| Title | Digital Twin Technology in Manufacturing: Enhancing Efficiency, Predictive Maintenance, and Industry 4.0 Adoption |
| Research Area | IoT |
| Abstract | The manufacturing industry is undergoing a major transformation under the paradigm of Industry 4.0, driven by technologies such as the Internet of Things (IoT), artificial intelligence, big data analytics, and cyber-physical systems. Digital Twin technology has emerged as a key enabler of this transformation by creating virtual replicas of physical assets, processes, and systems. These digital representations allow real-time monitoring, simulation, optimization, and predictive maintenance of manufacturing operations. This paper presents a comprehensive study of Digital Twin technology in manufacturing, focusing on its architecture, applications, benefits, and challenges. Case-based analysis and experimental findings indicate that Digital Twin-enabled manufacturing systems can reduce downtime by 30–40%, improve production efficiency, and support data-driven decision-making. The paper also discusses implementation challenges and future research directions for large-scale industrial adoption. |
| Keywords | Digital Twin, Industry 4.0, Smart Manufacturing, Predictive Maintenance, IoT, Cyber-Physical Systems |
| Paper Status | Published |
| Volume | 2 |
| Issue | 2 |
| Published On | 13/01/2026 |
| Published File |
IJSRTD_4871.pdf
|