Digital Twins in Industrial Production and Smart Manufacturing - (Hardcover)

About the Book

"While production and industrial processes become increasingly digital and the Internet of Things (IoT) becomes more prevalent, the digital twin is now within reach. Digital twins are designed to resemble diverse frameworks that interact with their surroundings in a variety of ways and for which it is difficult to forecast consequences over the product's whole lifecycle. Twin Engineering assists development teams in adjusting manufacturing operations to accomplish desired improvements in addition to assisting them in understanding the effects of any prospective modifications in production processes on operational outputs. As a result, producers can enhance processes and lower the total cost of engineering. Manufacturers can save time and money by constructing, deploying, and assessing factory production systems using digital twins that reflect the products and production systems."--

From the Back Cover

Comprehensive reference exploring the benefits and implementation of digital twins in industrial production and manufacturing

Digital Twins in Industrial Production and Smart Manufacturing provides an overview of digital twin theoretical concepts, techniques, and recent trends used to meet the requirements and challenges of industrial production and smart manufacturing. The text describes how to achieve industrial excellence through virtual factory simulation and digital modeling innovations for next-generation manufacturing system design. The contributing authors address the many possible technical advantages of major Industry 5.0 technological advancements, using illustrations to aid readers in practical implementation of concepts, along with existing scenarios, potential research gaps, adoption difficulties, case studies, and future research objectives.

The text also presents many applications and use cases of Industry 5.0 and digital twins in a variety of industries, including the aerospace industry, pharmaceutical manufacturing and biotech, augmented reality, virtual reality, edge computing and blockchain-based Internet of Things (IoT), cobots, intelligent logistics and supply chain management, and more.

Edited by a group of highly qualified academics with significant experience in the field, Digital Twins in Industrial Production and Smart Manufacturing covers additional topics such as:

• Hyper-automation technology, including specialized workflow procedures and particular sectors of solicitations linked to hyper-automation
• Digital twins in the context of smart cities, with attempts to draw comparisons with the use of digital twins in industrial IoT
• Virtual factories based on digital twins and corresponding architecture to facilitate modeling, simulation, and assessment of manufacturing systems
• Cognitive, interactive, and standardization aspects of digital twins, and the proper implementation of digital twin technology for safety critical systems

Digital Twins in Industrial Production and Smart Manufacturing is a must-have reference for researchers, scholars, and professionals in fields related to digital twins in industrial production and manufacturing. It is also suitable as a hands-on resource for students interested in the fields of digital twins and smart manufacturing.

About the Author

Rajesh Kumar Dhanaraj, PhD, is a Full Professor at Symbiosis International (Deemed University), Pune, India.

Balamurugan Balusamy, PhD, is an Associate Dean Student in Shiv Nadar University, Delhi-NCR.

Prithi Samuel, PhD, is an Assistant Professor in the Department of Computational Intelligence at SRM Institute of Science and Technology, Kattankulathur Campus, Chennai.

Ali Kashif Bashir, PhD, is a Chair Professor of Networks and Security at the Manchester Metropolitan University, UK.

Seifedine Kadry, PhD, is a Full Professor of Data Science with the Department of Computer Science and Mathematics, Lebanese American University, Beirut, Lebanon; Department of Applied Data Science, Noroff University College, Kristiansand, Norway.