatic mechanism exists for improving the consistency for AHP. This work proposes an adaptive AHP approach (A ) that uses a soft computing scheme, Genetic Algorithms, to recover the real number weightings of the various criteria in AHP and provides a function for automatically improving the consistency ratio of pairwise comparisons. A real world construction management example for determining the weightings of the multiple criteria for a best-value bid is chosen as a case study to demonstrate the applicability of the proposed A . The application results show that the proposed A is superior to the traditional AHP in terms of cost effectiveness, timeliness, and improved decision quality.
There are many nondestructive testing techniques that can be applied to assess the condition of existing concrete structures with little expenditure of human labor. The objective of the current research is to pilot-study how one can combine active infrared thermography (IRT) with elastic wave techniques. In such a manner, the fast scanning of a large structure is followed by elastic wave probing at a given small area. Concrete slabs with embedded defects are heated by means of lamps prior to acquisition of thermal images. The thermal images recorded show clear indication of hidden defects of various depths and areas. At present, the results of IRT provide only limited quantitative information regarding the depth of hidden defects in concrete. Depth of defects is readily deduced based on spectral analyses of received elastic wave signals. The fusion of information gathered from IRT and elastic waves provides effective and efficient means for inspection of the building exterior.
One of the most important phases in the construction industry (CI) is the bidding process. During the bidding process, selecting the most appropriate sub-contractors (SCs) for the relevant sub-works is highly critical for the overall project performance. In order to select the most appropriate SCs for the project and prepare the most realistic and accurate bid proposal, general contractors (GCs) have to know all financial, technical and general information about these SCs. Within this context, GCs should consider several factors in the selection process. These factors may include the quality of production, efficiency, employment of qualified members, reputation of the company, accessibility to the company, completion of the work on time etc. This paper proposes a web-based sub-contractor evaluation system called WEBSES by which the SCs can be evaluated based on a combined criterion. It enables GCs to select the most appropriate SCs for their relevant sub-works, speed up the selection process and gain time and cost savings during the bidding process.