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The building stock accounts for a significant portion of worldwide energy consumption and greenhouse gas emissions. While the majority of the existing building stock has poor energy performance, deep renovation efforts are stymied by a wide range of human, technological, organisational and external environment factors across the value chain. A key challenge is integrating appropriate human resources, materials, fabrication, information and automation systems and knowledge management in a proper manner to achieve the required outcomes and meet the relevant regulatory standards, while satisfying a wide range of stakeholders with differing, often conflicting, motivations. RINNO is a Horizon 2020 project that aims to deliver a set of processes that, when working together, provide a system, repository, marketplace and enabling workflow process for managing deep renovation projects from inception to implementation. This paper presents a roadmap for an open renovation platform for managing and delivering deep renovation projects for residential buildings based on seven design principles. We illustrate a preliminary stepwise framework for applying the platform across the full-lifecycle of a deep renovation project. Based on this work, RINNO will develop a new open renovation software platform that will be implemented and evaluated at four pilot sites with varying construction, regulatory, market and climate contexts.
Theo Lynn; Pierangelo Rosati; Antonia Egli; Stelios Krinidis; Komninos Angelakoglou; Vasileios Sougkakis; Dimitrios Tzovaras; Mohamad Kassem; David Greenwood; Omar Doukari. RINNO: Towards an Open Renovation Platform for Integrated Design and Delivery of Deep Renovation Projects. Sustainability 2021, 13, 6018 .
AMA StyleTheo Lynn, Pierangelo Rosati, Antonia Egli, Stelios Krinidis, Komninos Angelakoglou, Vasileios Sougkakis, Dimitrios Tzovaras, Mohamad Kassem, David Greenwood, Omar Doukari. RINNO: Towards an Open Renovation Platform for Integrated Design and Delivery of Deep Renovation Projects. Sustainability. 2021; 13 (11):6018.
Chicago/Turabian StyleTheo Lynn; Pierangelo Rosati; Antonia Egli; Stelios Krinidis; Komninos Angelakoglou; Vasileios Sougkakis; Dimitrios Tzovaras; Mohamad Kassem; David Greenwood; Omar Doukari. 2021. "RINNO: Towards an Open Renovation Platform for Integrated Design and Delivery of Deep Renovation Projects." Sustainability 13, no. 11: 6018.
Inefficiencies in the management of earthmoving equipment greatly contribute to the productivity gap of infrastructure projects. This paper develops and tests a Deep Neural Network (DNN) model for estimating the productivity of excavators and establishing a productivity measure for their benchmark. After investigating current practices for measuring the productivity of earthwork equipment during 13 interviews with selected industry experts, the DNN model was developed and tested in one of the ‘High Speed rail second phase’ (HS2) sites. The accuracy of prediction achieved by the DNN model was evaluated using the coefficient of determination (R2) and the Weighted Absolute Percentage Error (WAPE) resulting in 0.87 and 69.64%, respectively. This is an adequate level of accuracy when compared to other similar studies. However, according to the WAPE method, the accuracy is still 10.36% below the threshold (i.e. 80%) expected by the industry experts. An inspection of the prediction results over the testing period (21 days) revealed better precision in days with high excavation volumes compared to days with low excavation volumes. This was attributed to the likely involvement of manual work (i.e. archaeologists in the case of the selected site) alongside some of the excavators, which caused gaps in telematics data. This indicates that the accuracy attained is adequate, but the proposed approach is more accurate in a highly mechanised environment (i.e. excavation work with equipment predominantly and limited manual interventions) compared to a mixed mechanised-manual working environment. A bottom-up benchmark measure (i.e. excavation rate) that can be used to measure and benchmark the excavation performance of an individual or a group of equipment, through a work area, to a whole site was also proposed and discussed.
Mohamad Kassem; Elham Mahamedi; Kay Rogage; Kieren Duffy; James Huntingdon. Measuring and benchmarking the productivity of excavators in infrastructure projects: A deep neural network approach. Automation in Construction 2021, 124, 103532 .
AMA StyleMohamad Kassem, Elham Mahamedi, Kay Rogage, Kieren Duffy, James Huntingdon. Measuring and benchmarking the productivity of excavators in infrastructure projects: A deep neural network approach. Automation in Construction. 2021; 124 ():103532.
Chicago/Turabian StyleMohamad Kassem; Elham Mahamedi; Kay Rogage; Kieren Duffy; James Huntingdon. 2021. "Measuring and benchmarking the productivity of excavators in infrastructure projects: A deep neural network approach." Automation in Construction 124, no. : 103532.
BIM for Facilities Management (BIM for FM) is a relatively new and growing topic of inquiry aiming to fulfil the informational needs of the operational phase of assets within increasingly digitalised project workflows. Research into the management of structured (i.e. graphical and non-graphical) and unstructured data (i.e. documents) has largely focused on design and construction phases. Information management in facilities management and maintenance is still challenged by the lack of a structured framework that can simultaneously fulfil these three capabilities: (1) the delivery of information models (i.e. Asset Information Models) from distributed data sources; (2) the validation of these information models against the requirements; and (3) the use of their information in facilities management (e.g. operation and maintenance). This research aims to develop and test a framework and a prototype Common Data Environment (CDE) to achieve these three capabilities. The framework and the developed CDE are entirely based on use open standards and integration of existing technologies. A requirements model, underpinning the framework and the CDE was developed during three iterative stages of interviews –in line with the adopted Grounded Theory and Design Science Research methodologies– with industry experts and through a three-stage coding process at each iteration. The framework and the CDE were tested in pilot demonstrations with a use case focused on preventive and reactive maintenance. The testing demonstrated that the implementation of ‘BIM for FM’ processes is feasible with the proposed framework and CDE relying entirely on open standards and existing technologies. Some additional requirements for BIM for FM processes were also identified during the verification sessions with industry and are proposed for future research.
João Patacas; Nashwan Dawood; Mohamad Kassem. BIM for facilities management: A framework and a common data environment using open standards. Automation in Construction 2020, 120, 103366 .
AMA StyleJoão Patacas, Nashwan Dawood, Mohamad Kassem. BIM for facilities management: A framework and a common data environment using open standards. Automation in Construction. 2020; 120 ():103366.
Chicago/Turabian StyleJoão Patacas; Nashwan Dawood; Mohamad Kassem. 2020. "BIM for facilities management: A framework and a common data environment using open standards." Automation in Construction 120, no. : 103366.
Field BIM and its enabling Mobile BIM Technologies (MBT) are increasingly recognised for their role in improving collaboration and integration between project teams on construction sites. Very limited research about the development and applications of Field BIM and MBT is available in the literature. The few available studies have generally focused on specific types of MBT and their application on a single project or individual use cases. A framework to clarify the technical and business requirements of MBT is still missing. This paper is part of a wider research aiming to develop a holistic framework for MBT and Field BIM consisting of a requirements taxonomy, a benefits evaluation approach linking use cases to relevant performance metrics, and a project and supply chain performance analytics dashboard. This paper presents the findings about the technical and business requirements of MBT, which represents the first step towards the development of the requirements taxonomy.
Benjamin Jowett; Mohamad Kassem. Field BIM: Establishing a Requirements Framework for Mobile BIM Technologies. Lecture Notes in Civil Engineering 2020, 1003 -1013.
AMA StyleBenjamin Jowett, Mohamad Kassem. Field BIM: Establishing a Requirements Framework for Mobile BIM Technologies. Lecture Notes in Civil Engineering. 2020; ():1003-1013.
Chicago/Turabian StyleBenjamin Jowett; Mohamad Kassem. 2020. "Field BIM: Establishing a Requirements Framework for Mobile BIM Technologies." Lecture Notes in Civil Engineering , no. : 1003-1013.
The construction industry is facing many challenges including low productivity, poor regulation and compliance, lack of adequate collaboration and information sharing, and poor payment practices. Advances in distributed ledger technologies (DLT), also referred to as Blockchain, are increasingly investigated as one of the constituents in the digital transformation of the construction industry and its response to these challenges. The overarching aim of this study was to analyse the current state of DLT in the built environment and the construction sector with a view to developing a coherent approach to support its adoption specifically in the construction industry. Three objectives were established to achieve this: (a) to present the first state-of-the-art and literature review on DLT in the built environment and construction industry providing a consolidated view of the applications explored and potential use cases that could support disruption of the construction industry. Seven use-categories were identified: [1] Smart Energy, [2] Smart Cities & the Sharing Economy, [3] Smart Government, [4] Smart Homes, [5] Intelligent Transport, [6] BIM and Construction Management, and [7] Business Models and Organisational Structures; (b) to propose a framework for implementation composed of two conceptual models (i.e. the DLT Four-Dimensional Model, and the DLT Actors Model), developed according to extended socio-technical systems theory and including four dimensions (technical, social, process and policy), to support the development of DLT-based solutions that are adequate to the challenges faced by the construction industry. The DLT Four-Dimensional Model and the DLT Actors Model contribute to improve the understanding of the concepts involved when discussing DLT applications in construction and represent flexible, adaptable and scalable knowledge constructs and foundations that can be used for various further investigations; and (c) to appraise three specific use cases (i.e. Project Bank Accounts, regulation and compliance, and a single shared-access BIM model) as potential areas for DLT through the application of a decision support tool. The results show that Project Bank Accounts (PBAs) and regulation and compliance are candidate areas for DLT applications and warrant further attention. However, for the third use case (i.e. single shared-access BIM model) DLT are still insufficiently developed at this time. The research shows that there is real potential for DLT to support digitalisation in the construction industry and enable solutions to many of its challenges. However, there needs to be further investigation of the readiness of the industry, its organisations and processes, and to evaluate what changes need to occur before implementation can be successful. Further investigations will include the development of a roadmap process incorporating the four dimensions to evaluate readiness across a series of use cases for the construction industry.
Jennifer Li; David Greenwood; Mohamad Kassem. Blockchain in the built environment and construction industry: A systematic review, conceptual models and practical use cases. Automation in Construction 2019, 102, 288 -307.
AMA StyleJennifer Li, David Greenwood, Mohamad Kassem. Blockchain in the built environment and construction industry: A systematic review, conceptual models and practical use cases. Automation in Construction. 2019; 102 ():288-307.
Chicago/Turabian StyleJennifer Li; David Greenwood; Mohamad Kassem. 2019. "Blockchain in the built environment and construction industry: A systematic review, conceptual models and practical use cases." Automation in Construction 102, no. : 288-307.
Building Information Modelling (BIM) is an innovation that is transforming practices within the Architectural, Engineering, Construction and Operation (AECO) sectors. Many studies have investigated the process of BIM adoption and diffusion and in particular, the drivers affecting adoption at different levels, ranging from individual and team through organisations and supply chains to whole market level. However, in-depth investigations of the stages of the BIM adoption process and the drivers, factors and determinants affecting such stages are still lacking. A comprehensive classification and integration of adoption drivers and factors is absent as these are disjointedly identified across disparate studies. There is also limited attention to the key terms and concepts (i.e. readiness, implementation, diffusion, adoption) in this area of study. This aim in this paper is twofold: (1) to develop and validate a Unified BIM Adoption Taxonomy (UBAT); and (2) to identify the taxonomy's constructs (i.e. three driver clusters and their 17 factors) that have influence on the first three stages of the BIM adoption process namely, awareness, interest, and decision stages, and compare their effects on each of the stages. The research uses: a systematic literature review and knowledge synthesisation to develop the taxonomy; a confirmatory factor analysis for its validation; and an ordinal logistic regression to test the effect of the UBAT's constructs on the BIM adoption process within the UK Architectural sector using a sample of 177 organisations. The paper is primarily intended to enhance the reader's understanding of the BIM adoption process and the constructs that influence its stages. The taxonomy and its sets of drivers and determinants can be used to perform various analyses of the BIM adoption process, delivering evidence and insights for decision makers within organisations and across whole market when formulating BIM diffusion strategies.
Ahmed Louay Ahmed; Mohamad Kassem. A unified BIM adoption taxonomy: Conceptual development, empirical validation and application. Automation in Construction 2018, 96, 103 -127.
AMA StyleAhmed Louay Ahmed, Mohamad Kassem. A unified BIM adoption taxonomy: Conceptual development, empirical validation and application. Automation in Construction. 2018; 96 ():103-127.
Chicago/Turabian StyleAhmed Louay Ahmed; Mohamad Kassem. 2018. "A unified BIM adoption taxonomy: Conceptual development, empirical validation and application." Automation in Construction 96, no. : 103-127.