MULTI-AGENT SYSTEM FOR AUTOMATIC PLANNING AND MANAGEMENT OF ENGINEERING CHANGES AT A RADIOELECTRONICS ENTERPRISE
- Authors: Irzaev G.K.1, Adamova A.A.2, Yurkov N.K.3
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Affiliations:
- Daghestan State Technical University
- Bauman Moscow State Technical University
- Penza State University
- Issue: No 3 (2025)
- Pages: 45-53
- Section: DESIGN AND TECHNOLOGY OF INSTRUMENTATION AND ELECTRONIC EQUIPMENT
- URL: https://journal-vniispk.ru/2307-4205/article/view/353684
- DOI: https://doi.org/10.21685/2307-4205-2025-3-5
- ID: 353684
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Abstract
Background. Modern radio-electronic enterprises have to maintain consumer interest by continuously improving their products, developing new modifications and introducing engineering changes into the design and manufacturing technology. Engineering changes require significant efforts for their planning, coordination and implementation at the enterprise and are carried out in most cases manually. This study aims to develop a multi-agent decision support system for managing engineering changes in products using the wide capabilities of artificial intelligence technologies. Materials and methods. Based on the engineering change maintenance model previously developed by the authors, an original role model of agent interactions has been formed. Agents operating in an uncertain environment and lack of complete information use cognitive data structures and deduction and induction methods to draw conclusions. Results and conclusions. The concept of a system consisting of four agents and containing cognitive data structures and methods of logical inference with training and adaptation is proposed. Local goals of agents in the system are formulated, their role and general logic of actions to support decision-making on the implementation of engineering changes in electronic products are revealed. The logical architecture of the coordinator agent is developed, which requests the optimal time and cost of implementing engineering changes and makes a schedule for their implementation at the enterprise. Architectures of the forecaster agent, optimizer agent and feedback agent are also built. The model has limitations in the form of emergency situations at the enterprise, legally significant or critical changes for the safety of the enterprise, which requires switching to manual control.
About the authors
Gamid Kh. Irzaev
Daghestan State Technical University
Author for correspondence.
Email: irzajev@mail.ru
Candidate of technical sciences, associate professor, associate professor of the sub-department of software, computer science and automated systems
(70 I. Shamil avenue, Makhachkala,Republic of Daghestan, Russia)Arina A. Adamova
Bauman Moscow State Technical University
Email: arinaadamova75@gmail.com
Candidate of technical sciences, associate professor, associate professor of the sub-department of design and production technology of electronic equipment
(build. 1, 5 2-ya Baumanskaya street, Moscow, Russia)Nikolay K. Yurkov
Penza State University
Email: yurkov_nk@mail.ru
Doctor of technical sciences, professor, honoured worker of science of the Russian Federation, head of the sub-department of radio equipment design and production
(40 Krasnaya street, Penza, Russia)References
- Irzayev G.Kh. Analysis of the processes of making engineering changes to the design of electronic means at the stages of design and development of mass production. Voprosy radioelektroniki = Radio electronics issues. 2016;(11):72–78. (In Russ.)
- Wooldridge M., Jennings N.R., Kinny D. The Gaia Methodology for Agent-Oriented Analysis and Design. Autonomous Agents and Multi-Agent Systems. 2000;3(3):285–312.
- Wildemann H. Änderungs management, Leitfaden zur Einführung eineseffizienten Managements technischer Änderungen. München: Tcwtransfer-Centrum, 2006.
- Ehrlenspiel K. Integrierte Produkt entwicklung. Denkabläufe, Methodeneinsatz, Zusammenarbeit. München; Wien, 2007.
- Irzayev G.Kh. Management of engineering changes in electronic instrumentation products using virtual and augmented reality technologies. Fundamental′nyye i prikladnyye problemy tekhniki i tekhnologii = Fundamental and applied problems of engineering and technology. 2024;(1):130–140. (In Russ.)
- Russell S.J., Norvig P. Artificial intelligence: A modern approach, Always learning, Third edition, Global edition, Pearson. Boston; Columbus; Indianapolis, 2016.
- Likhtenshteyn V.E., Konyavskiy V.A., Ross G.V., Los′ V.P. Mul′tiagentnyye sistemy: samoorganizatsiya i razvitiye = Multi-agent systems: self-organization and development. Moscow: Finansy i statistika, 2018:264. (In Russ.)
- Romancheva N.I. Features of the use of multi-agent technologies in cybersocial systems. Trudy Mezhdunarodnogo simpoziuma Nadezhnost′ i kachestvo = Proceedings of the International Symposium Reliability and Quality. 2017;1:79–82. (In Russ.)
- Yurkov N.K., Betskov A.V., Samokutyayev A.M. Multi-agent management of complex dynamic systems. Trudy Mezhdunarodnogo simpoziuma Nadezhnost′ i kachestvo = Proceedings of the International Symposium Reliability and Quality. 2023;1:6–12. (In Russ.)
- Potdar P., Jonnalagedda V. Design and development of a framework for effective engineering change management in manufacturing industries. International Journal of Product Lifecycle Management. 2018;11(4):368.
- Masloboyev A.V. Generalized methodology for building multi-agent systems for managing the viability of critical infrastructures. Nadezhnost′ i kachestvo slozhnykh system = Reliability and quality of complex systems. 2024;(2):134–146. (In Russ.)
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