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Modularity is an approach to simplify systems and reduce complexity. However, existing research suggests that a mono-dimensional modularity strategy, focusing solely on one dimension, such as product, process, or organisation, might not fully achieve these goals in design activities. This research investigates how combining strategies from various dimensions of modularity can reduce the complexity of large-scale engineering design. The Huoshenshan Hospital, a 1,000-bed hospital designed and built in 10 days, provided an extreme case study of the first emergency hospital to address COVID-19. The research identified ten different aspects, termed 'proximities', which relate to how people perceive the four dimensions of modularity, specifically across organisation-process-productsupply chain dimensions. Additionally, it identified three types of reinforcement relationships aimed at diminishing complexity in design activities: modular alignment (i.e. synchronised alignment and asynchronous alignment), modular complementarity (i.e. subtraction complement and addition complement) and modular incentive relationships. This research highlights that these three types of reinforcement relationships between different dimensions of modularity can reduce complexity, allowing sub-systems to support the system in working as a whole.
Modularity is an approach to simplify systems and reduce complexity. However, existing research suggests that a mono-dimensional modularity strategy, focusing solely on one dimension, such as product, process, or organisation, might not fully achieve these goals in design activities. This research investigates how combining strategies from various dimensions of modularity can reduce the complexity of large-scale engineering design. The Huoshenshan Hospital, a 1,000-bed hospital designed and built in 10 days, provided an extreme case study of the first emergency hospital to address COVID-19. The research identified ten different aspects, termed 'proximities', which relate to how people perceive the four dimensions of modularity, specifically across organisation-process-productsupply chain dimensions. Additionally, it identified three types of reinforcement relationships aimed at diminishing complexity in design activities: modular alignment (i.e. synchronised alignment and asynchronous alignment), modular complementarity (i.e. subtraction complement and addition complement) and modular incentive relationships. This research highlights that these three types of reinforcement relationships between different dimensions of modularity can reduce complexity, allowing sub-systems to support the system in working as a whole.
In this paper, we explore the integration of building information modeling (BIM) technology to assess carbon emissions, emphasizing the unique contributions to smart and sustainable approaches in prefabricated buildings and focusing on the application of digital construction strategies facilitated by BIM to evaluate carbon emissions in green prefabricated buildings, with a detailed case study on C-House at Southeast University, Nanjing, China. The research methodology involved creating a BIM model of C-House in Rhino and collecting data from the operationalization phase. This research work delves into analyzing the structural components, on-site assembling process, and evaluation of carbon emissions by using a BIM-based assessment, as well as the energy load and consumption of prefabricated components, including sustainable PV panels, to enhance building efficiency and sustainability. The findings uncover the life cycle of C-House, which spans seven stages, compared with the five stages of conventional builds. Currently in its third cycle, C-House exhibits significant reductions of 70.57% in carbon emissions during the second cycle and 43.53% in the first one. This highlights the pattern showing that the prolonged reuse of prefabricated buildings leads to decreasing emissions over time. Such results underscore the potential carbon emission reductions and environmental advantages of reusing green prefabricated buildings. Furthermore, this study provides insights into the entire life cycle of the building, from inception to occupation and post-phase performance evaluation. By employing BIM for modeling, simulation, and analysis, we offer practical insights into the application of smart technologies for sustainable construction practices, significantly contributing to the advancement of green and digital construction technologies.
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