A Three Methods Proactive Improvement Model for Buildings Construction Processes
Abdul-Aziz Banawi,
Alia Besné,
David Fonseca and
Jose Ferrandiz
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Abdul-Aziz Banawi: Department of Construction Management and Engineering, North Dakota State University, Fargo, ND 58108, USA
Alia Besné: Gretel-Group de REcerca on Technology Enhanced Learning, La Salle, Ramon Llull University, 08022 Barcelona, Spain
David Fonseca: Gretel-Group de REcerca on Technology Enhanced Learning, La Salle, Ramon Llull University, 08022 Barcelona, Spain
Jose Ferrandiz: Technology Department, Nortfolk State University, Nortfolk, VA 23504, USA
Sustainability, 2020, vol. 12, issue 10, 1-14
Abstract:
This paper proposes a proactive model to improve the overall performance of construction processes. The main advantage is that potential waste and associate impacts could be identified in the early stages of a project before the construction phase. To accomplish that, the model combines three methods; Lean-to identify waste, Green to assess environmental impact, and Six-Sigma to measure and improve process performance (LG6). The LG6 model helps in evaluating processes one step at a time, identifying consumed resources, analyzing the environmental performance of all steps as well as highlighting generated impacts, applying improving alternatives if needed, and measuring process performance for evaluation. The functionality of LG6 is illustrated through a case study of woodpiles installation. In this case study, the LG6 model identified four steps out of eight that are considered potential waste or (non-value-added steps) according to the Lean principles. As a result, the LG6 model helped in reducing impact by 9% and expenses by 1%. The LG6 model can help to improve the performance of construction processes and reduces unnecessary waste.
Keywords: lean construction; Six-sigma; green building; construction process improvement (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:12:y:2020:i:10:p:4335-:d:362827
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