Expert review of engineering survey results and design documentation using information modeling technology: a case study of a warehouse facility

Abstract

This article provides a theoretical and practical rationale for a methodology to review engineering survey results and design documentation using building information modeling (BIM) on the example of constructing a warehouse facility. The aim is to develop an integrated model of expert analysis in a digital environment that improves the quality of design solutions and reduces capital construction risks. The study uses an analysis of the current Russian regulatory framework for expert review and information modeling, a synthesis of research on digital transformation of construction expertise, and a structured description of expert process stages for warehouse facilities. Based on a systematization of expert review functions, the paper substantiates the sequence of actions in a BIM environment: checking completeness and reliability of initial survey data and its implementation in the information model; assessing the correctness of the transition from surveys to design documentation; analyzing consistency of architectural, structural, engineering and technological solutions; and verifying that the model complies with regulatory and technical requirements for data format and content. The paper shows that BIM enables visualization of clashes between disciplines, increases transparency of design decisions, and reduces review time through early defect detection and partial automation. For warehouse facilities, specific parameters of expert assessment are highlighted, including loads from racking systems, floor parameters, routing of engineering networks in congested spaces, and compliance with storage and logistics standards. Key limitations of implementation are discussed, including fragmented regulation, a shortage of BIM skilled personnel, and the dependence of review quality on the reliability of initial survey data. The conclusion outlines directions for improving expert practice: developing regulations for reviewing information models, standardizing data-structure requirements, upskilling experts, and gradually moving to digital expertise as part of life-cycle management for warehouse facilities.