By Antonia Egli (Dublin City University)

The RINNO blog series on the recently published open access book ‘Disrupting Buildings: Digitalisation and the Transformation of Deep Renovation’ continues with a spotlight on Chapter 3: Building Information Modelling with Dr Omar Doukari, Prof Mohamad Kassem, and Prof David Greenwood. Read on to better understand the potential of building information modelling in deep renovation projects. For timely updates on this blog series, sign up to the RINNO newsletter or follow us on social media here.

The construction industry is undergoing a paradigm shift, and at the forefront of this transformation is Building Information Modelling (BIM). Originally conceived as a computer-aided three-dimensional modelling tool, BIM has evolved into a comprehensive framework that integrates time scheduling, cost management, and information structuring. This evolution positions BIM as a transformative force with the potential to reshape decision-making processes throughout the entire life cycle of built assets.

Understanding BIM: Beyond Modelling

At its core, BIM is more than just a digital representation of a building; it is a dynamic framework that encapsulates both the physical and functional aspects of a facility. The U.S. National Institute of Building Sciences defines BIM as “a digital representation of the physical and functional characteristics of a facility.” BIM isn’t just a model; it’s a process, as defined by Hamil (2022), involving the creation and management of information throughout a project’s life cycle.

BIM in practice (credits: CEM Solutions)

However, despite its transformative potential, the widespread adoption of BIM faces challenges. Hamil and Bain (2021) note that the industry has been tempted to ‘cherry-pick’ convenient elements of BIM, leaving many of its broader aspects overlooked and their benefits untapped. The concept of BIM maturity has been introduced, attempting to measure the industry’s progress in adopting BIM, but barriers such as resistance to change, required software investments, and cybersecurity concerns persist.

The Multidimensional Benefits of BIM

BIM originated as a tool for enhanced 3D design, but its capabilities quickly expanded into various applications, leading to the recognition of BIM dimensions. Beyond the traditional 3D modelling, these dimensions include time scheduling (4D), cost management (5D), sustainability considerations (6D), and life cycle analysis (7D). Each of these dimensions represents an application, allowing for the efficient sharing of data between different functions and throughout the project life cycle.

The applications and benefits of BIM are wide-ranging. Georgiadou (2019) outlines organisational benefits such as design optimisation, improved on-time delivery, cost efficiency, quality assurance, collaboration, and sustainability. Ghaffarianhoseini et al. (2017) add technical superiority, interoperability, information capture, improved cost control, whole-life applicability, and reduced conflict. BIM, in essence, becomes a cornerstone for the industry’s transition to ‘Construction 4.0,’ where innovations like the Internet of Things (IoT), blockchain, artificial intelligence (AI), and modern construction methods (MMC) play a crucial role in shaping the built environment’s future.

The benefits of BIM in construction (credits: Monarch Innovations)

How can BIM mitigate challenges in the realm of deep renovation?

While BIM has made substantial inroads into traditional construction practices, its application in deep renovation projects presents distinctive challenges. Renovation projects, by nature, disrupt existing building occupants, complicating logistics, schedules, and budgets. Deep renovation, focused on maximising energy efficiency, introduces additional complexities as it affects a building’s fabric, services, and structure. Conventional time and cost control techniques often prove inadequate for these projects, leading to delays and cost overruns.

Deep renovation projects are inherently uncertain, often driven by judgement and experience rather than standardised solutions. The disturbance to existing building occupants amplifies construction logistics, schedules, and budgetary challenges. Chaves et al. (2016) highlight disruptions involving utilities, access, use of space, environmental quality, and transport, all of which need mitigation through new technologies and optimised processes.

BIM emerges as a transformative tool to address the intricate demands of deep renovation. The process begins with the capture of point-cloud data through laser scanning, forming the basis for a 3D BIM model. This ‘scan to BIM’ process facilitates building condition assessment, aiding in the prioritisation of renovation options. BIM’s capabilities extend to a common data environment, enabling seamless information exchange among design consultants. Through 4D BIM, project schedules can be meticulously managed, while 5D BIM ensures budgetary control.

From a communication perspective, BIM simulations and visualisations prove useful in mitigating disruption to and by occupants. Passoni et al. (2021) emphasise the need for digital tools based on BIM for identifying, optimising, validating, and communicating different renovation scenarios in terms of cost, time, and effectiveness.

Overcoming Interoperability in BIM Use

Nonetheless, challenges to BIM in deep renovation projects persist. Interoperability and workflow issues hinder the seamless integration of BIM across various design software and project phases. Extracting object information from the 3D model, defining appropriate work breakdown structures, linking these elements with the BIM model, and generating schedule or cost models involve intricate processes that often require manual effort. Automated processes, though theoretically possible, depend on overcoming interoperability challenges and coordinating with the original design.

The Future Landscape: BIM, AI, and Ontologies

Looking ahead, the marriage of BIM with Artificial Intelligence (AI) and Machine Learning (ML) promises groundbreaking solutions. Mulero-Palencia et al. (2021) propose applying AI and ML to BIM models in deep renovation interventions, focusing in particular on the diagnosis and optimisation stages. A current barrier to this integration is the lack of ontologies appropriate for renovation work. Ontologies, fundamental for formalising domain knowledge, are essential for producing machine-readable code that supports process automation. Amorocho and Hartmann (2021) note that comprehensive ontologies for renovation activities are currently lacking, necessitating further development to unlock the full potential of BIM-driven AI solutions.

In conclusion, Chapter 3 of ‘Disrupting Buildings’ delves into the state-of-the-art of BIM, with a specific emphasis on its potential in deep renovation projects. As the construction industry develops towards a digital future, disruptions and uncertainties in deep renovation projects necessitate innovative solutions. BIM, with its multidimensional applications, emerges as a linchpin in overcoming challenges and unlocking efficiencies. The synergy of BIM with emerging technologies, particularly AI and ML, promises not just streamlined processes, but sustainable and efficient built environments. The journey of BIM, from a modelling tool to a comprehensive decision-making framework, continues to redefine the landscape of construction.

References

Amorocho, J. A. P., & Hartmann, T. (2021). Reno-Inst: An ontology to support renovation projects planning and renovation products installation. Advanced Engineering Informatics, 50, 101415.

Chaves, F. J., Tzortzopoulos, P., Formoso, C. T., & Biotto, C. N. (2016). Building Information Modelling to cut disruption in housing retrofit. Proceedings of the Institution of Civil Engineers-Engineering Sustainability, 170(6), 322–333.

Georgiadou, M. C. (2019). An overview of benefits and challenges of Building Information Modelling (BIM) adoption in UK residential projects. Construction Innovation.

Ghaffarianhoseini, A., Tookey, J., Ghaffarianhoseini, A., Naismith, N., Azhar, S., Efimova, O., & Raahemifar, K. (2017). Building Information Modelling (BIM) uptake: Clear benefits, understanding its implementation, risks and challenges. Renewable and Sustainable Energy Reviews, 75, 1046–1053.

Hamil, S. (2022). What is BIM? NBS Enterprises. Retrieved April 30, 2022, from https://www.thenbs.com/knowledge/what-is-building-information-modelling-bim

Hamil, S., & Bain, D. (2021). Digital construction report 2021. NBS Enterprises. Retrieved June 9, 2022, from https://www.thenbs.com/digital-construction-report-2021/

Mulero-Palencia, S., Álvarez-Díaz, S., & Andrés-Chicote, M. (2021). Machine learning for the improvement of deep renovation building projects using as-built BIM models. Sustainability, 13(12), 6576.

Passoni, C., Marini, A., Belleri, A., & Menna, C. (2021). Redefining the concept of sustainable renovation of buildings: State of the art and an LCT-based design framework. Sustainable Cities and Society, 64, 102519.