Design for manufacturing and assembly (DfMA) is an engineering methodology which aims to increase ease of manufacture and efficiency of assembly by considering manufacturing and assembly constraints in the design process. However, current DfMA approaches in the construction sector are not automated enough to identify the design features that may cause project delay in real time. This leads to longer design cycle. Also, current scheduling algorithms rely on human intervention to generate activity network from a design output. Addressing these inefficiencies, we propose an interpretative machining learning model to predict the construction duration given a design output. More importantly, the same model identifies the design features that may cause the most delay in the project. The model is trained on a residential design dataset with various features, such as layout, geometry, and element typology. The output of the model is the project duration and an importance map, indicating the influence each feature of the given design has on the total project duration. The results from this model can considerably reduce the design cycle by supporting architects to create fabrication and assembly aware design even when they have little knowledge of production and assembly processes. This model will contribute to a novel computational approach for DfMA.

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The field of construction informatics is fragmented and lacks clarity in understanding the interconnection of different data management strategies. This makes it challenging to address industry-specific data management issues. Using a critical interpretive synthesis, this study reviews and integrates both present and emerging data management approaches in construction informatics. The review is meant to be comprehensive, encompassing technologies and concepts such as Open Schema, Information Container, Common Data Environments, Linked Data, as well as cutting-edge Web3 technologies such as blockchain and decentralized data protocols. The different approaches are identified and classified into five categories and mapped into a two-dimensional framework that considers data storage and data processing modes. The systematic categorization provides a simple, but comprehensive understanding of data management strategies in construction informatics. Moreover, the framework allows to identify the state of the art and trends of data management approaches, providing guidance for future research perspectives, especially in the intersection with Web3 technologies.

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Extended reality (XR) technologies refer to mixed reality and virtual reality configurations that augment real or represent fully virtual information in an intuitive and immersive manner, transforming the way we plan, design, construct, and operate built environment assets. XR offers great potential to support and accelerate the transition of built environment practices to a circular economy by supporting decisions based on narrow, slow, close, and regenerate strategies. Narrow strategies use XR to simulate the building process to identify potential issues, reduce material waste, and avoid costly mistakes. Slow strategies use XR to enable construction with durable materials and designing for adaptability to extend the lifespan of buildings. Close strategies use XR to facilitate material recovery and support repurposing and reuse, thus reducing waste. Regenerate strategies use XR as a motivational tool to engage citizens, communities, and professionals in design and management decisions. However, applying XR is not without challenges, including technical and process-related limitations, potential misuse, and a lack of rich digital twins. Future research opportunities include the development of rich and accurate digital twins, ethical and sustainable use of XR technologies, and overcoming technical and logistical challenges through interdisciplinary collaboration and user-friendly and accessible XR hardware and software.@en

Mobile factories promise an increased project efficiency with on-demand production and Just-in-Time delivery of prefabricated elements. However, traditional scheduling methods predominantly focus on either factory or site and neglect the factory mobility, often leading to suboptimal synchronization. To address this gap, this paper introduces a novel reinforcement learning (RL)-based model for optimizing the operational policy of mobile factories in infrastructure projects. The developed model simultaneously schedules on-site and off-site operations, effectively integrating the performance metrics at the project level. Utilizing RL, the factory's production management system continuously learns and adjusts in response to real-time project developments, ensuring optimal decision-making regarding scheduling and resource allocation.@en

Buildings are responsible for a huge amount of negative environmental impacts at the End-of-Life (EoL) stage because of the massive global production of waste. Therefore, there is an urgent need for developing design systems to decrease waste generation by facilitating the reuse and recycling of building materials. Building Information Modeling (BIM) has been demonstrated to be an effective tool for enhancing building performance at the different life cycle stages. However, the implementation of BIM for assessing the EoL stage of building projects is still underdeveloped. One important activity on the EoL stage is disassembly planning for reuse of building components and building renovation. The aim of this study is to develop the framework for a BIM Model View Definition (MVD) for disassembly planning. First, we developed a framework for an MVD for the disassembly planning of buildings based on the literature review in the field. Then, we proposed a workflow for implementing the MVD, as well as the validation procedures. In the end, the MVD was validated by compiling the information of a BIM-based disassembly model. Results of the case study show that the presented approach is efficient for corroborating the syntax, semantic structure, and information content of BIM models.@en

Human-Data Interaction is central to the dynamic nature of the construction industry and its growing reliance on substantial data sets. In this paper, we evaluate literature on the topic of Human-Data Interaction across several technologies and concepts within the built environment with the aim of identifying underlying aspects that can lead to an underpinning theory of Human-Data Interaction in the built environment to support advancement of the research in the field. Those aspects were identified as trust, game theory, empowerment of humans, human control, safety, accessibility, enhancing understanding, and the three pillars of Human-Data Interaction of agency, legibility, and negotiability.

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Purpose: This paper aims to conduct a qualitative assessment of synergies between information flows of a multifamily product platform used for industrialized housing and materials passports that can promote a circular economy in the construction industry. Design/methodology/approach: Using a single case study method, the research assesses the availability and accessibility of materials passport-relevant information generated by a leading Swedish industrialized housing construction firm. Data is collected using semistructured interviews, document analysis and an extended research visit. Findings: The research findings identify the functional layers of the product platform, map the information flow using a process diagram, assess the availability and accessibility of material passport relevant information by lifecycle stage and actor, and summarize the key points using a SWOT (strengths, weaknesses, opportunities and threats) analysis. Research limitations/implications: The three main implications are: the technical and process platforms used in industrialized construction allow for generating standardized, digital and reusable information; the vertical integration of trades and long-term relationships with suppliers improve transparency and reduce fragmentation in information flows; and the design-build-operate business model strategy incentivizes actors to manage information flows in the use phase. Practical implications: Industrialized construction firms can use this paper as an approach to understand and map their information flows to identify suitable approaches to generate and manage materials passports. Originality/value: The specific characteristics of product platforms and industrialized construction provide a unique opportunity for circular information flow across the building lifecycle, which can support material passport adoption to a degree not often found in the traditional construction industry.

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Ontologies play a pivotal role in knowledge representation, particularly beneficial for the Architecture, Engineering, and Construction (AEC) sector due to its inherent data diversity and intricacy. Despite the growing interest in ontology and data integration research, especially with the advent of knowledge graphs and digital twins, a noticeable lack of consolidated academic synthesis still needs to be addressed. This review paper aims to bridge that gap, meticulously analysing 142 journal articles from 2000 to 2021 on the application of ontologies in the AEC sector. The research is segmented through systematic evaluation into ten application domains within the construction realm- process, cost, operation/maintenance, health/safety, sustainability, monitoring/control, intelligent cities, heritage building information modelling (HBIM), compliance, and miscellaneous. This categorisation aids in pinpointing ontologies suitable for various research objectives. Furthermore, the paper highlights prevalent limitations within current ontology studies in the AEC sector. It offers strategic recommendations, presenting a well-defined path for future research to address these gaps.

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In the realm of construction production control, effective communication across operational levels and the rapid influx of diverse data are essential. Yet, integrating this data faces challenges due to disparate systems and a lack of common terminology, resulting in data silos and hindered interoperability. An ontology-based solution emerges as promising for enhancing interoperability. This research paper introduces the development, implementation, and assessment of the cSite ontology, encompasses several crucial facets necessary for efficient production control such as location, activities, and documents. To evaluate its practicality, a real-case study was conducted, wherein the ontology was employed to answer competency questions through SPARQL queries. Furthermore, interactive dashboards, situated within the construction control rooms, were developed to present the information visually. This paper underscores the transformative potential of integrated and visualised production information in construction projects. Additionally, it illuminates how the cSite ontology can facilitate the development and implementation of construction digital twins.

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Long-term access to lifecycle data is key to a successful transition towards a circular built environment. However, the underlying technology often remains centralized and risks becoming inaccessible over time. In this paper, we investigate whether decentralized access methods using Web3, i.e. blockchain and decentralized data storage protocols, can help to mitigate this limitation. We implement Web3 data access mechanisms for a material passport with both a role-based and a token-based smart contract. Initial results suggest that Web3 offers a promising approach to data access over the lifecycle of a built asset-but only with careful design choices.

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A digital twin (DT) can enhance construction management with comprehensive real-time simulations. However, research rarely considers prefabrication factories, whose processes have a significant impact on cost and duration. It remains unclear how construction DTs can achieve their expected benefits without dynamically interacting with the DTs of manufacturing facilities. To address this, a DT integration model is proposed. It builds upon systems theory and describes integration across the three layers objectives, processes, and data & tools. A theoretical example demonstrates potential benefits of integrated DTs. This work can assist researchers and practitioners who are focusing on DTs in the execution phase.@en

A pronounced gap often exists between expected and actual safety performance in the construction industry. The multifaceted causes of this performance gap are resulting from the misalignment between design assumptions and actual construction processes that take place on-site. In general, critical factors are rooted in the lack of interoperability around the building and work-environment information due to its heterogeneous nature. To overcome the interoperability challenge in safety management, this paper represents the development of an ontological model consisting of terms and relationships between these terms, creating a conceptual information model for construction safety management and linking that ontology to IfcOWL. The developed ontology, named Safety and Health Exchange (SHE), comprises eight concepts and their relationships required to identify and manage safety risks in the design and planning stages. The main concepts of the developed ontology are identified based on reviewing accident cases from 165 Reporting of Injuries, Diseases and Dangerous Occurrences Regulations (RIDDOR) and 31 Press Releases from the database of the Health and Safety Executive (HSE) in the United Kingdom. Consequently, a semantic mapping between the developed ontology and IfcOWL (the most popular ontology and schema for interoperability in the AEC sector) is proposed. Then several SPARQL queries were developed and implemented to evaluate the semantic consistency of the developed ontology and the cross-mapping. The proposed ontology and cross-mapping gained recognition for its innovation in utilising OpenBIM and won the BuildingSMART professional research award 2020. This work could facilitate developing a knowledge-based system in the BIM environment to assist designers in addressing health and safety issues during the design and planning phases in the construction sector.

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Material passports have been proposed to collect, store, and share material information to promote circularity in the construction sector. However, the current recommendations for material passports focus on material information at a building scale with little attention to its implications on a city scale. To address this limitation, this paper provides directions for developing a material passport ontology that could be used to collect, store, share, and retrieve data at multiple scales of abstraction. It describes the requirements for a material passport ontology and provides recommendations for integrating existing ontologies. This paper is relevant to researchers developing information management platforms to enable a circular economy.

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With ongoing development of construction digital twins, several works presented in the last couple of years are taking the same approach, solutions, steps, and findings of Building Information Modelling (BIM). This piece of work is questioning if that is enough or we could be misinformed by the BIM’s survivorship bias of what information should be collected, integrated, and visualized in construction sites. This research is a part of ongoing research project exploring the application of construction digital twins through production control rooms. In this research, an ontology related to construction programme and production control (CPPC) is proposed. The proposed ontology is shared representation that specify the terms and relations of production control in construction. The development is based on a real case study in the U.K and it is mapped to existing ontologies such as BOT, DiCon and Prov. The developed ontology was evaluated by automatic consistency checking, evaluating the SPARQL queries against the competency questions and representing the outputs to stakeholders of the selected construction project. The results show that the ontology represents the domain knowledge and demonstrates its’ efficiency to enhance the production control of construction sites.

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The current digital fabrication workflow requires many iterations between design and manufacturing. Automated manufacturability analysis can reduce the number of iterations at the design stage. However, existing approaches that leverage design for manufacturing and assembly (DfMA) do not consider detailed product features and production capabilities. To address this limitation, this paper utilizes an ontology-based approach to connect design and manufacturing knowledge. The developed manufacturability analysis system (MAS) involves semantic reasoning to analyze manufacturability by combining feature-based modelling, production capability modelling and manufacturing rules. The system was tested on a timber panelized project to demonstrate complex manufacturability analysis capability. The testing proves that the system could provide real-time feedback to the designers, leading to fewer design iterations. Thus, the paper is a first step towards automated fabrication-aware design and the results from the study lay the foundation for future research on connecting knowledge for interdisciplinary rule checking

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Look-ahead planning is the stage in construction planning where information from diverse sources is integrated and plans developed for the next six/eight weeks. Poor planning of construction site activities at this stage often results in cost overruns and schedule delays. This work presents a novel Look-Ahead Schedule (LAS) generation method, which uses reinforcement learning and linked-data based constraint checking within the reward, to address the issues associated with manual look-ahead planning and help construction professionals efficiently plan construction activities at this stage. Our proposal can generate conflict-free LAS significantly faster than conventional methods, demonstrating its capability as a decision support tool during look-ahead planning meetings. Therefore, this paper extends existing knowledge in the construction informatics domain by demonstrating the application of reinforcement learning to aid data-driven look-ahead planning.

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Extending current work on visualization in the Architecture, Engineering, and Construction (AEC) sector, this paper describes an industry-led collaborative research and innovation project to develop and use a control room on the construction site. The work is inspired by NASA mission operations, with its large-scale visual display. It addresses the challenges of visualizing realtime construction data. Working with a main contractor, technology companies, and other researchers, we first give an overview of the progress of the overall project to date and discuss our contributions on requirements, realtime simulation of construction data, and visualization. We conclude by discussing the contribution to work on visualizing construction.

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There has been much work on Scan-vs-BIM, and it has implications on construction productivity, quality, and safety. However, these methods need to be extended /altered to do real-time Scan-vs-BIM. This paper presents the extensions for existing methods such as registration, point matching, object detection, and pose estimation to cater to real-time Scan-vs-BIM. Further, we describe the applications for such methods in construction and describes the challenges for their implementation. We conclude by implication of this paper on researchers working on augmented reality and construction robotics.@en