Digital Twins and Distributed Computing to Transform Manufacturing via Sustainable Innovation

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Authors: Subham Kumar, Purvesh Kolpe, Debanjali Barman Roy, Yashodhan Sonwane
Cited by: 0

Abstract

Electron Device Networks (EDNs) enable “Digital Twins” (DTs) by making the easy flow and transfer of data seamless among the manufacturing ecosystem’s different devices. EDNs help to lower emissions, diminish waste of resources, and present operational improvements to accomplish numerous UN Sustainable Development Goals(SDGs). Specifically, digital technologies are assisting in achieving the SDGs: Goal 13: Climate action; Goal 12: Responsible consumption and production; Goal 9: Industry, Innovation and Infrastructure. DTs provide a pathway towards sustainable manufacturing, a circular economy by optimizing processes, reducing material waste, and reducing energy usage. However, widespread acceptance of DTs is still hindered both technically and financially by issues such as energy usage, electronic waste, and expensive integration. In tackling these issues, emerging solutions are renewable energy-based data centers, artificial intelligence (AI)-enhanced energy efficiency, and programs for managing e-waste. While not yet part of classical manufacturing, upcoming trends convey progress to further enhance AI-boosted DTs and the utilization of fifth-(5G) and sixth-generation (6G) networks for more flexible and sustainable manufacturing methods. In this chapter, we look at how DT technology, distributed computing, and EDNs are changing the manufacturing industry into a sustainable, efficient, and innovative one. However, as manufacturers exploit these technologies, they can accommodate international sustainability targets, reduce environmental impacts, and facilitate an environmentally conscious, high-producibility future.

Fields of Study & Subjects

Digital Transformation in Industry Impact of AI and Big Data on Business and Society Applied Advanced Technologies

Publication details

Journal / source
CRC Press eBooks
Pages
126–135
Publication date
6 February 2026
Language
EN
Document type
Book chapter