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Constructability in industrial plants construction: a BIM-lean approach using the Digital Obeya Room framework

    Daniel Luiz de Mattos Nascimento Affiliation
    ; Elisa Dominguez Sotelino Affiliation
    ; Thiago Pires Santoloni Lara Affiliation
    ; Rodrigo Goyannes Gusmão Caiado Affiliation
    ; Paulo Ivson Affiliation

Abstract

One of the main problems the construction industry faces is the high cost and slow execution time due to inadequate planning, which results in poor use of human resources. A common solution for reducing time and costs is the adoption of prefabricated components (prefabs). This paper proposes a novel methodology for interdisciplinary man­agement of construction projects by integrating Building Information Modeling (BIM) and Lean Thinking to improve the production planning and control of pipe-rack modules in an industrial facility. The article first presents a literature review to assess the key synergies between BIM and Lean Thinking. These led to the development of a new integrated work methodology named Digital Obeya Room. This model focuses on the required workflows, the analysis of collected data, and the visual management of construction planning and control. A real-world empirical study in the Oil and Gas industry evaluated how the newly devised practices could improve prefabrication and preassembly planning. The pro­posed methodology was capable of reducing the welding-time in 8.7% related on global prefabrication average in con­struction projects from Fails Management Institute (FMI) prefabrication report survey 2017.

Keyword : BIM, construction projects, interdisciplinary management, Lean Thinking, PDCA, Obeya Room, constructability, prefabrication, production planning

How to Cite
Nascimento, D. L. de M., Sotelino, E. D., Lara, T. P. S., Caiado, R. G. G., & Ivson, P. (2017). Constructability in industrial plants construction: a BIM-lean approach using the Digital Obeya Room framework. Journal of Civil Engineering and Management, 23(8), 1100-1108. https://doi.org/10.3846/13923730.2017.1385521
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Nov 20, 2017
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This work is licensed under a Creative Commons Attribution 4.0 International License.