Uncapping Ultimate Machine Learning for Advanced Manufacturing Optimization: Steering Supply Chain Projecting Sustainability

Uncapping Ultimate Machine Learning for Advanced Manufacturing Optimization: Steering Supply Chain Projecting Sustainability

Bhupinder Singh (Sharda University, India), Christian Kaunert (Dublin City University, Ireland), Kittisak Jermsittiparsert (Shinawatra University, Thailand), and Saurabh Chandra (Bennett University, Greater Noida, India)
Copyright: © 2025 |Pages: 24
DOI: 10.4018/979-8-3693-5350-9.ch011
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Abstract

The disruptive impact of Machine Learning presents an opportunity to rethink the optimization of industrial processes, especially in the complex supply chain. The need to reduce environmental effect is driving a paradigm change in the industrial sector towards sustainability. The world struggles associated with sustainable development, the manufacturing industry is leading the charge in pursuing efficiency and environmentally responsible methods. The revolutionary potential of the machine learning to revolutionize factory optimization especially in the supply chain is examined. This chapter focuses on the understanding of current challenges in manufacturing optimization for sustainability; explore the fundamentals of Machine Learning and it's application to manufacturing; analyze diverse aspects and examples of Machine Learning in supply chain optimization; discuss the potential impact of Machine Learning on sustainability within the manufacturing sector while reducing its environmental impact and advancing global sustainability.
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