Most read articles by the same author(s)
Khudoyor Sayilkhonov , B. Ergashev , INNOVATIVE PRACTICES IN PRIMARY AND SECONDARY EDUCATION , Journal of Applied Science and Social Science: Vol. 1 No. 3 (2025): Journal of Applied Science and Social Science
21-06-2025
220-225
42
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DIGITALIZATION OF THE PLANT'S TECHNOLOGICAL MAP: THE INTERACTION BETWEEN DIGITAL TWIN AND AUTOMATION
In today’s fast-evolving industrial landscape, the digital transformation of manufacturing processes is becoming a critical driver of efficiency, flexibility, and innovation. One of the most promising developments in this area is the integration of digital twin technology with automation systems, which enables the creation of intelligent, real-time virtual replicas of physical assets and processes. These digital models not only mirror the actual state of the plant but also interact dynamically with automated systems to support continuous monitoring, predictive maintenance, and optimized control. Recent advancements have shown that this fusion can turn conventional technological maps—once static and manually updated—into living digital frameworks that enhance visibility and responsiveness across the entire production lifecycle. Real-time data from sensors, machines, and control systems feed into the digital twin, which in turn enables simulations, scenario planning, and automated decision-making. This evolution is particularly significant in complex industrial environments where operational continuity, risk mitigation, and sustainability are top priorities. Despite the substantial benefits, practical implementation faces several challenges, including data interoperability across diverse platforms, cybersecurity concerns, and the need for a digitally skilled workforce. However, the growing adoption of open standards, AI-driven analytics, and secure cloud infrastructures is gradually addressing these barriers. As industries increasingly seek resilient and adaptive solutions, the synergy between digital twin technology and automation is emerging as a cornerstone of smart, data-centric manufacturing strategies. This shift signals not just a technological upgrade, but a fundamental transformation in how industrial intelligence is designed and applied.
