Sustainable material selection represents an important strategy in building design. Current building materials selection methods fail to provide adequate solutions for two major issues: assessment based on sustainability principles, and the process of prioritizing and assigning weights to relevant assessment criteria. This paper proposes a building material selection model based on the fuzzy extended analytical hierarchy process (FEAHP) techniques, with a view to providing solutions for these two issues. Assessment criteria are identified based on sustainable triple bottom line (TBL) approach and the need of building stakeholders. A questionnaire survey of building experts is conducted to assess the relative importance of the criteria and aggregate them into six independent assessment factors. The FEAHP is used to prioritize and assign important weightings for the identified criteria. A numerical example, illustrating the implementation of the model is given. The proposed model provides guidance to building designers in selecting sustainable building materials. ► Sustainable material selection is an important strategy in the design of a building. ► Sustainable assessment model is developed for materials selection. ► Model validation suggests that it is valuable and suitable for use in practice.
The properties of BIM are; parametric modelling providing tabular views of components and characteristic interaction with elements, for example if a pitch roof changes so do the walls and bi-directional co-ordination enabling virtual simulations of physical construction. However, the dilemma is how to share these properties of BIM applications on one single platform. Thus creating a service that would enable the end-user to use multiple of nDs such as, 3D (three dimensional modelling), 4D (time - programming), 5D (costing) and 6D (sustainability) actions asynchronously. The prospect of using remote data servers with web service applications provides a mechanism for exchanging data openly. The main exchange format for BIM files is Industry Foundation Classes (IFCs). However, the initial problem with IFCs is that they are not intended to store and carry all relevant data for all multi-featured construction processes. Furthermore, not all relevant data can be structured in a single super schema. This papers' methodology focuses on the results of a semi-structured interview of 11 expert respondents, on using cloud computing as integration platform for BIM applications ‘Cloud BIM’. The proposed model is not to introduce a new schema in contrast to IFC but to harness the capability of IFC XML and or possibly engage with using Simplified Markup Language (SML) subsets of eXtensible Markup Language (XML) for exchanging partial data to design an integrated platform that would enhance the BIM usability experience for various disciplines in making key design decisions at a relatively early design stage. ► The methodology centres on extracting knowledge from semi-structured interviews. ► Focused on using cloud computing as an integrated platform for BIM applications. ► The service ‘Cloud BIM’ would create the use of multiple nD actions asynchronously. ► The proposed model is to engage with using SML for exchanging partial BIM data. ► Enhancing the BIM usability experience for disciplines in making design decisions.
Automated rule checking has been identified as potentially providing significant value to the AEC industry from both regulatory and industry perspectives. Key challenges to a successful rule checking implementation are the complexities inherent in the rules themselves and the breadth of conditions to which they need to apply. Due to the large number of building codes and theoretically infinite number of rules that can be defined, it is critical to systematize the rules to make the task of rule checking tractable. This paper is a first step towards classifying automated rule checking. In this paper, the authors draw upon their extensive international exposure with various building codes and rule checking areas in the AEC domain to introduce a general classification of rules across application domains using criteria that apply to all known aspects of automated rule checking. The exposure covers both academic research as well as actual production implementation done with CORENET ePlanCheck project in Singapore, and also various pilot implementations in the US and other countries. The authors offer a survey of representative examples of different classes of rules, their key concepts, potential tools required to implement them, and at least one possible solution of each example rule in each category. The examples are drawn from both research domains and existing commercial applications. The aim of this paper is to provide an initial guide for creating a framework for rule classification that articulates both the process challenges and the technology needs to address rule automation.
Emerging wireless remote sensing technologies offer significant potential to advance the management of construction processes by providing real-time access to the locations of workers, materials, and equipment. Unfortunately, little is known regarding the accuracy, reliability, and practical benefits of an emerging technology, effectively impeding widespread adoption. This paper evaluates a commercially-available Ultra Wideband (UWB) system for real-time, mobile resource location tracking in harsh construction environments. A focus of this paper is to measure the performance of the UWB technology for tracking mobile resources in real-world construction settings. To assess tracking accuracy, location error rates for select UWB track signals are obtained by automatically tracking a single entity using a Robotic Total Station (RTS) for ground truth. Furthermore, to demonstrate the benefits of UWB technology, the paper provides case studies of resource tracking for analysis of worksite operations. The work demonstrates the applicability of UWB for the design of construction management support tools. ► A commercially-available UWB system provided real-time location data in harsh environments. ► Construction resources (personnel, equipment, material) were tracked in realistic field trials. ► The accuracy of UWB system is sufficient enough in large open construction environments. ► Reliable spatio-temporal information from job sites can be automatically extracted. ► Important construction safety and work sampling problems can be resolved.
This research proposes an ontological inference process to automate the process of searching for the most appropriate work items, which is limited to tiling in this case study. The proposed ontological approach can help engineers to find work items with greater ease and consistency. Suggestions are also made for further research on ways of improving the accuracy of BIM-based quantity take-off, and developing a methodology to match between work items which are expressed as different terms; however, the proposed approach emphasizes the automation of searches using BIM data to find items suitable for building elements and materials. To enable automated inference, this study establishes (1) a work condition ontology that consists of the determinants required to select work items, (2) a work item ontology, which consists of the factors defining the tiling method, and (3) semantic reasoning rules. By conducting a case study to demonstrate the proposed ontological inference process in a real-world situation, we confirm that the proposed process can provide consistent results; however, since work items differ depending on construction type and technological advancement, the work item ontology should be continually revised and updated. The ontological inference process removes the need for the intervention of a cost estimator's subjectivity in searching for an appropriate work item. Also, if ontology is elaborately defined by the knowledge of experienced engineers, then accurate and consistent results can be obtained. In addition, the proposed process will assist cost estimators to use BIM data more easily, and it will help the expansion of BIM-based construction management.
The extent of effectiveness of real-time communication within BIM environment is somehow restrained due to the limited sense of immersion into virtual environments. The objective of this paper highlights the need for a structured methodology of fully integrating Augmented Reality (AR) technology in BIM. Based on the generic review of BIM in construction, this paper forms the rationales for the onsite information system for construction site activities, and then formulates the methods of configuring BIM + AR prototypes. It is demonstrated that, extended to the site via the “hand” of AR, the BIM solution can address more real problems, such as low productivity in retrieving information, tendency of committing error in assembly, and low efficiency of communication and problem solving.
Site layout planning is often performed on construction sites to find the best arrangement of temporary facilities so that transportation distances of on-site personnel and equipment are minimized. It could be achieved by creating dynamic layout models, which capture the changing requirements of construction sites. However, formulating such models is extremely tedious because it requires much manual data input and changes to design and construction plans are manually updated by layout planners. This study presents an automated framework of creating dynamic site layout models by utilizing information from BIM. The A* algorithm is used in conjunction with genetic algorithms to develop an optimization framework that considers the actual travel paths of on-site personnel and equipment. To address the space limitation on site, our model optimizes the dimensions of facilities and also considers interior storage within buildings under construction. A case example is demonstrated to validate this framework and shows a 13.5% reduction in total travel distance compared with conventional methods.
Insufficient interoperability resulting from complex data exchange between architectural design and building energy simulation prevents the efficient use of energy performance analyses in the early design stage. This paper presents the development of a Modelica library for Building Information Modeling (BIM)-based building energy simulation (ModelicaBIM library) using an Object-Oriented Physical Modeling (OOPM) approach and Modelica, an equation-based OOPM language. By using the ModelicaBIM library, our project investigates system interfaces between BIM and energy simulation, which can perform semi-automatic translation from the building models in BIM to building energy modeling (BEM) using a BIM's authoring tool's Application Programming Interface (API). The ModelicaBIM library consists of OOPM-based BIM classes and OOPM-based BIM structure. OOPM-based BIM classes represent building component information. OOPM-based BIM structure consists of test case models that demonstrate (i) how building information in BIM can be transformed to OOPM and (ii) how design operations in BIM, such as changing a building geometry and editing building components, can be translated into BEM. A case study for simulation result comparisons has been conducted using (i) OOPM-based BIM models in the ModelicaBIM library and (ii) LBNL Modelica Buildings library (a Modelica-based building thermal simulation library developed by Lawrence Berkeley National Laboratory). Our implementation shows that the ModelicaBIM library enables (i) objects in BIM to be translated into the OOPM-based energy models and (ii) existing OOPM library to be utilized as a simulation solver for BIM-based energy simulation.
Facilities managers need to identify failure cause–effect patterns in order to prepare corrective and preventive maintenance plans. This task is difficult because of the complex interaction and interdependencies between different building components. Standardization based on Building Information Modeling (BIM) provides new opportunities to improve the efficiency of facilities management (FM) operations by sharing and exchanging building information between different applications throughout the lifecycle of the facilities. This paper aims to utilize BIM visualization capabilities to provide FM technicians with visualizations that allow them to utilize their cognitive and perceptual reasoning for problem solving. It investigates a knowledge-assisted BIM-based visual analytics approach for failure root-cause detection in FM. For this purpose, the inspection and maintenance data of Computerized Maintenance Management System (CMMS) are integrated with a BIM. Moreover, various sources of building knowledge such as fault trees and relationships between components are formally represented. These resources are used to create custom visualizations through an interactive user interface which helps in exploiting the heuristic problem solving ability of field experts to find root causes of failures in a building.
Understanding the state, behavior, and surrounding context of construction workers is essential to effective project management and control. Exploiting the integrated sensors of ubiquitous mobile phones offers an unprecedented opportunity for an automated approach to workers' activity recognition. In addition, machine learning (ML) methodologies provide the complementary computational part of the process. In this paper, smartphones are used in an unobtrusive way to capture body movements by collecting data using embedded accelerometer and gyroscope sensors. Construction activities of various types have been simulated and collected data are used to train five different types of ML algorithms. Activity recognition accuracy analysis has been performed for all the different categories of activities and ML classifiers in user-dependent and -independent ways. Results indicate that neural networks outperform other classifiers by offering an accuracy ranging from 87% to 97% for user-dependent and 62% to 96% for user-independent categories.
The ever increasing volume of visual data due to recent advances in smart devices and camera-equipped platforms provides an unprecedented opportunity to visually capture actual status of construction sites at a fraction of cost compared to other alternatives methods. Most efforts on documenting as-built status, however, stay at collecting visual data and updating BIM. Hundreds of images and videos are captured but most of them soon become useless without properly being localized with plan document and time. To take full advantage of visual data for construction performance analytics, three aspects (reliability, relevance, and speed) of capturing, analyzing, and reporting visual data are critical. This paper 1) investigates current strategies for leveraging emerging big visual data and BIM in construction performance monitoring from these three aspects, 2) characterizes gaps in knowledge via case studies and structures a road map for research in visual sensing and analytics.
The prevalent work-related musculoskeletal disorders (WMSDs) around lower back and neck amongst construction workers are precursors of operational injury in the construction industry. As a significant risk factor of WMSDs, time spent in insecure operational postures should be proactively prevented. This study developed a real-time motion warning personal protective equipment (PPE) that enables workers' self-awareness and self-management of ergonomically hazardous operational pattern for the prevention of WMSDs based on wearable Inertial Measurement Units (WIMUs). Data processing and real-time warning algorithms are proposed for automatically risk postures assessment and warning through a connected smartphone application as soon as dangerous operational patterns are detected. The system was tested and validated with robust clinical motion data output and effective alarm ringing in both laboratory and field experiments on a construction site in Hong Kong. The proposed PPE provides an alternative to help construction workers prevent WMSDs without disturbance and distraction in operations.
Designing with building performance simulation feedback in the early design stage has existed since the early days of computational modeling. However, as a consequence of a fragmented building industry building performance simulations (BPSs) in the early design stage are closely related to who is creating and operating the BPS models. This paper critically reviews the different ways designers and analysts use BPS in the early design stage. One of the key findings is that most tools and methods used in the early design stages are insufficient to provide valid feedback while in the same time being flexible enough to accommodate a rapid changing design process. The main concern points to the way geometrical models and analytical models are combined and how this affects the way the buildings are designed and perform. This paper concludes that integrated dynamic models may combine a design tool, a visual programming language and a BPS to provide better support for the designer during the early stages of design as opposed to alternatives such as the current implementation of IFC or gbXML or the unaccompanied use of simulation packages.
The potential of Building Information Modeling (BIM) to support a transformation of the processes of design and construction has been evident in the construction industry. Although BIM is considered helpful in improving design quality by eliminating conflicts and reducing rework, there has been little research into using BIM throughout the project for construction quality control and efficient information utilization. Due to the consistency of design data with quality data and construction process with quality control process, the potential of BIM implementation in quality management lies in its ability to present multi-dimensional data including design data and time sequence. This paper explores and discusses the advantages of 4D BIM for a quality application based on construction codes, by constructing the model in a product, organization and process (POP) data definition structure. A case study is provided to validate the use of the proposed 4D BIM application for quality control during the construction phase of the Wuhan International EXPO Center.
The use of Building Information Modelling (BIM) has increased in recent years, mostly due to the potential of the methodology for improving construction project performance and efficiency. With a view to achieving a better understanding of the research work on this subject, this paper conducts a bibliometric analysis and a review of existing literature on BIM focusing on the last decade. The authors selected the articles published in journals with an impact factor higher then 1.0, as well as the top 100 most cited articles. The search resulted on 381 articles, which were then categorised in order to systematise the research conducted over the years. The authors have not only analysed the existing literature but also highlighted new emerging fields in BIM research, being possible to identify Collaborative Environments and Interoperability, Sustainable Construction, BIM Adoption & Standardisation, and BIM Programming as the categories with the most significant growth in the last years. It was also observed that the most researched topics were related with the development of BIM tools, the study of BIM adoption worldwide, the energy simulation using BIM-based information and, more recently, with the semantic interoperability and ontology. On the other hand, the study on BIM at the academic level is very small, as well as parametric modelling and quantity take-off. (C) 2017 Elsevier B.V. All rights reserved.
The use of prefabrication offers significant advantages, yet appropriate criteria for applicability assessments to a given building have been found to be deficient. Decisions to use prefabrication are still largely based on anecdotal evidence or simply cost-based evaluation when comparing various construction methods. Holistic criteria are needed to assist with the selection of an appropriate construction method in concrete buildings during early project stages. Following a thorough literature review and comprehensive comparisons between prefabrication and on-site construction method, a total of 33 sustainable performance criteria (SPC) based on the triple bottom line and the requirements of different project stakeholders were identified. A survey of U.S. experienced practitioners including clients/developers, engineers, contractors, and precast concrete manufacturers was conducted to capture their perceptions on the importance of the criteria. The ranking analysis of survey results shows that social awareness and environmental concerns were considered as increasingly important in construction method selections. Factor analysis reveals that these SPCs can be grouped into seven dimensions, namely, economic factors: “long-term cost,” “constructability,” “quality,” and “first cost”; social factors: “impact on health and community,” “architectural impact”; and environmental factor: “environmental impact.” The resultant list of SPCs provides team members a new way to select a construction method, thereby facilitating the sustainable development of built environment.
Professional, organisational and educational institutions have started to adopt BIM software tools and adapt their existing delivery systems to satisfy evolving market requirements. To enable individuals within these organisations to develop their BIM abilities, it is important to identify the BIM competencies that need to be learned, applied on the job, and measured for the purposes of performance improvement. Expanding upon previous research, this paper focuses on , the building blocks of organisational capability. The paper first introduces several taxonomies and conceptual models to clarify how individual competencies may be , , and . Competency items are then fed into a specialised to generate flexible assessment tools, learning modules and process workflows. Finally, the paper discusses the many benefits this competency-based approach brings to industry and academia, and explores future conceptual and tool development efforts to enable industry-wide BIM performance assessment and improvement.
Building Information Modeling (BIM) has been recognized as an emerging technological innovation which can help transform the construction industry and it has been adopted broadly in the field of built environment. Due to the rapid development of BIM research, various stakeholders require a state-of-the-art review of the BIM research and implementation. The purpose of this paper is to provide an objective and accurate summary of BIM knowledge using 1874 published BIM-related papers. The results show that 60 key research areas, such as information systems, 3D modeling, design and sustainability and 10 key research clusters, such as architecture design studio, building information and lean construction, are extremely important for the development of BIM knowledge. The results are useful for the identification of research clusters and topics in the BIM community. More importantly, these results can help highlight how BIM-related research evolves over time, thus greatly contributing to understanding the underlying structure of BIM. This study offers useful and new insights to summarize the status quo of BIM knowledge and can be used as a dynamic platform to integrate future BIM developments.
The ability to locate people quickly and accurately in buildings is critical to the success of building fire emergency response operations, and can potentially contribute to the reduction of various building fire-caused casualties and injuries. This paper introduces an environment aware beacon deployment algorithm designed by the authors to support a sequence based localization schema for locating first responders and trapped occupants at building fire emergency scenes. The algorithm is designed to achieve dual objectives of improving room-level localization accuracy and reducing the effort required to deploy an ad-hoc sensor network, as the required sensing infrastructure is presumably unavailable at most emergency scenes. The deployment effort is measured by the number of beacons to deploy, and the location accessibility to deploy the beacons. The proposed algorithm is building information modeling (BIM) centered, where BIM is integrated to provide the geometric information of the sensing area as input to the algorithm for computing space division quality, a metric that measures the likelihood of correct room-level estimations and associated deployment effort. BIM also provides a graphical interface for user interaction. Metaheuristics are integrated to efficiently search for a satisfactory solution in order to reduce the computational time, which is crucial for the success of emergency response operations. The algorithm was evaluated by simulation, where two building fire emergency scenarios were simulated. The tabu search, which employs dynamically generated constraints to guide the search for optimum solutions, was found to be the most efficient among three tuned tested metaheuristics. The algorithm yielded an average room-level accuracy of 87.1% and 32.1% less deployment effort on average compared with random beacon placements. The robustness of the algorithm was also examined as the deployed ad-hoc sensor network is subject to various hazards at emergency scenes. Results showed that the room-level accuracy could remain above 80% when up to 54% of all deployed nodes were damaged. The tradeoff between the space division quality and deployment effort was also examined, which revealed the relationship between the total deployment effort and localization accuracy.
Most construction worker education and training environments apply traditional teaching methods to educate workers about hazards and productivity in the workplace. Many rely on using conventional teacher–student classroom settings, but there are few effective interactive methods applied which can objectively engage trainer and trainees and assess their performance during and after training sessions. Presented is a novel approach towards integrating real-time location tracking and three-dimensional immersive data visualization technologies in existing construction worker education and training environments. The scope is limited to steel-erection tasks performed by union ironworkers in an indoor training center. Results to analysis and visualization of the gathered data from training session are shown. The potential for assessing and improving the trainers' and apprentices' safety and productivity performance is explained. Since such technologies have hardly been used as part of existing construction education and training techniques, the opportunities including return on investment and user feedback were studied. The results show that unsafe practices in worker training environments can be detected and visualized and furthermore their training effectiveness can be indirectly measured.