GENERATIVE ARTIFICIAL INTELLIGENCE
IN MANUFACTURING PLANNING 

Vitaly R. Aleksandrov, Director of digital transformation, Research and Production Enterprise "Istok named after A.I. Shokin" (2а Vokzalnaya street, Fryazino, Moscow region, Russia), E-mail: vraleksandrov@istokmw.ru
Aleksey A. Shchetkin, Head of the department, Research and Production Enterprise "Istok named after A.I. Shokin" (2а Vokzalnaya street, Fryazino, Moscow region, Russia), E-mail: aaschetkin@istokmw.ru
Aleksandr S. Bevz, Programmer, Research and Production Enterprise "Istok named after A.I. Shokin" (2а Vokzalnaya street, Fryazino, Moscow region, Russia),E-mail: asbevz@istokmw.ru

Background. In modern manufacturing, optimization of production processes is becoming increasingly important. One of the effective tools to achieve this goal is the use of MES/APS systems (Manufacturing Execution System/ Advanced Planning and Scheduling) in combination with IIoT (Industrial Internet of Things) and artificial intelligence (AI), which qualitatively affects the development and implementation of new methods and means of mechanization, automation, robotics and digitalization of instrument-making production, ensuring increased productivity, reduced labor intensity, increased cost-effectiveness of production, taking into account the solution of issues of ensuring reliability, environmental safety and the possibility of implementation in digital information technologies. In this article, we will consider the prospects and challenges associated with the use of these technologies, and discuss the possibility of using MES/APS as a digital assistant for the dispatcher. Materials and methods. The research is based on the interaction of a set of MES/APS software and hardware, AI and the domestic Industrial Internet of Things Platform IIoT.Istok. Results. The article provides an overview of the digital assistant and a brief analysis. Conclusions. The presented research on the use of MES/APS with AI as a digital assistant can improve production efficiency by automating the production manager's workplace.

manufacturing, machine learning, maintenance and repair, planning, OEE, industrial Internet of Things, neural network, optimization, dashboard, cyber-physical system, SCADA, big data, smart manufacturing, artificial intelligence, planning objects, graphs

Aleksandrov V.R., Shchetkin A.A., Bevz A.S. Generative artificial intelligence in manufacturing planning. Izmerenie. Monitoring. Upravlenie. Kontrol' = Measuring. Monitoring. Management. Control. 2025;(1):34–45. (In Russ.). doi: 10.21685/2307-5538-2025-1-5