Akademik Veri Yönetim Sistemi
8th International Black Sea Scientific Research and Innovation Congress, Prof. Dr. Songül TÜMKAYA,Doç.Dr. Yunus Emre ŞİMŞEK, Editör, İksad Yayınevi, Trabzon, ss.559-565, 2026
The rapid transition toward smart and sustainable manufacturing has increased the need for energy-aware decision-making in production systems. This study proposes a novel framework that integrates Digital Twin technology with artificial intelligence and multi-objective optimization to enhance production scheduling under dynamic conditions. A real-time Digital Twin model of a manufacturing system is developed using IoT-enabled data streams, enabling continuous synchronization between the physical and virtual environments. Within this framework, machine learning models—specifically LSTM-based architectures—are employed to forecast both production demand and energy consumption patterns. Building upon these predictions, a multi-objective optimization model is formulated to simultaneously minimize operational cost, total energy consumption, and carbon emissions. The proposed model is solved using an evolutionary optimization approach, generating Pareto-optimal solutions that provide decision-makers with flexible trade-off options. Unlike conventional static scheduling approaches, the integration of a Digital Twin allows adaptive and responsive decision-making under uncertainty and fluctuating demand scenarios. Comprehensive simulation experiments are conducted under various demand and energy price conditions to evaluate the effectiveness of the proposed approach. The results demonstrate significant improvements in energy efficiency and cost reduction compared to traditional methods, while also achieving lower emission levels. This study contributes to the emerging field of smart manufacturing by presenting a scalable and energy-centric optimization framework that bridges the gap between real-time system monitoring and intelligent decision-making, offering a practical pathway toward Industry 5.0-oriented sustainable production systems.