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Proposal of an Artefact in the Design of BIM Systematizing Lean Concepts and Tools through Neural Networks

Author(s): ORCID
ORCID
ORCID
Medium: journal article
Language(s): English
Published in: Buildings, , n. 4, v. 13
Page(s): 1020
DOI: 10.3390/buildings13041020
Abstract:

Research studies related to BIM go beyond the use of models where other tools are applied in synergy. Lean, for example, has been inserted with the perspective of improving processes both qualitatively and quantitatively and goes beyond the technological aspects, covering behavioural and cultural issues. Studies related to the simultaneous applications of Lean and BIM have shown several benefits but also several adversities inside the BIM cycle. Having raised this gap, this work aimed to identify existing adversities in the design phase of BIM through a systematic literature review and enable a method to guide the main causal factors in this stage for companies that work with BIM using artificial neural networks, to build an artefact composed of Lean concepts and tools that promote simple alternatives to be applied in companies. The obtained results indicated that obstacles to the application of Lean and BIM in the design phase are related to technology, cost, management, shortage of professionals, data interoperability and changes to workflow processes. An analysis including standards and guidelines can be useful to understand the company’s processes and apply BIM protocols in order to collect particularities and aspects to be implemented.

Copyright: © 2023 by the authors; licensee MDPI, Basel, Switzerland.
License:

This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met.

  • About this
    data sheet
  • Reference-ID
    10728172
  • Published on:
    30/05/2023
  • Last updated on:
    01/06/2023
 
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