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The purpose of this paper is to present a strategic overview of the current literature on “Building information modelling (BIM) for Building Refurbishment and Maintenance” to unfold the factors behind the relative underdeveloped state of the field and to contribute to the development of a more cumulative knowledge base by presenting the current status and suggesting future directions for research.

A systematic review of the literature has been undertaken by classifying and mapping the literature, identifying the input-output relations, exhibiting the areas focused on by researchers as well as neglected ones and by indicating the trends in research through the years. Both qualitative and quantitative analysis is used in the study to better interpret the existing studies in a holistic perspective.

Although the need for BIM in facility management (FM) has been acknowledged by researchers and practitioners, the results highlight that studies related to BIM applications in maintenance and especially refurbishment are relatively recent. However, the trend in published articles shows that the interest is continuously growing. Existing research in this field can be clustered in the following subtopics: (1) building survey and as-built BIM, (2) modelling and managing energy, (3) design assessment, (4) access to and integration of maintenance information and knowledge, and (5) information exchange and interoperability.

The paper identifies the gaps in the research domain that hinders a widespread adoption of BIM in refurbishment and maintenance stages and introduces roadmaps to surmount the challenges identified in each specific subtopic of the field.

The purpose of this paper is to present a review of the implications building information modelling (BIM) is having on the building energy modelling (BEM) and design of buildings. It addresses the issues surrounding exchange of information throughout the design process, and where BIM may be useful in contributing to effective design progression and information availability.

Through review of current design procedures and examination of the concurrency between architectural and thermophysical design modelling, a procedure for information generation relevant to design stakeholders is created, and applied to a high-performance building project currently under development.

The extents of information key to the successful design of a buildings energy performance in relation to its architectural objectives are given, with indication of the level of development required at each stage of the design process.

BIM offers an extensible medium for parametric information storage, and its implementation in design development offers the capability to include BEM parameter-integrated construction information. The extent of information required for accurate BEM at stages of a building’s design is key to understanding how best to record performance information in a BIM environment.

This paper contributes to the discussion around the integration of concurrent design procedures and a common data environment. It presents a framework for the creation and dissemination of information during design, exemplifies this on a real building project and evaluates the barriers experienced in successful implementation.

This paper aims to represent the results of a case study to establish a building information model (BIM)-enabled workflow to capture and retrieve facility information to deliver integrated handover deliverables.

The Building Handover Information Model (BHIM) framework proposed herein is contextualized given the Construction Operation Information Exchange (COBie) and the level of development schema. The process uses Autodesk Revit as the primary BIM-authoring tool and Dynamo as an add-in for extending Revit’s parametric functionality, BHIM validation, information retrieval and documentation in generating operation and maintenance (O&M) deliverables in the end-user requested format.

Given the criticality of semantics for model elements in the BHIM and for appropriate interoperability in BIM collaboration, each discipline should establish model development and exchange protocols that define the elements, geometrical and non-geometrical information requirements and acceptable software applications early in the design phase. In this case study, five information categories (location, specifications, warranty, maintenance instructions and Construction Specifications Institute MasterFormat division) were identified as critical for model elements in the BHIM for handover purposes.

Design- and construction-purposed BIM is a standard platform in collaborative architecture, engineering and construction practice, and the models are available for many recently constructed facilities. However, interoperability issues drastically restrict implementation of these models in building information handover and O&M. This study provides essential input regarding BIM exchange protocols and collaborative BIM libraries for handover purposes in collaborative BIM development.

Developing a reliable cost estimate at the early stage of construction projects is challenging due to inadequate project information. Most of the information during this stage is qualitative, posing additional challenges to achieving accurate cost estimates. Additionally, there is a lack of tools that use qualitative project information and forecast the budgets required for project completion. This research, therefore, aims to develop a model for setting project budgets (excluding land) during the pre-conceptual stage of residential buildings, where project information is mainly qualitative.

Due to the qualitative nature of project information at the pre-conception stage, a natural language processing model, DistilBERT (Distilled Bidirectional Encoder Representations from Transformers), was trained to predict the cost range of residential buildings at the pre-conception stage. The training and evaluation data included 63,899 building permit activity records (2021–2022) from the Victorian State Building Authority, Australia. The input data comprised the project description of each record, which included project location and basic material types (floor, frame, roofing, and external wall).

This research designed a novel tool for predicting the project budget based on preliminary project information. The model achieved 79% accuracy in classifying residential buildings into three cost_classes ($100,000-$300,000, $300,000-$500,000, $500,000-$1,200,000) and F1-scores of 0.85, 0.73, and 0.74, respectively. Additionally, the results show that the model learnt the contextual relationship between qualitative data like project location and cost.

The current model was developed using data from Victoria state in Australia; hence, it would not return relevant outcomes for other contexts. However, future studies can adopt the methods to develop similar models for their context.

This research is the first to leverage a deep learning model, DistilBERT, for cost estimation at the pre-conception stage using basic project information like location and material types. Therefore, the model would contribute to overcoming data limitations for cost estimation at the pre-conception stage. Residential building stakeholders, like clients, designers, and estimators, can use the model to forecast the project budget at the pre-conception stage to facilitate decision-making.

Current research efforts exhibit a surge imperative for a building information modelling (BIM) approach that embodies a repository of all relevant data of existing building components while monitoring and consistently recording numerous components’ functions throughout its lifecycle, especially in Egypt. This research paper aims to develop an integrated as-is BIM-facility management (FM) information model for the existing building’s components via a case study, depicting a repository for historical data and knowledge amassed from inspections and conveying maintenance decisions automatically during the FM practices.

The developed approach pursues four successive steps: data acquisition and processing of building components; components recognition from point clouds; modelling scanned point clouds; and quick response code information transfer to BIM components.

The proposed approach incorporates the as-is BIM with the building components’ as-is FM information to portray a repository for historical data and knowledge collected from inspections to proactively benefit facility managers in simplifying, expediting and enhancing maintenance decisions automatically during FM practices.

This paper presents a digital alternative to manual maintenance recordkeeping concerning building components to retrieve their as-is and historical data using a case study in Egypt. This paper proposes a broad scan to as-is information BIM approach for the existing building’s components to condone maintenance interventions using a versatile, affordable, readily available and multi-functional method for scanning the building’s components using a handheld tool.

Building information modeling (BIM) is most often used for the construction of new buildings. By using BIM in such projects, collaboration among stakeholders in an architecture, engineering and construction project is improved. To even further improve collaboration, there is a move toward the production and usage of BIM standards in various countries. These are typically national documents, including guides, protocols, and mandatory regulations, that introduce guidelines about what information should be exchanged at what time between which partners and in what formats. If a nation or a construction team agrees on these guidelines, improved collaboration can come about on top of the collaboration benefits induced by the mere usage of BIM. This scenario might also be targeted for interventions in existing buildings. The paper aims to discuss these issues.

In this paper, the authors investigate the general content and usage of existing BIM standards for new constructions, describing specifications about BIM deliverable documents, modeling, and collaboration procedures. The authors suggest to what extent the content in the BIM standards can also be used for interventions in existing buildings. These suggestions rely heavily on literature study, supported by on-site use case experiences.

From this research, the authors can conclude that the existing standards give a solid basis for BIM collaboration in existing building interventions, but that they need to be extended in order to be of better use in any intervention project in an existing building. This extension should happen at: data modeling level: other kinds of data formats need to be considered, coming from terrestrial laser scanning and automatic digital photogrammetry tools; at data exchange level: exchange requirements should take explicit statements about modeling tolerances and levels of (un)certainty; and at process modeling level: business process models should include information exchange processes from the very start of the building survey (BIM→facility management→BIM or regular audit).

BIM environments are not often used to document existing buildings or interventions in existing buildings. The authors propose to improve the situation by using BIM standards and/or guidelines, and the authors give an initial overview of components that should be included in such a standard and/or guideline.

To mitigate the problems in sensor-based facility management (FM) such as lack of detailed visual information about a built facility and the maintenance of large scale sensor deployments, an integrated data source for the facility’s life cycle should be used. Building information modeling (BIM) provides a useful visual model and database that can be used as a repository for all data captured or made during the facility’s life cycle. It can be used for modeling the sensing-based system for data collection, serving as a source of all information for smart objects such as the sensors used for that purpose. Although few studies have been conducted in integrating BIM with sensor-based monitoring system, providing an integrated platform using BIM for improving the communication between FMs and Internet of Things (IoT) companies in cases encountered failed sensors has received the least attention in the technical literature. Therefore, the purpose of this paper is to conceptualize and develop a BIM-based system architecture for fault detection and alert generation for malfunctioning FM sensors in smart IoT environments during the operational phase of a building to ensure minimal disruption to monitoring services.

This paper describes an attempt to examine the applicability of BIM for an efficient sensor failure management system in smart IoT environments during the operational phase of a building. For this purpose, a seven-story office building with four typical types of FM-related sensors with all associated parameters was modeled in a commercial BIM platform. An integrated workflow was developed in Dynamo, a visual programming tool, to integrate the associated sensors maintenance-related information to a cloud-based tool to provide a fast and efficient communication platform between the building facility manager and IoT companies for intelligent sensor management.

The information within BIM allows better and more effective decision-making for building facility managers. Integrating building and sensors information within BIM to a cloud-based system can facilitate better communication between the building facility manager and IoT company for an effective IoT system maintenance. Using a developed integrated workflow (including three specifically designed modules) in Dynamo, a visual programming tool, the system was able to automatically extract and send all essential information such as the type of failed sensors as well as their model and location to IoT companies in the event of sensor failure using a cloud database that is effective for the timely maintenance and replacement of sensors. The system developed in this study was implemented, and its capabilities were illustrated through a case study. The use of the developed system can help facility managers in taking timely actions in the event of any sensor failure and/or malfunction to ensure minimal disruption to monitoring services.

However, there are some limitations in this work which are as follows: while the present study demonstrates the feasibility of using BIM in the maintenance planning of monitoring systems in the building, the developed workflow can be expanded by integrating some type of sensors like an occupancy sensor to the developed workflow to automatically record and identify the number of occupants (visitors) to prioritize the maintenance work; and the developed workflow can be integrated with the sensors’ data and some machine learning techniques to automatically identify the sensors’ malfunction and update the BIM model accordingly.

Transferring the related information such as the room location, occupancy status, number of occupants, type and model of the sensor, sensor ID and required action from the BIM model to the cloud would be extremely helpful to the IoT companies to actually visualize workspaces in advance, and to plan for timely and effective decision-making without any physical inspection, and to support maintenance planning decisions, such as prioritizing maintenance works by considering different factors such as the importance of spaces and number of occupancies. The developed framework is also beneficial for preventive maintenance works. The system can be set up according to the maintenance and time-based expiration schedules, automatically sharing alerts with FMs and IoT maintenance contractors in advance about the IoT parts replacement. For effective predictive maintenance planning, machine learning techniques can be integrated into the developed workflow to efficiently predict the future condition of individual IoT components such as data loggers and sensors, etc. as well as MEP components.

Lack of detailed visual information about a built facility can be a reason behind the inefficient management of a facility. Detecting and repairing failed sensors at the earliest possible time is critical to ensure the functional continuity of the monitoring systems. On the other hand, the maintenance of large-scale sensor deployments becomes a significant challenge. Despite its importance, few studies have been conducted in integrating BIM with a sensor-based monitoring system, providing an integrated platform using BIM for improving the communication between facility managers and IoT companies in cases encountered failed sensors. In this paper, a cloud-based BIM platform was developed for the maintenance and timely replacement of sensors which are critical to ensure minimal disruption to monitoring services in sensor-based FM.

Facilitating the information exchange and interoperability between stakeholders during the life-cycle of an asset can be one of the fundamental necessities for developing an enhanced information exchange framework. Such a framework can also improve the successful accomplishment of building projects. This paper aims to use Semantic Web technologies for facilitating information exchange within existing building projects.

In real-world building projects, the construction industry’s information supply chain may initiate from near scratch when new building projects are started resulting in diverse data structures represented in unstructured data sources, like Excel spreadsheets and documents. Large-scale data generated throughout a building's life-cycle requires exchanging and processing during an asset's Operation and Maintenance (O&M) phase. Building information modelling (BIM) processes and related technologies can address some of the challenges and limitations of information exchange and interoperability within new building projects. However, the use of BIM in existing and retrofit assets has been hampered by the challenges surrounding the limitations of existing technologies.

The aim of this paper is twofold. Firstly, it briefly outlines the framework previously developed for generating semantically enriched 3D retrofit models. Secondly, a framework is proposed focussing on facilitating the information exchange and interoperability for existing buildings. Semantic Web technologies and standards, such as Web Ontology Language and existing AEC domain ontologies are used to enhance and improve the proposed framework.

The proposed framework is evaluated by implementing an example application and the Resource Description Framework data produced by the previously developed framework. The proposed approach makes a valuable contribution to the asset/facilities management (AM/FM) domain. It should be of interest to various FM practices for existing assets, such as the building information/knowledge management for design, construction and O&M stages of an asset’s life-cycle.

Three dimensional (3 D) laser scanner surveying is widely used in many fields, such as agriculture, mining and heritage documentation and can be of great benefit for as-built documentation in construction and facility management domains. However, there is lack of applied research and use cases integrating 3 D laser scanner surveying with building information modeling (BIM) for existing facilities in Malaysia. This study aims to develop a scan to as-built BIM workflow to use 3 D laser scanner surveying and create as-built building information models of an existing complex facility in Malaysia.

A case study approach was followed to develop a scan to as-built BIM workflow through four main steps: 3 D laser scanning, data preprocessing, data registration and building information modeling.

This case study proposes a comprehensive scan to as-built BIM workflow which illustrates all the required steps to create a precise 3 D as-built building information model from scans. This workflow was successfully implemented to the Eco-Home facility at the Universiti Teknologi Malaysia.

Scan to as-built BIM is a digital alternative to manual and tedious process of documentation of as-built condition of a facility and provides a detail process using laser scans to create as-built building information models of facilities.

The compliance checking of Building Information Modeling (BIM) models is crucial throughout the lifecycle of construction. The increasing amount and complexity of information carried by BIM models have made compliance checking more challenging, and manual methods are prone to errors. Therefore, this study aims to propose an integrative conceptual framework for automated compliance checking of BIM models, allowing for the identification of errors within BIM models.

This study first analyzed the typical building standards in the field of architecture and fire protection, and then the ontology of these elements is developed. Based on this, a building standard corpus is built, and deep learning models are trained to automatically label the building standard texts. The Neo4j is utilized for knowledge graph construction and storage, and a data extraction method based on the Dynamo is designed to obtain checking data files. After that, a matching algorithm is devised to express the logical rules of knowledge graph triples, resulting in automated compliance checking for BIM models.

Case validation results showed that this theoretical framework can achieve the automatic construction of domain knowledge graphs and automatic checking of BIM model compliance. Compared with traditional methods, this method has a higher degree of automation and portability.

This study introduces knowledge graphs and natural language processing technology into the field of BIM model checking and completes the automated process of constructing domain knowledge graphs and checking BIM model data. The validation of its functionality and usability through two case studies on a self-developed BIM checking platform.