Digital Twins and AI: Transforming Smart Manufacturing Strategies

Digital Twin technology and Artificial Intelligence (AI) have been integrated as the new paradigm of the next generation of smart manufacturing systems. The Digital Twins enable creation of high-fidelichen virtual models of the physical resources, processes and manufacturing environments where it can be possible to monitor, simulate and optimize the manufacturing life cycle. With AI-based analytics, machine learning, and predictive intelligence, Digital Twins can be formulated into real-time adaptive and autonomous decision support systems. The integration can be very powerful to enhance the operational effectiveness, the accuracy of predictive maintenance, quality assurance and optimization of resources and facilitate data-oriented strategic planning. Increased scalability of AI-enables Digital Twins of manufacturing ecosystem is further enhanced by the growth of Industrial Internet of Things (IIoT), cloud-edge computing systems, and cyber-physical systems. However, there are interoperability of data, model synchronization, cybersecurity, computational complexity, and organizational preparedness problems which continue to hamper widespread use. Conceptual, enabling technologies, architectural and strategic implications of Digital Twin integration with AI in smart manufacturing will be an indepth part of the paper. Besides that, it examines the current industrial uses, major research shortfalls and future orientations needed to have resilient, autonomous and sustainable manufacturing businesses aligning with the Industry 4.0 and Industry 5.0 visions.