Search Results (133)

The construction sector significantly contributes to global environmental degradation through intensive resource extraction, high energy consumption, and substantial waste generation. Addressing this unsustainable trajectory requires integrated approaches that simultaneously improve operational efficiency and material circularity. Lean Construction (LC) and Circular Economy (CE) offer complementary frameworks for enhancing process performance and reducing environmental impacts. However, their combined implementation remains underdeveloped and fragmented. This study conducts a systematic literature review (SLR) of 18 peer-reviewed articles published between 2010 and 2025, selected using PRISMA 2020 guidelines and sourced from Scopus and Web of Science databases. A mixed-method approach combines bibliometric mapping and qualitative content analysis to investigate how LC and CE are jointly operationalized in construction contexts. The findings reveal that LC improves cost, time, and workflow reliability, while CE enables reuse, modularity, and lifecycle extension. Integration is further supported by digital tools—such as Building Information Modelling (BIM), Design for Manufacture and Assembly (DfMA), and digital twins—which enhance traceability and flow optimization. Nonetheless, persistent barriers—including supply chain fragmentation, lack of standards, and regulatory gaps—continue to constrain widespread adoption. This review identifies six strategic enablers for LC-CE integration: crossdisciplinary competencies, collaborative governance, interoperable digital systems, standardized indicators, incentive-based regulation, and pilot demonstrator projects. By consolidating fragmented evidence, the study provides a structured research agenda and practical insights to guide the transition toward more circular, efficient, and sustainable construction practices. Full article

As BIM projects grow in volume and complexity, automated Information Compliance Checking (ICC) is becoming essential to meet demanding regulatory and contractual requirements. This study presents novel controlled vocabularies and processes for the management of information requirements, along with a structured evaluation of the Information Delivery Specification (IDS) and its associated tools. The controlled vocabularies are important as they provide support to standardization, information retrieval, data-driven workflows, and AI integration. Information requirements are classified by input type and project interaction context (phase, origin, project role, and communication), as well as by applicability (data management function, model granularity, BIM usage, and checkability). The ontology comprises seven categories: identity, geometry, design/performance, fabrication/construction, operation/maintenance, cost, and regulatory category, each linked to verification principles such as uniqueness and consistency. This enables systematic implementation of validation checks aligned with company and project needs. We introduce three ICC workflows in relation to the BIM authoring tools (inside, outside, and hybrid) and suggest key criteria for the functional and non-functional evaluation of IDS tools. Empirical results from a real project using five IDS tools reveal implementation issues with the classification facet, regular expressions, and issue reporting. The proposed ontology and framework lay the foundation for a scalable, transparent ICC within openBIM. The results also provide ICC process guidance for practitioners, a SWOT analysis that can inform enhancements to the existing IDS schema, identify possible inputs for certification of IDS tools, and generate innovative ideas for research and development. Full article

The construction industry is moving towards the era of industry 4.0; 5.0 with Building Information Modelling (BIM) as the tool gaining significant traction owing to its inherent advantages such as enhancing construction design, process and data management. However, the integration of BIM presents risks that are often overlooked in project implementation. This study aims to develop a novel amalgamated dimensional factor (Techno-organizational Aspect) that is set out to identify and align appropriate management strategies to these risks. Firstly, it encompasses an in-depth analysis of BIM and risk management, through an integrative review approach. The study utilizes an exploratory-based review centered around journal articles and conference papers sourced from Scopus and Google Scholar. Then processed using NVivo 12 Pro software to categorise risks through thematic analysis, resulting in a comprehensive Risk Breakdown Structure (RBS). Then qualitative content analysis was employed to identify and develop management strategies. Further data collection via online survey was crucial for closing the research gap identified. The analysis by mixed method research enabled to determine the risk severity via the quantitative approach using SPSS (version 29), while the qualitative approach linked management strategies to the risk factors. The findings accentuate the crucial linkages of key strategies such as version control system that controls BIM data repository transactions to mitigate challenges controlling transactions in multi-model collaborative environment. The study extends into underexplored amalgamated domains (techno-organisational spectrum). Therefore, a significant contribution to bridging the existing research gap in understanding the intricate relationship between BIM implementation risks and effective management strategies. Full article

The construction industry is one of the largest contributors to the world economy. However, the level of automation and digitalization in the construction industry is still at its infancy in comparison with other industries due to the complex nature and the large size of construction projects. Meanwhile, construction projects are prone to cost overruns and schedule delays due to the adoption of traditional progress monitoring techniques to retrieve progress on-site, having indoor activities participating with an accountable ratio of these works. Improvements in deep learning and Computer Vision (CV) algorithms provide promising results in detecting objects in real time. Also, researchers have investigated the probability of using CV as a tool to create a Digital Twin (DT) for construction sites. This paper proposes a model utilizing the state-of-the-art YOLOv8 algorithm to monitor the progress of bricklaying activities, automatically extracting and analyzing real-time data from construction sites. The detected data is then integrated into a 3D Building Information Model (BIM), which serves as a DT, allowing project managers to visualize, track, and compare the actual progress of bricklaying with the planned schedule. By incorporating this technology, the model aims to enhance accuracy in progress monitoring, reduce human error, and enable real-time updates to project timelines, contributing to more efficient project management and timely completion. Full article

Traditional project scheduling tools like Gantt charts struggle with dynamic adjustments and real-time optimization in complex construction projects, leading to inefficiencies and delays. This study addresses this challenge by proposing a dynamic optimization framework that integrates Building Information Modeling (BIM) and Artificial Intelligence (AI) to enhance schedule management. The framework comprises three layers: a data layer for collecting BIM and real-time site data, an analysis layer powered by AI algorithms for predictive analytics and optimization, and an application layer for visualizing progress and supporting decision-making. Through a case study on a large-scale water reservoir tunnel project in China, the framework demonstrated significant improvements in identifying schedule risks, optimizing resource allocation, and enabling real-time adjustments. Key innovations include a 4-in-1 Network Diagram Engine and a Blueprint Engine, which facilitate intuitive progress monitoring and automated task management. However, limitations in personnel skill matching, interface complexity, and mobile system performance were identified. This research advances the theoretical foundation of BIM-AI integration and provides practical insights for improving scheduling efficiency and project outcomes in the construction industry. Future work should focus on enhancing human resource management modules and refining system usability for broader adoption. Full article

Building Information Modeling (BIM) is an emerging information technology tool and management concept in the construction industry, enabling the transition from traditional 2D drawings to 3D models. It helps improve efficiency and promote industrial upgrading in the construction sector. However, in actual project practices, the effectiveness of BIM application has not been as expected, and the return on investment (ROI) may even be negative. Through a literature review, we found that risk identification, correlation analysis, and risk assessment related to BIM implementation require further research. To better promote the application of BIM in the construction industry, this study employs relevant methods to analyze the risk factors of BIM implementation. Through the literature review, 31 BIM implementation risk factors were identified, and 24 major risk factors were extracted using the AHP (Analytic Hierarchy Process) method. The ISM (Interpretative Structural Modeling) method was then used to determine the interrelationships among these major risk factors, establishing a hierarchical model with seven levels. Through MICMAC (Matrices Impacts Corises-Multiplication Appliance Classment) analysis, the BIM implementation risk factors were categorized into three groups, and three-tiered response strategies were proposed at the industry, organizational, and project levels. By analyzing the main risk factors of BIM application in China’s construction industry and formulating corresponding response strategies to promote its successful application, this study contributes to the knowledge system. The findings also provide a reference for other countries and regions to clarify major risk factors and their interrelationships, thereby improving the effectiveness of BIM implementation. Full article

The demand for interoperable, lifecycle-oriented data exchange in the port and waterway sector is intensifying amid global digital transformation and infrastructure modernisation. Traditional Building Information Modelling (BIM) practices often fail to capture the domain-specific complexity and multidisciplinary collaboration required in maritime infrastructure. This paper critically evaluates the IFC 4.3 schema as a foundational standard for openBIM-based integration in this sector, offering a semantic alignment framework designed for the planning, design, and operational phases of port projects. Rather than proposing schema extensions, the framework interprets existing IFC constructs to model port-specific assets while supporting environmental and geospatial integration. Two case studies, a master planning project for a shipyard and a design coordination project for a ship lock complex, demonstrate the schema’s capability to facilitate federated modelling, reduce semantic discrepancies, and enable seamless data exchange across disciplines and software platforms. The research delivers actionable implementation strategies for practitioners, identifies technical limitations in current toolchains, and outlines pathways for advancing standardisation efforts. It further contributes to the evolving discourse on digital twins, GIS-BIM convergence, and semantic enrichment in infrastructure modelling. This work provides a scalable, standards-based roadmap to improve interoperability and enhance the digital maturity of port and waterway infrastructure. Full article

The construction industry is well known for its problems in completing projects on time and within budget. While constructability has been promoted as a best practice to address these challenges, a clear gap remains regarding its practical definition and implementation, exacerbated by industry reluctance to share proprietary knowledge. This narrative review investigated the current state of constructability in industrial plant construction projects, synthesizing literature from leading databases and professional sources. The methodology involved a critical qualitative analysis of studies addressing constructability frameworks, critical success factors, and the impact of BIM technologies. The findings revealed that traditional constructability reviews, though valuable, are limited by human expertise and subjectivity. The integration of BIM offers transformative potential by enabling collaborative, comprehensive constructability analysis and facilitating the transfer of tacit to explicit knowledge. This study clarifies the constructability concept and highlights persistent knowledge gaps and it illustrates how BIM-aided constructability can optimize the design and planning of industrial plant projects, ultimately enhancing project sustainability and delivery outcomes. Full article

Quality management during construction is critical to ensuring compliance with technical specifications and quality standards. Traditional practices often rely on manual, paper-based documentation, leading to inefficiencies, data fragmentation, and poor traceability. This study presents QualiSite, a novel digital workflow that integrates Building Information Modeling (BIM) and Geographic Information Systems (GIS), aligned with ISO 9001:2015 requirements, to enhance quality management in building projects. The research is framed under the Design Science Research Method (DSRM), guiding the iterative development and validation of the tool. QualiSite was tested in a real-world case study involving the construction of reinforced concrete walls. The results demonstrated functional improvements in inspection traceability, consistency of quality records, and coordination between field data and BIM elements. Using structured digital forms contributed to more consistent data capture and greater efficiency in recording, organizing, and visualizing quality control statuses within the 3D environment. These outcomes enabled transparent inspection processes and clear visualization of quality status across construction elements. The digital workflow also facilitated the identification of nonconformities and streamlined communication between field inspectors and model managers. This approach advances traditional quality management by embedding inspection records into a Cyber-Physical Systems (CPS) framework, contributing to the digital transformation of the Architecture, Engineering, and Construction (AEC) industry and supporting the vision of Smart Industry. Full article

Highway alignment optimization is critical for developing sustainable and resilient transportation infrastructure. Traditional alignment selection methods frequently fail to comprehensively account for all of the diverse factors, including geometric compliance, traffic efficiency, land use factors, environmental impacts, and cost considerations, ultimately resulting in suboptimal project outcomes. To address these challenges, this study proposes a building information modeling (BIM)-based alignment optimization framework that integrates diverse datasets, sophisticated modeling techniques, and stakeholder collaboration. The proposed framework systematically enables the user to model terrain, design geometric features, simulate traffic, and conduct cost analysis and environmental impact assessments. A case study of the Dera Ghazi Khan Northern Bypass project in Pakistan, a critical infrastructure project designed to ease congestion and enhance regional connectivity, is presented to validate the proposed framework. Three alignment alternatives were analyzed, with the optimized solution (Alignment Option 2) demonstrating a 30% reduction in congestion, a 20% decrease in travel time, and a 6.48% reduction in construction costs compared to the other alignment alternatives. These outcomes highlight the transformative potential of BIM-driven optimization to significantly enhance sustainability, cost-efficiency, and operational performance. This framework offers a scalable and adaptable model to guide future infrastructure development initiatives toward more sustainable outcomes. Full article

As the construction industry shifts from an extensive development model to one characterized by intelligent structural systems, the imperative to enhance productivity and management efficiency has emerged as a critical challenge. Conventional rebar construction processes heavily rely on manual operations—such as on-site rebar cutting, manual transcription of material lists, and decentralized processing—which are susceptible to subjective errors and often result in significant material waste. This issue is particularly pronounced in large-scale projects, where disorganized management of rebar quantities and placements exacerbates inefficiencies. To address these challenges, this study proposes an integrated approach that synergistically combines a genetic algorithm-based rebar-cutting optimization model with BIM technology, thereby optimizing rebar management throughout the construction process. The research is structured into two primary components. Firstly, a one-dimensional mathematical model for rebar-cutting optimization is developed, incorporating an innovative real-number encoding strategy within the genetic algorithm framework to maximize material utilization. A case study conducted on a pump station project reveals that the utilization rates for 32 mm and 16 mm rebar reach 86.76% and 93.90%, respectively, significantly exceeding the industry standard of 80%. Secondly, an automated batch modeling tool is developed using C# and the Revit API, which enables the efficient generation of rebar components; a unique coding system is employed to establish a bidirectional mapping between the digital model and the physical rebar, ensuring precise positioning and effective information management. Overall, this integrated method—encompassing rebar-cutting optimization, digital modeling, and on-site intelligent management—not only mitigates material waste and reduces production costs but also markedly enhances construction efficiency and accuracy in complex projects, thereby providing robust technical support for the seamless integration of intelligent construction and industrialized building practices. Full article

Automation is revolutionizing a number of sectors, including construction, by bringing about important technological breakthroughs that increase productivity and efficiency. Automation in safety procedures is still scarce though. In India, the majority of safety procedures are still reactive, manual, and paper-based. This study is a component of a broader research project on automated safety screening for fall risks enabled by BIM. It entails codification of OSHA rules to perform safety checks, placing corrective actions into location, and generating reports in a virtual environment. As part of the broader risk lifecycle, these tasks are typically completed on-site during the various stages of construction. This study, on the other hand, executes these steps in a virtual environment in the preconstruction phase. The model has been assessed in a pilot study in India and was developed especially to address fall hazards from staircases. Through early hazard identification and mitigation, the system assists professionals in enhancing overall safety performance. Full article

The increasing complexity of data management in the Architecture, Engineering, and Construction (AEC) industry, driven by the adoption of distributed digital twins (dDTws) and cloud-based solutions, presents challenges in interoperability, data sovereignty, and scalability. Existing Building Information Modeling (BIM) and Common Data Environment (CDE) frameworks often fall short in addressing these issues due to their reliance on centralized and proprietary systems. This paper introduces a novel framework that transforms the Information Container for Linked Document Delivery (ICDD) into a dynamic, graph-based architecture. Unlike conventional file-based ICDD implementations, this approach enables fine-grained, semantically rich linking and querying across distributed models while maintaining data sovereignty and version control. The framework is designed to enhance real-time collaboration, ensure secure and sovereign data management, and improve interoperability across diverse project stakeholders. The framework leverages graph databases, semantic web technologies, and ISO standards such as ISO 21597 to facilitate seamless data exchange, automated linking, and advanced version control. Key functionalities include federated data storage, compliance with local and international regulations, and support for multidisciplinary workflows in large-scale AEC projects. To demonstrate the feasibility of the proposed framework, a simplified use case scenario is implemented and analyzed. By addressing critical challenges and enabling seamless integration of emerging technologies such as digital twins, this study advances the state of the art in data management for the AEC industry, providing a robust foundation for future innovations. Full article

Traditional construction safety management, reliant on manual inspections and heuristic judgments, increasingly fails to address the dynamic, multi-dimensional risks of modern projects, perpetuating fragmented safety governance and reactive hazard mitigation. This study proposes an integrated building information modeling (BIM)–AI platform to unify safety supervision across the project lifecycle, synthesizing spatial-temporal data from BIM with AI-driven probabilistic models and IoT-enabled real-time monitoring for sustainable construction safety management. Employing a Design Science Research methodology, the platform’s phase-agnostic architecture bridges technical–organizational divides, while the Multilayer Neural Risk Coupling Assessment framework quantifies interdependencies among structural, environmental, and human risk factors. Prototype testing in real-world projects demonstrates improved risk detection accuracy, reduced reliance on manual processes, and enhanced cross-departmental collaboration. The system transitions safety regimes from compliance-based protocols to proactive, data-empowered governance. This approach offers scalability across diverse projects. The BIM-AI intelligent fusion platform proposed in this study builds an intelligent construction paradigm with synergistic development of safety governance and sustainability through whole lifecycle risk coupling analysis and real-time dynamic monitoring, which realizes a proactive safety supervision system while significantly reducing construction waste and accident prevention mechanisms. Full article

A 3D visual presentation provides a wide spectrum of interpretive and collaborative possibilities. Building Information Modeling (BIM) is becoming increasingly popular in the AEC (Architecture, Engineering, Construction) sector. However, it mainly applies to cubic (building structures) and infrastructure projects. BIM is rarely used in the digitization of aboveground or underground networks. The purpose of this article is to fill this research gap and to demonstrate, through a case study, the real benefits of processing integrated 3D data covering civil structures, technical infrastructure and networks. The methodology of this paper included all steps towards the creation of an integrated model of a district heating network and the infrastructure located in its vicinity. The results show that integrated BIM models can help minimize or prevent design and execution collisions. This article undertakes critical inquiry and presents a unique approach to modeling urban spaces. The integrated BIM model enables management of the life cycle of a district heating network using a wide range of applications depending on the nature of the data, analysis and simulation. This article contributes to the discussion on modeling transmission infrastructure and integrating it with existing spatial models and databases. This paper presents innovative and significant interdisciplinary research. Full article