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AI-Driven Optimization in Sustainable Manufacturing for Eco-Efficient Manufacturing of Advanced Materials
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Author(s): R. Jegadeesan (Department of Computer Science and Engineering, Jyothishmathi Institute of Technology & Science, Thimmapur, India), Sonia Maria D'Souza (Department of Artificial Intelligence and Machine Learning, New Horizon College of Engineering, Bengaluru, India), B. Dhanasakkaravarthi (Department of Mechanical Engineering, Agni College of Technology, Chennai, India), S. Ranganathan (AMET University, India), V. Kavitha (Department of Data Science and Business Systems, School of Computing, SRM Institute of Science and Technology, Kattankulathur, India)and A. Rajendra Prasad (Department of Mechanical Engineering, Sri Sai Ram Engineering College, Chennai, India)
Copyright: 2025
Pages: 28
Source title:
Using Computational Intelligence for Sustainable Manufacturing of Advanced Materials
Source Author(s)/Editor(s): Kamalakanta Muduli (Papua New Guinea University of Technology, Papua New Guinea), Bikash Ranjan Moharana (Papua New Guinea University of Technology, Papua New Guinea), Steve Korakan Ales (Papua New Guinea University of Technology, Papua New Guinea)and Dillip Kumar Biswal (Aryan Institute of Engineering and Technology, Bhubaneswar, India)
DOI: 10.4018/979-8-3693-7974-5.ch008
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Abstract
The chapter studies the use of AI-driven optimization to apply methods of sustainable manufacturing based on the scenario of eco-efficient production of advanced materials. It also shows how AI methods could be used, including machine learning and optimization algorithms, to increase the efficiency of manufacturing processing flows while decreasing environmental impact. The chapter covers a scope of AI-based predictive maintenance, process optimization, and resource management strategies that result in a reduction in waste generation, energy use, and gases emitted. These are demonstrated in practice through case studies and examples in the manufacturing of advanced materials, ensuring the transformation of conventional manufacturing practices into more sustainable operations. In fact, the implementation of AI into the practice of manufacturing that recognizes and promotes sustainable manufacturing would massively contribute to the enhancement of full sustainability benefits by encouraging environmental stewardship while fostering innovation in material science.
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