DIGITAL TWIN-BASED SMART MANUFACTURING FOR REAL-TIME PROCESS OPTIMIZATION
Ganesh Baliram Dongre, Satish Mohanrao Turkane, Rashmi Dahiya, Abhijeet Deshpande, Yuvraj Nikam, Yatin Gandhi
Abstract: The fast development of Industry 4.0 has increased the pressure on smart manufacturing systems with the ability to monitor in real time, have adaptive control, and optimize the processes. Conventional manufacturing optimization strategies are typically based on the models that are not dynamic and the type of decisions emphasizing the offline approach; other words, they are not responsive to dynamic disturbances of the shop-floor, variability of production and tailor-made needs. In an attempt to solve these issues, digital twin technology has been proposed as a central facilitator of smart manufacturing since it provides a real-time, two-way alignment of the real production system with its virtual counterpart. The study will implement and simulate a digital twin-enabled smart manufacturing system to optimize processes in real-time through the use of real-time data collection and monitoring, intelligent analytics, and the enhancement of decisions. The suggested solution will involve a multi-layer digital twin design with artificial intelligence and optimization, such as heuristic algorithms, machine learning models, and reinforcement learning tooling, to dynamically model, simulate, and optimize manufacturing processes. The methodology includes integration of shop-floor sensors in real time, modeling of the virtual process, predictive analysis of performance and close loop optimization. The key manufacturing measures used to determine performance include production throughput, machine utilization, scheduling efficiency, energy consumption and mean tardiness. The results verify that smart manufacturing incorporating the digital twin allows proactive decision-making, prompt adjustments to the changes in the system, and the continuous optimization of the performance, which makes it a powerful and scalable solution in the next-generation intelligent manufacturing setting.
Keywords: Digital twin; Smart manufacturing; Real-time process optimization; Industry 4.0; Artificial intelligence; Closed-loop control; Intelligent decision-making
DOI: 10.24874/PES08.03.002
Recieved: 04.05.2026 Revised: 17.06.2026 Accepted: 21.07.2026
UDC:
Reads: 10 
