Approach to organizing distributed production of unmanned aerial vehicles using digital twin and multi-agent systems technologies

Victor Shalnyev, Mariia Danova

Abstract


The research focuses on methods and software tools for decision support for the organization of distributed production of unmanned aerial vehicles (UAVs) based on digital twin and multi-agent systems technologies. The purpose of the work is to provide a critical review of existing approaches to the organization of distributed production of UAVs, as complex technical objects, and to substantiate an approach to building a multi-agent decision support system for the synthesis of a rational production structure based on digital twins of participants in production cooperation. The tasks include: classifying unmanned aerial vehicles according to the main features that determine their production specifics; analysing modern scientific publications in the field of distributed production informatization, multi-agent systems, digital twins and intelligent decision support; identifying the limitations of existing solutions; and proposing an approach to the organization of distributed production of UAVs using digital twins in the form of intelligent agents. The applied methods are based on system and classification analysis, generalization of modern scientific approaches to the organization of production, decision-making theory, the concept of multi-agent systems, digital twin technologies, production logistics and artificial intelligence. The following results were obtained: UAVs were classified by mass, purpose and level of autonomy, which made it possible to determine the specifics of their production and life cycle management. An analysis of scientific publications was performed, which showed the active development of areas related to the use of multi-agent systems, digital twins and artificial intelligence to address complex tasks in UAV life cycle management. It was established, in particular, that the works of recent years consider the issues of cooperative UAV production, the use of deep learning algorithms for decision-making in dynamic environments and the integration of digital twins into relevant production systems. At the same time, a number of limitations on the implementation of existing solutions were identified: insufficient formalization of business processes between production participants, weak integration of digital twins into production logistics, and the lack of self-organization mechanisms. An approach to solving the problem of effective organization of distributed UAV production is proposed. The architecture of a multi-agent decision support system for distributed UAV production is developed, which includes modules for coordination, self-organization, and the evaluation of the effectiveness of production configuration options, considering the initial risk tolerance indicator. Conclusions. The scientific novelty of the results obtained is as follows: an approach to solving the problem of effective organization of distributed UAV production is proposed, which, unlike existing ones, is based on the representation of production participants as digital twins in the form of intelligent agents, this enables the generation of multiple options and the subsequent selection of the most rational configuration for organizing distributed UAV production in terms of business process efficiency and the reduction of production risks. The research results create a basis for further integration of multi-agent technologies into real-world manufacturing platforms and the expansion of their application to other types of complex machinery.

Keywords


unmanned aerial vehicles (UAVs); distributed manufacturing; multi-agent systems; digital twins; decision support; business processes; risk tolerance; self-organization; production logistics; artificial intelligence

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References


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DOI: https://doi.org/10.32620/aktt.2026.2.09