In a construction project schedule, delays in delivery are one of the most important problems. Delays can be caused by several project components; however, the issue is amplified when delays occur simultaneously. Classifying delays is relevant in order to allocate responsibility to the parties. In Italy, the delay in the delivery of medium and large-sized works in residential urban centers is about 15% compared to the project forecast. Moreover, the AECO sector’s ability to adapt to emerging challenges, such as environmental sustainability and digitization, is limited by the lack of innovation in management methods. The aim of this research is to create a methodology for managing the built and to-be-built environment in a digital way. This will optimize the building process by reducing delays and waste of resources. The methodology will use tools such as digital twin (DT), Building Information Modeling (BIM), Internet of Things (IoT), and Artificial Intelligence (AI) algorithms. The integration of lean construction practices can make the use of these technologies even more efficient, supporting better workflow management by using the BIM environment. The paper presents a methodology that can be applied to various scaling factors and scenarios. It is also useful for construction sites that are already in progress. As highlighted below, this brings significant economic-temporal advantages.

Digital management methodology for building production optimization through digital twin and artificial intelligence integration / Piras, G.; Muzi, F.; Tiburcio, V. A.. - In: BUILDINGS. - ISSN 2075-5309. - 14:7(2024), pp. 1-23. [10.3390/buildings14072110]

Digital management methodology for building production optimization through digital twin and artificial intelligence integration

Piras G.
Primo
;
Muzi F.
Secondo
;
Tiburcio V. A.
Ultimo
2024

Abstract

In a construction project schedule, delays in delivery are one of the most important problems. Delays can be caused by several project components; however, the issue is amplified when delays occur simultaneously. Classifying delays is relevant in order to allocate responsibility to the parties. In Italy, the delay in the delivery of medium and large-sized works in residential urban centers is about 15% compared to the project forecast. Moreover, the AECO sector’s ability to adapt to emerging challenges, such as environmental sustainability and digitization, is limited by the lack of innovation in management methods. The aim of this research is to create a methodology for managing the built and to-be-built environment in a digital way. This will optimize the building process by reducing delays and waste of resources. The methodology will use tools such as digital twin (DT), Building Information Modeling (BIM), Internet of Things (IoT), and Artificial Intelligence (AI) algorithms. The integration of lean construction practices can make the use of these technologies even more efficient, supporting better workflow management by using the BIM environment. The paper presents a methodology that can be applied to various scaling factors and scenarios. It is also useful for construction sites that are already in progress. As highlighted below, this brings significant economic-temporal advantages.
2024
AI; BIM; building production; digital management; digital twin; IoT; machine learning
01 Pubblicazione su rivista::01a Articolo in rivista
Digital management methodology for building production optimization through digital twin and artificial intelligence integration / Piras, G.; Muzi, F.; Tiburcio, V. A.. - In: BUILDINGS. - ISSN 2075-5309. - 14:7(2024), pp. 1-23. [10.3390/buildings14072110]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1717005
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