Digital Transformation of Resource Logistics and Organizational and Structural Support of Construction

Abstract

Introduction. Compliance of timing of construction works and supply of resources to the site with the works program is an urgent need, because any failure to supply or mismatch of schedules of works and the movement of materials and technical resources may have serious negative consequences for the construction process.
Problem Statement. It is necessary to minimize deviations of real construction dates from those specified in the design documents by creating tools for managing the organization of the construction process based on operational data, their mathematical processing, identification of trends and remedy of deviations based on current information on the course of construction.
Purpose. To improve tools and means of the resource logistics and organizational and structural support of construction in order to minimize deviations of the real terms of the supply of resources to the site from those specified in the design documents at the stage of design works and preparation of BSOS (building site organization scheme) and SWEP (site work execution program) with seasonal factors taken into consideration.
Materials and Methods. The research uses methods of expert estimations, seasonal decomposition of time series, and comparative analysis.
Results. The analysis of modern software for the construction of construction, the scheme of organization of the process of construction of the object has been established. it is proved that seasonality is a factor that performs moderate influence on the terms of construction and supply of resources, created models of forecasting deviations of the course of the building process taking into account seasonality.
Conclusions. The existing methods for forecasting deviations, which are used in the Microsoft Project, OpenPlan, Spider Project, SureTrek Project Manager, Primavera Project Planner, and other software should be added with models designed to predict realistic timelines with seasonal factors taken into consideration.