The Practical Implications of Using Fuzzy Logic for Mapping Data for Life Cycle Analysis

Abstract

For the last decade, the focus on sustainability has increased significantly. In the Architectural, Engineering, and Construction industry (AEC), the focus of sustainability is on making a Life Cycle Analysis (LCA) on the different building components. Research indicates that the collaboration between disciplines is limited because of human linguistic failure in BIM models. This research aims to bring forth the principles of mapping data with fuzzy logic algorithms and show the application in a practical collaborative context. With the application of Design Science Research methodology, this research will create an artifact in Dynamo for Revit, with the implementation of fuzzy logic algorithms for mapping LCA data from LCAbyg, is an LCA-program used in the danish AEC industry, and the linguistic data from a BIM model. The research shows that the implementation of a fuzzy logic system is an effective tool for mapping data. The result of the prototype concludes that fuzzy logic algorithms with ease can be used in a collaborative context. The study implies that the AEC industry’s linguistic difference and purity are a limitation on using fuzzy logic algorithms. The research also indicates that the fuzzy logic algorithm used in parallel constellation may cause bad results, and the relegation or exclusion of different algorithms should be investigated. The research also shows that the linguistic deficiencies in LCAbyg concerning the applied linguistic of the industry have a significant implication on fuzzy logic.