A theoretical framework to align lean construction techniques in the 4.0 building industry

01 Pubblicazione su rivista
Fioravanti Antonio, Novembri Gabriele, Rossini FRANCESCO LIVIO
ISSN: 2036-1602

The research is oriented towards the definition of appropriate methodologies useful to seize the opportunities that the paradigm of industry 4.0 offers to the building industry. Hence, the goal is, on the basis of literature review and tests on methods and techniques currently used, to outline a methodology that, using the IoT, can give new spaces of application to Lean methodologies in the construction sector: the aim is, definitively, the improvement of the quality of the process through the optimization of resources, material and immaterial, to be used throughout the Life Cycle of the building.
Considering the complexity of the Construction Process, even for small to medium projects, it is necessary to design on collaborative digital platforms, starting from the BIM approach: in this scenario, all the problems related to the ‘BIM Utopia’ are investigated, such as the limits of interoperability, the slow adaptation of the construction chain to the procedures of good practice and the use of digital tools, as well as market fragmentation, which is very marked in culturally ‘handcrafted’ contexts, such as the Italian one.
In the development of these studies, prototypes have been formalized that can support the designer in the validation of the project, through iterative agent-based tests, as well as the definition of the most appropriate phases and sequences of construction, to fluidify the building production and therefore limit the waste of resources and time. As a result of these experiences it is therefore necessary to broaden the field of exploration towards an increasingly pervasive use of interconnected tools, with the dual objective of constantly having the opportunity to monitor the site, in addition to collecting an important database, useful to sediment the knowledge (global and specialized) necessary to further develop predictive tool capable to provide designer a variety of choices to improve the project in a Lean way.

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