Georgian Scientists/ . 7 N 3, 2025 660 Georgian Scientists Vol. 7 Issue 3, 2025 https://doi.org/10.52340/gs.2025.07.03.35 1, 2, 3 1 , , . : sanadzegivi05@gtu.ge 2 , - , . : eprikyanpavle@gmail.com 3 , . : dima.beridze@gmail.com : , , ) . , , , , . , , . , , . . : , , , , , , , , , . Georgian Scientists/ . 7 N 3, 2025 661 , , , . , . , , , . , , , . , , , , . , , , [1][5]. : , . , , , , , [1]. , , , , , , . , . , , , – . , , [3]. (Predictive Maintenance) , Georgian Scientists/ . 7 N 3, 2025 662 . . , , , , [2]. , , . , . , , , [3]. , . , , – . , [1][3]. , , : , [1][4]. . , , . , , . . , , , . , , [4]. , , , . . , Georgian Scientists/ . 7 N 3, 2025 663 , , [4][5]. . , . , , , . , , [1]. . , , , , . , . , . , , [4][5]. , , , , . , . , . , . : . . , . , , , ( , , ) . , [1][3]. Georgian Scientists/ . 7 N 3, 2025 664 . , , , , . , , , , . , , . , . , [1][3][4][5]. 1. Smith, J. Industrial Equipment Monitoring: Best Practices and Challenges. Journal of Manufacturing Systems. 2023. 45(2), p.123-135. 2. Johnson, M., & Lee, K. Predictive Maintenance in Modern Manufacturing. International Journal of Industrial Engineering. 2022. 38(4), p. 210-225. 3. Brown, T. Real-Time Diagnostics in Production Processes. Manufacturing Technology Review. 2021. 29(1), p. 56-70. 4. Kumar, R., & Patel, S. Challenges in Implementing Monitoring Systems in Small Enterprises. Journal of Production Engineering. 2024. 50(3), p. 89-102. 5. Georgian Industrial Association. Current State of Manufacturing in Georgia: Challenges and Opportunities. Tbilisi: GIA Press. 2023. Georgian Scientists/ . 7 N 3, 2025 665 Best Practices and Challenges in Diagnostic and Monitoring Methods of Technological Equipment in Manufacturing Processes Givi Sanadze1, Pavle Eprikian2, Dima Beridze3 1Professor, Georgian Technical University, Email: sanadzegivi05@gtu.ge 2Master, LEPL - National Agency for Military Recruitment and Recruitment, Email: eprikyanpavle@gmail.com 3Master, Aviation Unit of the Ministry of Defense, Email: dima.beridze@gmail.com Abstract In modern manufacturing, the reliability and efficiency of technological equipment, such as machine tools and industrial robots, are critical for competitiveness. This article explores diagnostic and monitoring methods, focusing on best practices like continuous monitoring, predictive maintenance, and self-control systems, which reduce unplanned downtime and optimize costs. It also addresses challenges, including organizational, economic, and technical difficulties, as well as data reliability issues. Practical solutions, such as personnel training and system integration, are proposed to enhance production reliability. The study aims to promote the adoption of these methods in the Georgian industry. Keywords: Production processes, technological devices, diagnostics, monitoring, predictive maintenance, self-monitoring systems, anomaly detection, production efficiency, data reliability, cost optimization.