Omar Musazade, Stanislav Aghamatov
This research aims to advance industrial glass manufacturing by implementing a next-generation autonomous control architecture. The study focuses on maximizing energy efficiency and product quality by integrating Digital Twin technology, Deep Reinforcement Learning (DRL), and Explainable AI (XAI) to overcome the limitations of legacy control systems. This is an analytical and simulation-based research study centered on the cognitive optimization of industrial float glass production processes. Conducted in the Department of Instrumentation Engineering at Azerbaijan State Oil and Industry University, the study began in September 2025 and extended into June 2027. A high-fidelity Digital Twin of a float glass furnace was developed to simulate production dynamics, while a DRL-based agent was implemented for real-time furnace regulation, allowing for continuous self-optimization of thermal zones, ultimately leading to enhanced product quality and operational efficiencies.
@article{fa7d7721-c6bd-4c2e-97f4-ec9fb694c88f,
title={Application of AI-based Intelligent Control Methods for Enhancing Product Quality in Glass Manufacturing},
author={Omar Musazade and Stanislav Aghamatov},
year={2026},
language={en}
}TY - JOUR TI - Application of AI-based Intelligent Control Methods for Enhancing Product Quality in Glass Manufacturing AU - Omar Musazade AU - Stanislav Aghamatov PY - 2026 LA - en ER -
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