Optimization of technical customer functions when commissioning facilities using business process modelling tools

Introduction. The relevance of the study is due to the need to improve the efficiency of the technical customer at the stage of commissioning a construction project. The previous research demonstrated the possibility of using a parametric neural network model to assess efficiency, but the problem of detailed regulation of management processes and a clear definition of the functions of the technical customer at various stages of the life cycle (LC) remains unresolved. Modern construction projects require the coordination of multiple participants under strict time and budget constraints, placing high demands on the quality of management decisions made by the technical customer during the preparation and commissioning of the project. Business analysis and process modelling methodologies help overcome this problem by systematizing and optimizing management processes, identifying bottlenecks and duplication of functions, and ensuring the timely commissioning of the project. While there are developments aimed at structuring individual stages of construction production, less attention is paid to the comprehensive description and optimization of the entire cycle of technical customer management decisions using modern digital transformation tools.

Materials and methods. System analysis, comparative analysis, synthesis, parametric modelling, and the analogy method were used.

Results. A detailed BPMN model of the management decision-making process was developed, identifying participant roles, decision points, and feedback loops for cyclical performance adjustments. Mechanisms for integrating the process model with a parametric neural network model and the ability to connect BIM data for automation were proposed.

Conclusions. The use of BPMN 2.0 reengineering methods systematizes the technical client’s activities, ensures process transparency, clear assignment of responsibilities, and the ability to regularly optimize through the implementation of corrective organizational proposals. Using management models as a basis for developing information systems helps bridge the gaps between process design and practical implementation. The integration of BPMN models with artificial neural networks and BIM systems opens up the prospect of fully automating control and regulatory processes in construction.

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