Journal of Construction Engineering and Project Management

Korea Institute of Construction Engineering and Management (한국건설관리학회)
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The Application of Fuzzy Logic to Assess the Performance of Participants and Components of Building Information Modeling

  • Wang, Bohan (The Department of Civil, Environmental and Geodetic Engineering) ;
  • Yang, Jin (The Department of Civil, Environmental and Geodetic Engineering) ;
  • Tan, Adrian (The Department of Civil, Environmental and Geodetic Engineering) ;
  • Tan, Fabian Hadipriono (The Department of Civil, Environmental and Geodetic Engineering) ;
  • Parke, Michael (The Department of Engineering Education Room)
  • Received : 2017.07.11
  • Accepted : 2018.12.30
  • Published : 2018.12.31
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Abstract

In the last decade, the use of Building Information Modeling (BIM) as a new technology has been applied with traditional Computer-aided design implementations in an increasing number of architecture, engineering, and construction projects and applications. Its employment alongside construction management, can be a valuable tool in helping move these activities and projects forward in a more efficient and time-effective manner. The traditional stakeholders, i.e., Owner, A/E and the Contractor are involved in this BIM system that is used in almost every activity of construction projects, such as design, cost estimate and scheduling. This article extracts major features of the application of BIM from perspective of participating BIM components, along with the different phrases, and applies to them a logistic analysis using a fuzzy performance tree, quantifying these phrases to judge the effectiveness of the BIM techniques employed. That is to say, these fuzzy performance trees with fuzzy logic concepts can properly translate the linguistic rating into numeric expressions, and are thus employed in evaluating the influence of BIM applications as a mathematical process. The rotational fuzzy models are used to represent the membership functions of the performance values and their corresponding weights. Illustrations of the use of this fuzzy BIM performance tree are presented in the study for the uninitiated users. The results of these processes are an evaluation of BIM project performance as highly positive. The quantification of the performance ratings for the individual factors is a significant contributor to this assessment, capable of parsing vernacular language into numerical data for a more accurate and precise use in performance analysis. It is hoped that fuzzy performance trees and fuzzy set analysis can be used as a tool for the quality and risk analysis for other construction techniques in the future. Baldwin's rotational models are used to represent the membership functions of the fuzzy sets. Three scenarios are presented using fuzzy MEAN, AND and OR gates from the lowest to intermediate levels of the tree, and fuzzy SUM gate to relate the intermediate level to the top component of the tree, i.e., BIM application final performance. The use of fuzzy MEAN for lower levels and fuzzy SUM gates to reach the top level suggests the most realistic and accurate results. The methodology (fuzzy performance tree) described in this paper is appropriate to implement in today's construction industry when limited objective data is presented and it is heavily relied on experts' subjective judgment.

Keywords

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FIGURE I. TYPICAL PROJECT TEAM ORGANIZATION

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FIGURE II. FUZZY BIM PERFORMANCE TREE

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FIGURE IV. AN Α-CUT LEVEL AT 0.6 FOR FAIRLY HIGH

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FIGURE V. INTEGRATING HIGH AND FAIRLY HIGH TO PRODUCE CLOSE TO FAIRLY HIGH

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FIGURE VI. FUZZY AND FOR VERY POSITIVE AND NEGATIVE PERFORMANCE VALUES

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FIGURE VII. FUZZY OR FOR VERY POSITIVE AND NEGATIVE PERFORMANCE VALUES

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FIGURE VIII. FUZZY MEAN OF VERY POSITIVE AND NEGATIVE PERFORMANCE VALUES

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FIGURE IX. FUZZY SUM OF VERY POSITIVE AND NEGATIVE PERFORMANCE VALUES

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FIGURE X. PERFORMANCE TREE OF THE BIM APPLICATION WITH FUZZY MEAN AND SUM GATES

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FIGURE XI. PERFORMANCE TREE OF THE BIM APPLICATION WITH FUZZY 'AND' AND 'SUM' GATES

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FIGURE XII. PERFORMANCE TREE OF THE BIM APPLICATION WITH FUZZY 'OR' AND 'SUM' GATES

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FIGURE XIII. BIM FINAL PERFORMANCE: USING FUZZY MEAN TO REACH THE INTERMEDIATE LEVEL

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FIGURE XIV. BIM FINAL PERFORMANCE: USING FUZZY AND TO REACH THE INTERMEDIATE LEVEL

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FIGURE XV. BIM FINAL PERFORMANCE: USING FUZZY OR TO REACH THE INTERMEDIATE LEVEL

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FIGURE III. BALDWIN’S ROTATIONAL MODEL FOR POSITIVE AND NEGATIVE VALUES AND THEIR HEDGES

TABLE I. MAJOR FEATURES OF BIM APPLICATION AND THE RELATIONSHIP AMONG CONSTRUCTION PARTICIPANTS

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TABLE II. BASIC EVENTS AND THEIR DESCRIPTIONS

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TABLE III. PERFORMANCE AND IMPORTANCE VALUES

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TABLE IV. MEMBERSHIP FUNCTIONS FOR BIM PERFORMANCE VALUES

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