Towards a semantic Construction Digital Twin: directions for future research

As the Architecture, Engineering and Construction sector is embracing the digital age, the processes involved in the design, construction and operation of built assets are more and more influenced by technologies dealing with value-added monitoring of data from sensor networks, management of this data in secure and resilient storage systems underpinned by semantic models, as well as the simulation and optimisation of engineering systems. Aside from enhancing the efficiency of the value chain, such information-intensive models and associated technologies play a decisive role in minimising the lifecycle impacts of our buildings. While Building Information Modelling provides procedures, technologies and data schemas enabling a standardised semantic representation of building components and systems, the concept of a Digital Twin conveys a more holistic socio-technical and process-oriented characterisation of the complex artefacts involved by leveraging the synchronicity of the cyber-physical bi-directional data flows. Moreover, BIM lacks semantic completeness in areas such as control systems, including sensor networks, social systems, and urban artefacts beyond the scope of buildings, thus requiring a holistic, scalable semantic approach that factors in dynamic data at different levels. The paper reviews the multi-faceted applications of BIM during the construction stage and highlights limits and requirements, paving the way to the concept of a Construction Digital Twin. A definition of such a concept is then given, described in terms of underpinning research themes, while elaborating on areas for future research

Development of OntEIR framework to support BIM clients in construction

This paper discusses an ongoing research that is conducted to develop a framework that will support employers in making informed and sound decision in defining their requirements. The aim of this research is to develop an ontology-based, BIM enabled framework for EIR (OntEIR), it will examine the ability of this framework in capturing, analysing, and translating these requirements based on an ontology model. This framework will enable the project team to capture requirements and convert them to constructional terms understood by all stakeholders. It is the contention of this research that this process will save time, effort and cost, and will provide an informed basis for delivering a successful project that satisfies both the employer and the supply chain

Key functions in BIM-based AR platforms

The integration of Augmented Reality and Building Information Modelling is a promising area of research; however, fragmentation in literature hinders the development of mature BIM-based AR platforms. This paper aims to minimise the fragmentation in the literature by identifying the key functions that represent the essential capabilities of BIM-AR platforms. A systematic literature review is employed to identify, categorise, and discuss the key functions. The outcome of this paper identifies six key functions: positioning (P), interaction (I), visualisation (V), collaboration (C), automation (A), and integration (T). These key functions act as the foundation for an evaluation framework that can assist practitioners, developers, and researchers with assessing the requirements of the targeted application area, and hence be better informed on the appropriate devices, software, and techniques to use. Finally, this paper emphasises the importance of industrial-academic collaboration in BIM-AR research and suggests prospects for automation through the application of artificial intelligence

Streamlining Digital Modeling and Building Information Modelling (BIM) Uses for the Oil and Gas Projects

The oil and gas industry is a technology-driven industry. Over the last two decades, it has heavily made use of digital modeling and associated technologies (DMAT) to enhance its commercial capability. Meanwhile, the Building Information Modelling (BIM) has grown at an exponential rate in the built environment sector. It is not only a digital representation of physical and functional characteristics of a facility, but it has also made an impact on the management processes of building project lifecycle. It is apparent that there are many similarities between BIM and DMAT usability in the aspect of physical modeling and functionality. The aim of this study is to streamline the usage of both DMAT and BIM whilst discovering valuable practices for performance improvement in the oil and gas projects. To achieve this, 28 BIM guidelines, 83 DMAT academic publications and 101 DMAT vendor case studies were selected for review. The findings uncover (a) 38 BIM uses; (b) 32 DMAT uses and; (c) 36 both DMAT and BIM uses. The synergy between DMAT and BIM uses would render insightful references into managing efficient oil and gas’s projects. It also helps project stakeholders to recognise future investment or potential development areas of BIM and DMAT uses in their projects

Game-like interactive environment using BIM-Based Virtual Reality for the Timber Frame Self-Build Housing Sector

BIM, gamification, and Virtual Reality applications are more often used to serve the interests of Design for Manufacture and Assembly (DfMA). This paper presents a comprehensive study to exploit these technologies’ innovative approaches and capabilities. The study is specifically adopted to implement small and medium-size architectural and construction practices with a limited budget and time dedicated to visualisation creation. The collected evidence proved that a game-like platform combined with BIM could provide simplified data delivery to a client, leading to customer satisfaction, confidence and increased sales. The designed workflow and templates were tested in the case study of a small self-build construction company. The staff was trained to provide BIM data correctly and use supplied game templates. The case study demonstrated that automation of the VR House Configurator creation is achievable. The study’s outcome is an integrated solution to regenerate BIM models in the game environment and utilise the house configurator’s organised furniture library and costing interface. Furthermore, the usability tests confirmed the applicability, practicability, and validity of the developed framework and tools to deal with the revealed challenges in the self-build sector. Finally, the research provided a fresh approach for the companies in the sector, a step-by-step guide for implementing the innovative changes, and detailed descriptions of the methodologies and workflows

Digital Twins for the built environment: Learning from conceptual and process models in manufacturing

The overall aim of this paper is to contribute to a better understanding of the Digital Twin (DT) paradigm in the built environment by drawing inspiration from existing DT research in manufacturing. The DT is a Product Life Management information construct that has migrated to the built environment while research on the subject has grown intensely in recent years. Common to early research phases, DT research in the built environment has developed organically, setting the basis for mature definitions and robust research frameworks. As DT research in manufacturing is the most developed, this paper seeks to advance the understanding of DTs in the built environment by analysing how the DT systems reported in manufacturing literature are structured and how they function. Firstly, this paper presents a thorough review and a comparison of DT, cyber-physical systems (CPS), and building information modelling (BIM). Then, the results of the review and categorisation of DT structural and functional descriptions are presented. Fifty-four academic publications and industry reports were reviewed, and their structural and functional descriptions were analysed in detail. Three types of structural models (i.e. conceptual models, system architectures, and data models) and three types of functional models (process and communication models) were identified. DT maturity models were reviewed as well. From the reviewed descriptions, four categories of DT conceptual models (prototypical, model-based, interface-oriented, and service-based) and six categories of DT process models (DT creation, DT synchronisation, asset monitoring, prognosis and simulation, optimal operations, and optimised design) were defined and its applicability to the AECO assessed. While model-based and service-based models are the most applicable to the built environment, amendments are still required. Prognosis and simulation process models are the most widely applicable for AECO use-cases. The main contribution to knowledge of this study is that it compiles the DT’s structural and functional descriptions used in manufacturing and it provides the basis to develop DT conceptual and process models specific to requirements of the built environment sectors

Developing a Digital Twin at Building and City Levels: A Case Study of West Cambridge Campus

A digital twin (DT) refers to a digital replica of physical assets, processes, and systems. DTs integrate artificial intelligence, machine learning, and data analytics to create living digital simulation models that are able to learn and update from multiple sources as well as represent and predict the current and future conditions of physical counterparts. However, current activities related to DTs are still at an early stage with respect to buildings and other infrastructure assets from an architectural and engineering/construction point of view. Less attention has been paid to the operation and maintenance (O&M) phase, which is the longest time span in the asset life cycle. A systematic and clear architecture verified with practical use cases for constructing a DT would be the foremost step for effective operation and maintenance of buildings and cities. According to current research about multitier architectures, this paper presents a system architecture for DTs that is specifically designed at both the building and city levels. Based on this architecture, a DT demonstrator of the West Cambridge site of the University of Cambridge in the UK was developed that integrates heterogeneous data sources, supports effective data querying and analysis, supports decision-making processes in O&M management, and further bridges the gap between human relationships with buildings/cities. This paper aims at going through the whole process of developing DTs in building and city levels from the technical perspective and sharing lessons learned and challenges involved in developing DTs in real practices. Through developing this DT demonstrator, the results provide a clear roadmap and present particular DT research efforts for asset management practitioners, policymakers, and researchers to promote the implementation and development of DT at the building and city levels

Digital twin in aerospace industry: a gentle introduction

Digital twin (DT), primarily a virtual replica of any conceivable physical entity, is a highly transformative technology with profound implications. Whether it be product development, design optimisation, performance improvement, or predictive maintenance, digital twins are changing the ways work is undertaken in various industries with multifarious business applications. Aerospace industry, including its manufacturing base, is one such keen adopter of digital twins with an unprecedented interest in their bespoke design, development, and implementation across wider operations and critical functions. This, however, comes with some misconceptions about the digital twin technology and lack of understanding with respect to its optimal implementation. For instance, equating a digital twin to an intelligent model while ignoring the essential components of data acquisition and visualisation, misleads the creators into building digital shadow or digital models, instead of the actual digital twin. This paper unfolds such intricacies of digital twin technology for the aerospace community in particular and others in general so as to remove the fallacies that affect their effective realisation for safety-critical systems. It comprises a comprehensive survey of digital twins and their constituent elements. Elaborating their characteristic state-of-the-art composition along with corresponding limitations, three dimensions of the future digital twins for the aerospace sector, termed as aero-Digital Twins (aero-DTs), are proposed as an outcome of this survey. These include the interactive, standardisation, and cognitive dimensions of digital twins, which if leveraged diligently could help the aero-DT research and development community quadruple the efficiency of existing and future aerospace systems as well as their associated processes

Digital Twins in Industry

Digital Twins in Industry is a compilation of works by authors with specific emphasis on industrial applications. Much of the research on digital twins has been conducted by the academia in both theoretical considerations and laboratory-based prototypes. Industry, while taking the lead on larger scale implementations of Digital Twins (DT) using sophisticated software, is concentrating on dedicated solutions that are not within the reach of the average-sized industries. This book covers 11 chapters of various implementations of DT. It provides an insight for companies who are contemplating the adaption of the DT technology, as well as researchers and senior students in exploring the potential of DT and its associated technologies