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A Model for Evaluating Causes of Wastes and Lean Implementation in Construction Projects

Author(s):

Medium: journal article
Language(s): English
Published in: Journal of Civil Engineering and Management, , n. 4, v. 26
Page(s): 331-342
DOI: 10.3846/jcem.2020.12323
Abstract:

The wastes in construction projects such as wastes in materials, time, resources and achieving customer needs can be minimized using the new philosophy of Lean Construction (LC). This paper proposed a two-level model based on fuzzy logic technique for evaluating Causes of Wastes (CWs) and lean implementation in construction projects. The probability of occurrence and importance of CWs were two input parameters in level 01 of the model, whereas the output was the level of waste. On the other hand, level 02 of the model depended on using three input parameters which were: level of waste, controllability level for CWs and lean implementation level, while the output was the lean effect. Several linguistic variables and logical rules were used for relating inputs and outputs and new indices were introduced. The model was applied and validated for data collected in two countries: Egypt and Kingdom of Saudi Arabia (KSA). Results demonstrated that the expected lean effect is found with a positive correlation with various levels of wastes and can be improved by increasing controllability and lean implementation levels. Regarding the comparative study between the two countries, distinct disparities in lean effect were clarified. Most measured CWs indices were different in both countries while indices values in KSA were higher than in Egypt either in waste, controllability or implementation levels. The results presented an optimum arrangement to reach an effective new lean evaluation model that could be implemented for moving the traditional construction towards LC. Finally, the model can be applied easily in most countries to help decision makers in evaluating CWs and lean implementation in their construction projects.

Structurae cannot make the full text of this publication available at this time. The full text can be accessed through the publisher via the DOI: 10.3846/jcem.2020.12323.
  • About this
    data sheet
  • Reference-ID
    10419965
  • Published on:
    16/04/2020
  • Last updated on:
    16/04/2020
 
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