Waste management using lean construction and building infrmoation modelling: systematic literature review

Construction waste chains are propagated into interrelated, fuzzy, and complex nature, which make them challenging to address. The conventional approaches have failed in treating construction waste because they focus on waste symptoms instead of diagnosis the root causes. Additionally, there are few attempts to capture the whole taxonomies of waste based on the theory of production in construction. The synergies of Lean and BIM are well-documented improvements to construction production theory and practices and constituted the foundations to provide productivity improvements, automated workflows, and sustainable development. Lean-BIM facilitates significant analytical and actionable measures towards construction waste, by attacking waste at source, and limiting its’ occurrence. However, many measures to address waste elimination are not explored collectively. Thus, this paper reviews the impact of Lean and BIM synergies on waste taxonomies and elimination methods. Four main areas of knowledge communicated over the period 2000-2019, production planning and control systems; design management; supply chain management; and pursuits towards sustainable lean construction. Based on a systematic review of 32 published papers in academic journals and conference proceedings. There is a great need to provide more evidence-based research that reports lean metrics and BIM workflows impacts on core construction wastes. Research insights and future developments towards waste elimination identified and suggested, not only from a production point of view but also sustainable dimensions

Investigating the use of ChatGPT for the scheduling of construction projects

Large language models such as ChatGPT have the potential to revolutionize the construction industry by automating repetitive and time-consuming tasks. This paper presents a study in which ChatGPT was used to generate a construction schedule for a simple construction project. The output from ChatGPT was evaluated by a pool of participants that provided feedback regarding their overall interaction experience and the quality of the output. The results show that ChatGPT can generate a coherent schedule that follows a logical approach to fulfill the requirements of the scope indicated. The participants had an overall positive interaction experience and indicated the great potential of such a tool to automate many preliminary and time-consuming tasks. However, the technology still has limitations, and further development is needed before it can be widely adopted in the industry. Overall, this study highlights the potential of using large language models in the construction industry and the need for further research.Comment: 14 pages, 6 figure

Artificial intelligence in the construction industry: A review of present status, opportunities and future challenges

© 2021 The Authors. The growth of the construction industry is severely limited by the myriad complex challenges it faces such as cost and time overruns, health and safety, productivity and labour shortages. Also, construction industry is one the least digitized industries in the world, which has made it difficult for it to tackle the problems it currently faces. An advanced digital technology, Artificial Intelligence (AI), is currently revolutionising industries such as manufacturing, retail, and telecommunications. The subfields of AI such as machine learning, knowledge-based systems, computer vision, robotics and optimisation have successfully been applied in other industries to achieve increased profitability, efficiency, safety and security. While acknowledging the benefits of AI applications, numerous challenges which are relevant to AI still exist in the construction industry. This study aims to unravel AI applications, examine AI techniques being used and identify opportunites and challenges for AI applications in the construction industry. A critical review of available literature on AI applications in the construction industry such as activity monitoring, risk management, resource and waste optimisation was conducted. Furthermore, the opportunities and challenges of AI applications in construction were identified and presented in this study. This study provides insights into key AI applications as it applies to construction-specific challenges, as well as the pathway to realise the acrueable benefits of AI in the construction industry.Engineering and Physical Sciences Research Council (EPSRC), UK (Grant Reference No. EP/S031480/