Digitised engineering knowledge for prefabricated façades

Façade design is a multidisciplinary activity requiring the balancing of many conflicting design requirements. Very often, however, the designed façade does not respond to these requirement, as relevant design and manufacturing knowledge, normally originating downstream in the design process, is not properly used upstream in the process. The inability to respond to this challenge increases the environmental impact of the construction sector, which is currently covering nearly 40% of the global emissions. Also, improving the stagnant sector’s productivity is of paramount importance today, as it is deemed to be nearly as half as that of the manufacturing sector. This research has thus investigated ways to collect, store, represent and digitalise the engineering knowledge that underpins the design of façade products for façades that are better designed. The work has involved a close collaboration with the British general contractor (and façade manufacturer) Laing O’Rourke. The research has explored ways of using design and manufacturing knowledge and it has developed a digital tool and tested its functionalities. In the first part, after a review of the state-of-the-art in knowledge-based approaches in other fields, the digital tool, and relevant methodology, are developed. The tool informs the user about the expected performance and manufacturability of the façade product under analysis. The boundaries of traditional research were also pushed beyond the proof-of-concept by validating the digital tool in both simulated and real-world scenarios. The goal was to understand how people can develop a design solution while being supported by a digital tool. It was found that using such tool increases the user’s awareness about the consequences of the his/her choices in less time. In the last part of the research, the tool was used to develop a novel optimisation algorithm, by including considerations about aesthetics and manufacturability, in parallel with the traditional performance-based approach. The application of the algorithm to a case study has shown that it is possible to improve existing solutions in terms of performance, without affecting aesthetic and manufacturability significantly.EPSRC, Laing O'Rourk

On the use of Artificial Neural Networks in Topology Optimisation

The question of how methods from the field of artificial intelligence can help improve the conventional frameworks for topology optimisation has received increasing attention over the last few years. Motivated by the capabilities of neural networks in image analysis, different model-variations aimed at obtaining iteration-free topology optimisation have been proposed with varying success. Other works focused on speed-up through replacing expensive optimisers and state solvers, or reducing the design-space have been attempted, but have not yet received the same attention. The portfolio of articles presenting different applications has as such become extensive, but few real breakthroughs have yet been celebrated. An overall trend in the literature is the strong faith in the "magic" of artificial intelligence and thus misunderstandings about the capabilities of such methods. The aim of this article is therefore to present a critical review of the current state of research in this field. To this end, an overview of the different model-applications is presented, and efforts are made to identify reasons for the overall lack of convincing success. A thorough analysis identifies and differentiates between problematic and promising aspects of existing models. The resulting findings are used to detail recommendations believed to encourage avenues of potential scientific progress for further research within the field.Comment: 36 pages, 7 figures (13 figures counting sub-figures), accepted for publication in Structural and Multidisciplinary Optimizatio

Integrated Approaches to Digital-enabled Design for Manufacture and Assembly: A Modularity Perspective and Case Study of Huoshenshan Hospital in Wuhan, China

Countries are trying to expand their healthcare capacity through advanced construction, modular innovation, digital technologies and integrated design approaches such as Design for Manufacture and Assembly (DfMA). Within the context of China, there is a need for stronger implementation of digital technologies and DfMA, as well as a knowledge gap regarding how digital-enabled DfMA is implemented. More critically, an integrated approach is needed in addition to DfMA guidelines and digital-enabled approaches. For this research, a mixed method was used. Questionnaires defined the context of Huoshenshan Hospital, namely the healthcare construction in China. Then, Huoshenshan Hospital provided a case study of the first emergency hospital which addressed the uncertainty of COVID-19. This extreme project, a 1,000-bed hospital built in 10 days, implemented DfMA in healthcare construction and provides an opportunity to examine the use of modularity. A workshop with a design institution provided basic facts and insight into past practice and was followed by interviews with 18 designers, from various design disciplines, who were involved in the project. Finally, multiple archival materials were used as secondary data sources. It was found that complexity hinders building systems integration, while reinforcement relationships between multiple dimensions of modularity (across organisation-process-product-supply chain dimensions) are the underlying mechanism that allows for the reduction of complexity and the integration of building systems. Promoting integrated approaches to DfMA relies on adjusting and coupling multi-dimensional modular reinforcement relationships (namely, relationships of modular alignment, modular complement, and modular incentive). Thus, the building systems integrator can use these three approaches to increase the success of digital-enabled DfMA