student
Moscow, Russian Federation
UDC 004.94
Modern construction production has become significantly more complex: quality requirements are constantly increasing, and tolerances that were previously acceptable are becoming unacceptable. At the same time, on most Russian construction sites a traditional control system is still used, based on the work of an inspector with paper documentation, selective measurements and inspection reports, which has hardly changed in recent years. As the technical and organizational complexity of facilities increases, its effectiveness decreases, which leads to an increase in the amount of rework, violations of deadlines and the emergence of safety problems already at the stage of operation of structures. It makes sense to consider whether information modeling can offer a new approach to this problem. The study is based on an analysis of the regulatory and legal framework of the Russian Federation in the field of information modeling, a review of domestic and foreign works on the digitalization of construction, and a generalization of practical experience in the use of BIM technologies for quality control on real projects. As a result, four key shortcomings of the traditional control system have been identified: the fragmentary nature of inspections, the high share of subjectivity in assessments, delayed detection of deviations and the lack of a unified information space for all participants in the process. On the basis of these findings, a conceptual model of a digital quality control system based on information modeling technologies has been developed and proposed. The use of such a system makes it possible to reduce the number of design errors, increase the safety index, reduce the time of inspection rounds and reduce the overall costs of project implementation.
construction quality control, information modeling, BIM technologies, digital transformation, asset information model, automation of control processes, traceability, risk-based approach, construction supervision, common data environment
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