Machine learning-based decision support framework for BIM component specification

This article considers building information modeling (BIM) maturity levels as an ability to operate BIM technology both at an individual project and across the enterprise. The main indicator of BIM implementation maturity is the level of technological and organizational changes in a company. 3 levels of BIM maturity according to BIM Task Group are shown. This article shows some basic criteria of effective BIM-technology implementation. The core transformation is process reengineering, which gives a vector to all subsequent changes including conversion of organizational structure and material and technical equipment. In this regard, the early stages of BIM implementation major cost falls on process reengineering, especially on the transition from CAD to BIM. The radical conversion of work processes entails a review of the staff of the company in terms of the structure and qualification. Other types of BIM implementation investments for the subsequent stages of the project consist of the costs on structural changes, staff education, technical provision and infrastructure development. In order to estimate the investment in the process of implementing BIM all of the costs must be presented in monetary equivalent. This process is complicated by the necessity of converting high-quality information and time parameters, so it is advisable to appeal to the expert evaluation of the data. In addition to monetary costs of the implementation process there are some immeasurable ones. It is vital to take into account the losses associated with the absence of employees in the workplace at the time of re-education, as well as the costs of the process of evaluating the effectiveness of BIM.

Facility management (FM) accounts for more than two thirds of the total cost of the whole life cycle of a building. FM staff do have inadequate visualization and often have difficulty in querying information using 2D drawings and traditional facility management systems. Currently, building information modeling (BIM) is increasingly applied to FM in the operations and maintenance (O&M) stage. BIM represents the geometric and semantic information of building facilities in 3D object-based digital models and enables facility managers to manage building facilities better in the O&M stage. At the same time, the Internet of Things (IoT) technology can be used to acquire operational data of building facilities and real-time environmental data to support FM. However, few studies have used BIM and IoT technologies together for automated management and maintenance of building facilities. Around 65%~80% of the FM comes from facility maintenance management (FMM). However, there is a lack of efficient maintenance strategies and appropriate decision making approaches that can reduce FMM costs. Facility managers usually undertake reactive maintenance or preventive maintenance strategies in the O&M stage. However, reactive maintenance cannot prevent failures and preventive maintenance cannot predict the future condition of building components, which leads to maintenance actions being performed after failure has occurred and it cannot keep the functionality of a building consistent. This study aims to apply a predictive maintenance strategy with BIM and IoT technologies to overcome these limitations. In addition, there is an information interoperability problem among BIM, IoT and the FM system. Therefore, this study aims to leverage the BIM and IoT technologies to improve the efficiency of FMM and to address the information interoperability problem of integrating BIM, IoT and the FM system. In order to improve the efficiency of FMM, an FMM framework is proposed based on BIM and facility management systems (FMSs), which can provide automatic scheduling of maintenance work orders (MWOs) to enhance good decision making in FMM. In this framework, data are mapped between BIM and FMSs according to the developed Industry Foundation Classes (IFC) extension of maintenance tasks and MWO information in order to achieve data integration. Geometric and semantic information of the failure components is extracted from the BIM models in order to calculate the optimal maintenance path in the BIM environment. Moreover, the MWO schedule is automatically generated using a modified Dijkstra algorithm that considers four factors, namely, problem type, emergency level, distance among components, and location. In order to provide a better maintenance strategy for building facilities, a data-driven predictive maintenance framework based on BIM and IoT technologies for FMM has been developed. The framework consists of an information layer and an application layer. Data collection and data integration among the BIM models, FM system, and IoT system are undertaken in the information layer, while the application layer contains four modules to achieve predictive maintenance, namely: (1) condition monitoring and sensor data acquisition, (2) condition assessment module, (3) condition prediction module, and (4) maintenance planning module. In addition, machine learning algorithms, i.e. artificial neural network (ANN) and support vector machine (SVM), are used to predict the future condition of building components. For the information interoperability problem among BIM, IoT and FM system, an ontology-based methodology framework is proposed for data integration among the BIM, IoT and FM domains. The ontology-based approach is developed as a tool to facilitate knowledge management in BIM- and IoT-based FMM and improve the data integration process. First, three ontologies are developed for BIM, IoT, and FMM respectively according to the ontology development process and facility information requirement. Second, an ontology mapping method is designed to integrate the three developed ontologies based on mapping rules. Moreover, ontology reasoning rules are developed based on description logics to infer implicit facts from the integrated ontology and support quick information querying on FMM. The developed framework is validated through an illustrative example. This research provides an automatic work order scheduling approach in FMM and predictive maintenance strategy for building facilities, thereby enabling great saving in time and labor costs for facility staff. In addition, the proposed ontology-based methodology can address the information interoperability problem and integrate data from BIM, IoT and FM system for facility maintenance activities. In the future, the ontology-based methodology will be applied for the operation management of building facilities.

A review and outlook for integrated BIM application in green building assessment

Managing maintenance cost data is one of the issues due to difficulties in identifying the accurate cost for maintenance and repair of specific components. This is because of the accounting systems used by majority of building managers. The introduction of Building Information Modeling (BIM) as a tool for facilitating information and knowledge sharing through digital representation of the physical and functional characteristics of a facility has seen wide application in the construction industry, spanning over the entire life cycle of a facility, i.e., planning, design, pre-construction, construction and post-construction. In post-construction stage, BIM is used for transferring the data of building (spaces, systems and components) into maintenance management operations, keeping track of building assets, and enable scheduled maintenance and provides information of building maintenance history. However, the current BIM rather complex and requires a huge amount of data to develop, which make the system is difficult to adopt for the existing buildings. This study therefore aims to investigate the implementation of BIM for Operation and Maintenance Management (O&M) in Malaysia by identifying the information that should be prioritized to enable BIM mobile application at O&M phase. The study makes used of qualitative methods of data collection and analysis. Three (3) rounds of expert discussion using Delphi techniques were carried out with 10 to 15 selected respondents (experts in O&M and BIM). The framework validated by a case study via on-site data collection, which used site measurement, building modelling using appropriate software i.e., Revit and AutoCAD. Most of the experts agreed that technology could improve the efficiency of service delivery and interested in implementing BIM in O&M practices. Simplified BIM for O&M that consists of the critical information includes location, dimension asset information, asset capacity, specification, manufacturer, statutory, condition and cost was developed. For the O&M element and items, information varies and can be modified according to the needs. All this information was systematically organized in a data matrix. A simplified BIM model has been developed to demonstrate how the information is stored, shared, and utilised. Majority of the stakeholders agreed that the Simplified BIM system is useful, flexible, least complex, and effective in managing and monitoring maintenance operations of their building.

Developing a physical BIM library for building thermal energy simulation

Project management in office: BIM implementation

Building Information Modelling (BIM) is a new process that is spreading in the Architecture, Engineering and Construction field. It allows the creation of virtual building models, which can be linked to numerical data, texts, images, and other types of information. Building components, such as walls, floors, etc. are modelled as “smart objects”, i.e. they are defined by numerical parameters, such as dimensions, and are embedded with other kinds of information, such as building materials and properties. Stored data are accessible and modifiable by all different professionals involved in the same project. The BIM process has been developed for new buildings, and it allows to plan and manage the whole building life-cycle. BIM for built heritage has started to be researched recently, and its use is still not widespread. Indeed, built heritage is characterised by complex morphology and non-homogeneous features, which clash with BIM’s standardised procedures. Moreover, to date, BIM does not allow fully automated procedures to model heritage buildings. This review focuses on the survey and digitisation phases, which can be seen as the initial phases of application of BIM in conservation projects. It also briefly covers the modelling stage. Here we present the main methodologies developed for BIM for built heritage. Issues about digitisation are also highlighted, principally in connection with the unavailability of automated processes. During the last 10 years, research has led to promising results; for example, videogame interfaces have been used to simulate virtual 3D tours that display in a single interface the 3D model and the database containing metadata, and new software plug-ins have been developed, to easily create “smart objects”. Nevertheless, further research is needed to establish how BIM can support the practice of building conservation. There is a gap in BIM’s information holding capacities, namely the storage of cultural and historical documentation, as well as monitored and simulated data relevant for preventive conservation. Future work should focus on the development of new tools that will be able to store and share all the relevant metadata.

Building information modeling (BIM) aims to facilitate information management and collaboration among stakeholders in different domains over the building life cycle. BIM models are increasingly used as an object-based information hub for storing, integrating and managing building information in different aspects. Over the building life cycle, stakeholders like the owner, designers and subcontractors keep reviewing and commenting on different building components, but these social interactions are often not recorded and managed in a structured manner. This paper presents a distributed cloud-based BIM framework that was designed to support collaboration among project participants and information sharing. The framework, namely BIMCloud, was developed based on Apache Cassandra which can be deployed on public cloud servers like Amazon EC2 or private cloud servers hosted in own infrastructures. A schematic data structure was also developed to capture the building component-based social interactions, which could be used for mining and post-processing to generate knowledge in the future. The BIMCloud framework stores BIM models based on the IFC schema and the developed schema for Social BIM. Therefore, people can make changes to the BIM models in the BIMCloud framework by transferring only a partial BIM model. An example scenario is presented in this paper.

Building Information Modelling (BIM) is a methodology that can support such vision. The European Commission has also promoted the integration of BIM's data rich models and processes with sustainable methodologies that represent life-cycle thinking, such as life-cycle assessment (LCA). This chapter discusses the BIM–LCA integration process and explores integration and interoperability challenges, the actors that are involved in this process and how they can contribute to the success of BIM-LCA integration. The interoperability of BIM–LCA integration is of major importance, as the success of such a tool would depend on information transparency and the user's ability to manipulate the original information to fit their goals. A good example is the Australian National Specification System (NATSPEC) Guide, which includes the NATSPEC National BIM Guide and the NATSPEC BIM object/element matrix, providing suggestions for digital building information exchange.

As the Architecture, Engineering, Construction, and Facilities Management industry undergoes a profound change with Building Information Modeling (BIM), it seems the right moment to properly re-structure the inherent processes to promote a new wave of innovation. To leverage digital information from each individual project into business value for the whole industry, researchers must borrow knowledge and solutions from computational fields, such as Machine Learning, Artificial Intelligence, Data Mining and Data Science. They will provide a guide to the development, and even transformation of current BIM processes, with potential for development of new tools and automation of many tasks. What is not entirely clear is if BIM could take advantage also from Big Data Analytics, as some professionals are been advocating. In this paper, the author analyzes Big Data problems and the BIM context, and argues that BIM could not immediately take advantage from Big Datainfrastructure. Nevertheless, a route of development is suggested, which extends BIM from its predominantly building-focused models to models that encompass an entire city, which certainly will demand Big Data Analytics. Thus, a new City Information Modeling seems to be the right path of development for BIM as it turns to be integrated with Geographic Information Systems and will lead to tools that would be adequate for future Smart Cities planning and management.

The engineering design process is a complicated activity. It is often characterized by multi-disciplinary teams in multiple places working together on a single project, using different models and software tools. In addition, such activities generate a large amount of data that require exchange among designers and stages of the work. In industry, the current collaboration approaches often focus on integrating and managing multiple models from multi-designers. Building Information Modelling (BIM) is playing a major role in facilitating collaboration. BIM provides an opportunity to electronically model and manage the vast amount of information embedded in a building project, from conception to completion. In the building design process, changes and modifications are inevitable even in the contemporary BIM approach. Such changes need to be well managed to keep track of changes to ensure that designers have an up-to-date version of the BIM model. The main goal of this research is to develop a collaborative BIM platform that tackles the challenges of integrating object versioning, as a change management approach, and an IFC model, as data representation of BIM. This has been done through suggesting new IFC extensions to add further concepts representing the history of changing to any object of the model. It also explores possibilities of adding or merging object-based change information to existing BIM models to enable the representation of design intentions, identification of affected changes numerically and visually. A prototype system is implemented in C#, using .NET framework and Revit API platform. This paper concludes that the proposed system can contribute to improving collaboration - in terms of tracking and management of affected changes during multi-disciplinary design process.

A building information model (BIM) is an electronic repository of structured, three-dimensional data that captures both the physical and dynamic functional characteristics of a facility. In addition to its more traditional function as a tool to aid design and construction, a BIM can be used throughout the life cycle of a facility, functioning as a living database that places resources contained within the building in their spatial and temporal context. Through its comprehension of spatial relationships, a BIM can meaningfully represent and integrate previously isolated control and management systems and processes, and thereby provide a more intuitive interface to users. By placing processes in a spatial context, decision-making can be improved, with positive flow-on effects for security and efficiency. In this article, we systematically analyse the authorization requirements involved in the use of BIMs. We introduce the concept of using a BIM as a graphical tool to support spatial access control configuration and management (including physical access control). We also consider authorization requirements for regulating access to the structured data that exists within a BIM as well as to external systems and data repositories that can be accessed via the BIM interface. With a view to addressing these requirements we present a survey of relevant spatiotemporal access control models, focusing on features applicable to BIMs and highlighting capability gaps. Finally, we present a conceptual authorization framework that utilizes BIMs.

Building Information Modeling (BIM) has transformed the construction industry by offering a robust platform that integrates design, analysis, and construction processes within a single digital environment. This research explores the application of BIM technology, explicitly using Autodesk Revit, in modeling bridge abutments—an essential component in bridge construction that supports and distributes loads from the superstructure to the foundation. The study aims to demonstrate how BIM enhances the efficiency, accuracy, and sustainability of abutment design and construction. The methodology involves a comprehensive review of existing literature on BIM and bridge abutment design, focusing on technological advancements, case studies, and best practices. Additionally, practical implementation of BIM using Revit is conducted to develop detailed 3D models of abutments, incorporating architectural, structural, and geotechnical elements. The benefits of BIM in this context include improved collaboration among multidisciplinary teams, enhanced visualization capabilities for design optimization, and early detection of clashes and constructability issues. The research investigates the integration of Geographic Information Systems (GIS) with BIM to enhance site selection and environmental assessment phases, ensuring informed decision-making throughout the project lifecycle. Innovations in materials science, such as the use of fiber-reinforced polymers (FRP) and ultra-high-performance concrete (UHPC), are also considered for their potential to enhance the durability and longevity of bridge abutments. Ultimately, this study contributes to advancing the application of BIM in civil engineering, particularly in bridge construction, by showcasing Revit's capabilities in creating accurate, data-rich models that improve project outcomes.

Building Information Modelling (BIM) creates a way for all parties to share, exchange, and manage building information throughout the lifecycle of the building. On the other hand, radio frequency identification technology (RFID) has become one of the key technologies for automatic data collection and information storage. RFID can store building lifecycle information and context-aware information in a distributed database, so it can be considered as a component of the building information model. Therefore a standardized definition of the RFID components in the BIM is required. This paper proposes a standard method for adding RFID data definitions to BIM, and maps RFID data to related items in the BIM database. This study also defines the relationship between RFID tags and building components, and proposes the use of predefined relationships. The method of associating BIM data and RFID data can automatically select data related to RFID tag data by the relationship defined in BIM. Finally, the technical feasibility of the proposed method is proved by actual case test in the existing BIM software.

Digital construction has paved its way into the Architecture, Engineering and Construction (AEC) industries with the technological revolution, which significantly change the design, construction, and management processes. The use of Building Information Modelling (BIM) presents a valued collaborative technology that eliminates most communication related challenges of the industry. The Chinese government has emerged as a major force promoting BIM adoption, by implementing policies and promoting efforts with government support. Yet, the adoption rate is still unsatisfactory particularly for China cost engineering industry. This paper examines the drivers and barriers of BIM adoption and consequently review its impact on the current BIM implementation processes. This study also investigated their awareness and acceptance level of BIM adoption. The main respondents are the cost engineering practitioner specifically in the area of Guangxi. The UTAUT and TAM model are adopted, to analyse on individual intention and behaviour by distributing online questionnaires. This analysis reveals that the practitioners have poor awareness of BIM and have no willingness to learn new BIM knowledge independently. At present, the proportion of BIM actual use in projects is relatively low, and no single post-construction maintenance project applied BIM technology. The main influencing factors for BIM adoption are measured based on the Performance Expectation, Effort Expectation, Generation Gap, Social Influence, Managerial Attitude and Facilitating Conditions. This paper contributes to the strategic suggestions that puts forward the role of user, consultants, governments that may facilitate the advantages of BIM technology adoption. This paper identified that successful implementation include the role of consultants on their readiness and acceptance, followed by adequate technology education and training.