While BIM processes are established for new buildings, the majority of existing buildings is not maintained, refurbished or deconstructed with BIM yet. Promising benefits of efficient resource management motivate research to overcome uncertainties of building condition and deficient documentation prevalent in existing buildings. Due to rapid developments in BIM research, involved stakeholders demand a state-of-the-art overview of BIM implementation and research in existing buildings. This paper presents a review of over 180 recent publications on the topic. Results show scarce BIM implementation in existing buildings yet, due to challenges of (1) high modeling/conversion effort from captured building data into semantic BIM objects, (2) updating of information in BIM and (3) handling of uncertain data, objects and relations in BIM occurring in existing buildings. Despite fast developments and spreading standards, challenging research opportunities arise from process automation and BIM adaption to existing buildings' requirements.
There often is a significant difference between predicted (computed) energy performance of buildings and actual measured energy use once buildings are operational. This article reviews literature on this ‘performance gap’. It discerns three main types of gap: (1) between first-principle predictions and measurements, (2) between machine learning and measurements, and (3) between predictions and display certificates in legislation. It presents a pilot study that attempts an initial probabilistic probe into the performance gap. Findings from this pilot study are used to identify a number of key issues that need to be addressed within future investigations of the performance gap in general, especially the fact that the performance gap is a function of time and external conditions. The paper concludes that the performance gap can only be bridged by a broad, coordinated approach that combines model validation and verification, improved data collection for predictions, better forecasting, and change of industry practice.
Unmanned Aerial Vehicle (UAV) systems as a data acquisition platform and as a measurement instrument are becoming attractive for many surveying applications in civil engineering. Their performance, however, is not well understood for these particular tasks. The scope of the presented work is the performance evaluation of a UAV system that was built to rapidly and autonomously acquire mobile three-dimensional (3D) mapping data. Details to the components of the UAV system (hardware and control software) are explained. A novel program for photogrammetric flight planning and its execution for the generation of 3D point clouds from digital mobile images is explained. A performance model for estimating the position error was developed and tested in several realistic construction environments. Test results are presented as they relate to large excavation and earth moving construction sites. The experiences with the developed UAV system are useful to researchers or practitioners in need for successfully adapting UAV technology for their application(s).
Construction safety is a national and worldwide issue. This paper contributes in solving this problem by applying automated safety rule checking to Building Information Models (BIM). Algorithms that automatically analyze a building model to detect safety hazards and suggest preventive measures to users are developed for different cases involving fall related hazards. As BIM is changing the way construction can be approached, the presented work and case studies extend BIM to include automated hazard identification and correction during construction planning and in certain cases, during design. A rule-based engine that utilizes this framework is implemented on top of a commercially available BIM platform to show the feasibility of the approach. As a result, the developed automated safety checking platform informs construction engineers and managers by reporting, why, where, when, and what safety measures are needed for preventing fall-related accidents before construction starts. The safety area reviewed is fall protection. An example case study of such a system is also provided. ► Construction safety remains a national and world-wide issue. ► Rule-based engine detects safety hazards and suggests preventive measures to users. ► Algorithms for automated safety rule checking in Building Information Models (BIM). ► Different case studies involving fall related hazards are presented. ► Results show why, where, when, what safety measures are needed in constr. planning.
In the Architecture, Engineering, and Construction (AEC) domain, semantically rich 3D information models are increasingly used throughout a facility's life cycle for diverse applications, such as planning renovations, space usage planning, and managing building maintenance. These models, which are known as building information models (BIMs), are often constructed using dense, three dimensional (3D) point measurements obtained from laser scanners. Laser scanners can rapidly capture the “as-is” conditions of a facility, which may differ significantly from the design drawings. Currently, the conversion from laser scan data to BIM is primarily a manual operation, and it is labor-intensive and can be error-prone. This paper presents a method to automatically convert the raw 3D point data from a laser scanner positioned at multiple locations throughout a facility into a compact, semantically rich information model. Our algorithm is capable of identifying and modeling the main visible structural components of an indoor environment (walls, floors, ceilings, windows, and doorways) despite the presence of significant clutter and occlusion, which occur frequently in natural indoor environments. Our method begins by extracting planar patches from a voxelized version of the input point cloud. The algorithm learns the unique features of different types of surfaces and the contextual relationships between them and uses this knowledge to automatically label patches as walls, ceilings, or floors. Then, we perform a detailed analysis of the recognized surfaces to locate openings, such as windows and doorways. This process uses visibility reasoning to fuse measurements from different scan locations and to identify occluded regions and holes in the surface. Next, we use a learning algorithm to intelligently estimate the shape of window and doorway openings even when partially occluded. Finally, occluded surface regions are filled in using a 3D inpainting algorithm. We evaluated the method on a large, highly cluttered data set of a building with forty separate rooms. ► We present an automated method to convert 3D point data into information model for buildings. ► Our method identifies and models the main structural components of a building. ► Our method is robust to the presence of significant clutter and occlusion. ► We evaluate our method on a large, highly cluttered data set of a building with 40 rooms. ► We show promising results on this large dataset.
Building information models (BIMs) are maturing as a new paradigm for storing and exchanging knowledge about a facility. BIMs constructed from a CAD model do not generally capture details of a facility as it was actually built. Laser scanners can be used to capture dense 3D measurements of a facility's as-built condition and the resulting point cloud can be manually processed to create an as-built BIM — a time-consuming, subjective, and error-prone process that could benefit significantly from automation. This article surveys techniques developed in civil engineering and computer science that can be utilized to automate the process of creating as-built BIMs. We sub-divide the overall process into three core operations: geometric modeling, object recognition, and object relationship modeling. We survey the state-of-the-art methods for each operation and discuss their potential application to automated as-built BIM creation. We also outline the main methods used by these algorithms for representing knowledge about shape, identity, and relationships. In addition, we formalize the possible variations of the overall as-built BIM creation problem and outline performance evaluation measures for comparing as-built BIM creation algorithms and tracking progress of the field. Finally, we identify and discuss technology gaps that need to be addressed in future research.
Substantial impacts through BIM implementation may be achieved throughout all stages of the construction process. The paper measures BIM use throughout the project lifecycle, confirming BIM is most often used in the early stages with progressively less use in the latter stages. This research demonstrates via 92 responses from a sample of BIM users that collaboration aspects produce the highest positive impact. The process aspects are more important than the software technology. BIM necessitates investment in software and training however, smaller practices can afford it. Stakeholder financial benefits are ranked concluding that clients benefit most financially from BIM followed by Facilities Managers. Despite this, over 70% do not provide a 3D model and Cobie dataset at the conclusion of a project. Identification of Key Performance Indicators currently being used for BIM is provided and findings indicate a lack of industry expertise and training providing an opportunity for education providers.
3-D printing, which is an automated production process with layer-by-layer control, has been gaining rapid development in recent years. The technology has been adopted in the manufacturing industry for decades and has recently been introduced in the construction industry to print houses and villas. The technology can bring significant benefits to the construction industry in terms of increased customization, reduced construction time, reduced manpower, and construction cost. A few isolated products and projects have been preliminarily tested using the 3-D printing technology. However, it should be noted that such tests and developments on the use of 3-D printing in the construction industry are very fragmented at the time of the study. It is therefore necessary for the building and construction industry to understand the technology, its historical applications and challenges for better utilization in the future. A systematic review shows that 3-D printing technology, after years of evolution, can be used to print large-scale architectural models and buildings. However, the potential of the technology is limited by the lack of large-scale implementation, the development of building information modeling, the requirements of mass customization, and the life cycle cost of the printed projects. It is therefore expected that future studies should be conducted on these areas to consolidate the stability and expand the applicability of 3-D printing in the construction industry.
As a term and method that is rapidly gaining popularity, Building Information Modeling (BIM) is under the scrutiny of many building professionals questioning its potential benefits on their projects. A relevant and accepted calculation methodology and baseline to properly evaluate BIM's benefits have not been established, thus there are mixed perspectives and opinions of the benefits of BIM, creating a general misunderstanding of the expected outcomes. The purpose of this paper was to develop a more complete methodology to analyze the benefits of BIM, apply recent projects to this methodology to quantify outcomes, resulting in a more a holistic framework of BIM and its impacts on project efficiency. From the literature, a framework calculation model to determine the value of BIM is developed and presented. The developed model is applied via case studies within a large industrial setting where similar projects are evaluated, some implementing BIM and some with traditional, non-BIM approaches. Cost or investment metrics were considered along with benefit or return metrics. The return metrics were: requests for information, change orders, and duration improvements. The investment metrics were: design and construction costs. The methodology was tested against three separate cases and results on the returns and investments are presented. The findings indicate that in the tool installation department of semiconductor manufacturing, there is a high potential for BIM benefits to be realized. Actual returns and investments will vary with each project. ► We examine the literature and case studies to understand the background of BIM. ► We gather quantifiable performance data from BIM and Non-BIM projects. ► We analyze the investments and returns of BIM utilization via three case studies. ► BIM had a positive impact on semiconductor manufacturing construction. ► A framework for measurement of BIM's impact is developed.
The innovation of building information modelling (BIM) technology provides a new means of predicting, managing and monitoring the environmental impacts of project construction and development through virtual prototyping/visualisation technology. This paper aims to provide thought-provoking insights into the shortcomings in the scope of the existing green BIM literature, and outlines the most important directions for future research. A total of 84 green-BIM-related papers have been reviewed and compared. Most green BIM research, centres on environmental performance at the design (44 papers) and construction stages (25 papers) of building lifecycles. Few studies concentrated on the development of BIM-based tools for managing environmental performance during the building maintenance, retrofitting (8 papers), and demolition (12 papers) stages. It is suggested that a ‘one-stop-shop’ BIM for environmental sustainability monitoring and management over a building's full life cycle should be considered in future research. Future green BIM tools should also include the three R's concept (reduce, reuse and recycle) in their sustainability analysis for both new development and retrofitting projects. The system should offer better integration with facility operation maintenance manuals for more effective low-carbon management. The use of cloud-based BIM technology to enable the management of building sustainability using ‘big data’ is also needed. Despite these potential developments, it is argued that the lack of computer tools and the complications of the BIM models are hindering the adoption of green BIM.
Organizational and people centered issues pose the greatest challenge for Building Information Modeling (BIM) implementation. Studies showed that BIM implementation is still a challenge for the North American construction industry. The Canadian construction industry, in contrast, is well behind that of the U.S. in its BIM adoption rate. Maturity and adoption of BIM depends mainly on the client or the owner in construction projects. Public sector clients often think that the market is not ready for BIM and are afraid to increase project costs by limiting competition. Moreover, if the contractor is not integrated in the project in the design phase, BIM has limited power. This paper proposes a ‘BIM partnering’ based public procurement framework to ensure ‘best value’ in construction projects. The case study presented in the paper proved the feasibility of proposed BIM based procurement in publicly-funded construction projects. The suggested contractual arrangement for the project resulted in improved productivity, better coordination, and reduced error, and rework. ► This paper presents a public construction procurement framework through BIM-Partnering. ► This framework aligns with current contractual and project delivery methods. ► It proposes a virtual design environment with an unprecedented level of collaboration.
Building Information Modelling (BIM) is one of the important areas in current Virtual Reality (VR) research. VR research considers not only the technological development, a very important part of the research also concerns the application of the technologies and their adoption by the practices. This paper firstly presents an analysis of the current state of BIM in the Architecture, Engineering and Construction (AEC) industry and a re-assessment of its role and potential contribution in the near future. The paper analyses the readiness of the industry with respect to the (1) product, (2) processes and (3) people, to position BIM adoption in terms of current status and expectations across disciplines. The findings indicate that there were both technical and non-technical issues that need consideration. The evidence also suggests that there are varying levels of adoption and therefore the need for a specific tool to facilitate BIM adoption. The study revealed that even the market leaders who are early technology adopters in the Australian industry in many cases have varying degrees of practical experiential knowledge of BIM and hence at times different understandings and different levels of confidence regarding the future diffusion of BIM technology throughout the industry. There have been numerous factors affecting BIM adoption, which can be grouped into two main areas: technical tool functional requirements and needs, and non-technical strategic issues. There are varying levels of adoption and understanding within countries — from discipline to discipline and client to client. There are also varying levels of adoption from country to country and although many researchers and practitioners espouse collaborative working environments there are still challenges to be met in many parts of the world, particularly, in relation to a fully integrated collaborative multidisciplinary mode of operation. The challenges for the research community lie not only in addressing the technical solutions or addressing human centred issues but it is also in creating the enabling environment of a decision framework, which integrates both the technical and non-technical challenges. The need for guidance on where to start, what tools are available and how to work through the legal, procurement and cultural challenges was evidenced in the exploratory study. Therefore the Collaborative BIM Decision Framework has been initiated to facilitate the BIM adoption in the AEC industry, based upon these industry concerns, which consists of four interrelated key elements. The findings are drawn from a major research project funded by the Australian Cooperative Research Centre for Construction Innovation (CRC-CI), with a focus on the Australian context. ► BIM adoption needs consideration of both technical tool functional requirements and non-technical strategic issues. ► The Collaborative BIM Decision Framework is initiated to support the facilitation of the BIM adoption in the AEC industry.
Building Information Modelling (BIM) is an expansive knowledge domain within the Architecture, Engineering, Construction and Operations (AECO) industry. To allow a systematic investigation of BIM's divergent fields, its knowledge components must be defined and expanding boundaries delineated. This paper explores some of the publicly available international guidelines and introduces the BIM Framework, a research and delivery foundation for industry stakeholders. This is a ‘scene-setting’ paper identifying many conceptual parts (fields, stages, steps and lenses), providing examples of their application and listing some of the Framework's deliverables. This paper also identifies and deploys visual knowledge models and a specialised ontology to represent domain concepts and their relations.
Additive manufacturing in construction is beginning to move from an architect's modelling tool to delivering full-scale architectural components and elements of buildings such as walls and facades. This paper discusses large-scale additive manufacturing processes that have been applied in the construction and architecture arena and focuses on ‘Concrete Printing’, an automated extrusion based process. The wet properties of the material are critical to the success of manufacture and a number of new criteria have been developed to classify these process specific parameters. These criteria are introduced and key challenges that face construction scale additive manufacturing are presented. ► Built a full-scale of extrusion-based additive manufacturing (AM) machine for Freeform Construction. ► Developed a high performance concrete for Concrete Printing process. ► Created a variety of prototype parts, including the world's first reinforced concrete AM component — WonderBench.
There is a growing need for tools automating the processing of as-built 3D laser scanned data, and more particularly the comparison of this as-built data with planned works. This paper particularly considers the case of tracking MEP components with circular cross-sections, which essentially include pipes, and some conduits and ducts. Discrepancies between the as-built and as-planned status of pipes, conduit and ductwork result from changes that occur in the field and that are either unnoticed (human error) or not reflected in the 3D model. Previous research has shown that the Hough transform, with judiciously applied domain constraints, is a practical and cost-effective approach to find, recognize and reconstruct cylindrical MEP works within point clouds automatically. Previous research has also shown that “Scan-vs-BIM” systems that are based on the geometric alignment and comparison of as-built laser scans with as-designed BIM models can effectively recognize and identify MEP components as long as they are constructed near their as-planned locations. The research presented in this paper combines the two techniques in a unified approach for more robust automated comparison of as-built and as-planned cylindrical MEP works, thereby providing the basis for automated earned value tracking, automated percent-built-as-planned measures, and assistance for the delivery of as-built BIM models from as-designed ones. The proposed approach and its improved performance are validated using data acquired from an actual construction site. The results are very encouraging and demonstrate the added value of the proposed integrated approach over the rather simpler Scan-vs-BIM system. The two main areas of improved performance are: (1) the enabled recognition and identification of objects that are not built at their as-planned locations; and (2) the consideration for pipe completeness in the pipe recognition and identification metric.
Building information modeling (BIM) refers to a combination or a set of technologies and organizational solutions that are expected to increase interorganizational and disciplinary collaboration in the construction industry and to improve the productivity and quality of the design, construction, and maintenance of buildings. In this paper we analyze first the rhetorical–promotional dimension of the BIM implementation sometimes characterized as a “BIM utopia.” Second, we analyze the views of the enhancement of BIM implementation. Although BIM visions and promises are needed for BIM implementation, they need to be complemented with a more realistic view of conditions of the implementation. For this we outline an activity–theoretical and evolutionary view by drawing conceptual tools from science and technology studies and other relevant social scientific literature. According to this view, in addition to standards and guidelines underlined by normative approaches, local experimentation and continuous learning play a central role in the implementation of BIM.
There is a paucity of literature that examines building information modelling (BIM) for asset management within the architecture, engineering, construction and owner-operated (AECO) sector. This paper therefore presents a thorough review of published literature on the latest research and standards development that impact upon BIM and its application in facilities management (FM) during the operations and maintenance (O&M) phase of building usage. The purpose is to generate new ideas and provide polemic clarity geared to intellectually challenge readers from across a range of academic and industrial disciplines. The findings reveal that significant challenges facing the FM sector include the need for: greater consideration of long-term strategic aspirations; amelioration of data integration/interoperability issues; augmented knowledge management; enhanced performance measurement; and enriched training and competence development for facilities managers to better deal with the amorphous range of services covered by FM. Future work is also proposed in several key areas and includes: case studies to observe and report upon current practice and development; and supplementary research related to concepts of knowledge capture in relation to FM and the growing use of BIM for asset management.
In the recent years, building information modeling (BIM) has transformed the architecture, engineering, and construction industry, and attracted attentions from both researchers and practitioners. However, few studies have attempted to map the global research on BIM. This study conducts a scientometric review of global BIM research in 2005–2016, through co-author analysis, co-word analysis and co-citation analysis. A total of 614 bibliographic records from the Web of Science core collection database were analyzed. The results indicated that Charles M. Eastman received the most co-citations and that the most significant development in BIM research occurred primarily in the USA, South Korea and China. Additionally, BIM research has primarily focused on the subject categories of engineering, civil engineering and construction & building technology, and the keywords “visualization” and “industry foundation classes (IFC)” received citation bursts in the recent years. Furthermore, 10 co-citation clusters were identified, and the hot topics of BIM research were: mobile and cloud computing, laser scan, augmented reality, ontology, safety rule and code checking, semantic web technology, and automated generation. This study provides researchers and practitioners with an in-depth understanding of the status quo and trend of the BIM research in the world.
An increasing number of information management and information exchange applications in construction industry is relying on semantic web technologies or tools from the Linked Open Data (LOD) domain to support data interoperability, flexible data exchange, distributed data management and the development of reusable tools. These goals tend to be overlapped with the purposes of the Industry Foundation Classes (IFC), which is a standard for the construction industry defined through an EXPRESS schema. A connecting point between semantic web technologies and the IFC standard would be represented by an agreed Web Ontology Language (OWL) ontology for IFC (termed ifcOWL) that allows to (1) keep on using the well-established IFC standard for representing construction data, (2) exploit the enablers of semantic web technologies in terms of data distribution, extensibility of the data model, querying, and reasoning, and (3) re-use general purpose software implementations for data storage, consistency checking and knowledge inference. Therefore, in this paper we will look into existing efforts in obtaining an ifcOWL ontology from the EXPRESS schemas of IFC and analyse which features would be required in a usable and recommendable ifcOWL ontology. In making this analysis, we present our implementations of an EXPRESS-to-OWL converter and the key features of the resulting ifcOWL ontology.
Building Information Modeling (BIM) has emerged as one of the key streams in construction and civil engineering research within the last decade. Given this interest in BIM and the rapidly increasing volume of BIM literature, it is important to understand and discern the core themes and trends emerging in BIM research, and its implications for broader research. The previously reported studies to identify the core of BIM research are typically subjective and qualitative, and hence, prone to bias and interpretation of a limited number of reviewed papers. There is a lack of comprehensive, quantified and systematic classification of the BIM literature. This research brings some clarity by synthesizing and labeling a large corpus of BIM research studies published from 2004 through 2014. Latent Semantic Analysis (LSA), a natural language processing technique was applied to the abstracts of 975 academic papers. This objective analysis reveals twelve principal research areas. Various specific research themes associated with each principal area have been identified. These principal research areas and research themes indicate the patterns and trends in BIM research.