Abstract
The domain area of the article is life cycle management of the construction facilities, where the subject of consideration is the study of digital information models element classification, begun in previous works of the authors, which is part of the thesis. The object of the study is a construction information classifier integrated into the Russian Federation urban planning state information system. The purpose of the article is to analyze the features of the construction information classifier adaptation, as well as to demonstrate its impact on improving the efficiency and accuracy of classification on the base of approbation on a real capital construction object. The expected result is the simplification of the classification process, by automating routine and cyclic processes, which will lead to a labor costs reduction, as well as an overall improvement in information modeling technologies integration and accuracy. As a result of the method modernization described in the previously paper, the tables «Functional Systems» and «Technical Systems» were merged, the first level in the table «Technical Systems» was eliminated, as it serves as information generalization entered in the second level and can be replaced by the second level of the table «Functional System». A multi-level hierarchical table was created, with a structure ranging from two to four levels, providing flexibility and usability. The main conclusion of the article is that the proposed improved classification method based on combining the tables «Functional Systems» and «Technical Systems» of the construction information classifier more than halves the time spent on digital information model elements classifying, and also contributes to better interaction between the investment and construction project participants, increasing the accuracy and quality of work with the model. The authors also conclude that unification and standardization of classification systems (classifiers) taking into account modern requirements and trends in the construction industry are key factors for achieving a high degree of interoperability and efficiency in information modeling.
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