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A Three Methods Proactive Improvement Model for Buildings Construction Processes

Authors: Abdul-Aziz Banawi; Alia Besné; David Fonseca; Jose Ferrandiz;

A Three Methods Proactive Improvement Model for Buildings Construction Processes

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.

Related Organizations
Keywords

72, Construcció sostenible, 69, Six-sigma, 69 - Materials de construcció. Pràctiques i procediments de construcció, green building, 504, 504 - Ciències del medi ambient, Arquitectura sostenible, 72 - Arquitectura, construction process improvement, lean construction

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    3
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Average
Average
Average
Green
gold