Leveraging Artificial Intelligence for Sustainable Electronics Manufacturing Supply Chains

Gautam Nandkishore Nayak

doi:10.32628/CSEIT25111230

Authors

Gautam Nandkishore Nayak State University of New York at Binghamton, USA Author

DOI:

https://doi.org/10.32628/CSEIT25111230

Keywords:

Artificial Intelligence in Manufacturing, Environmental Impact Reduction, Industry 4.0 Implementation, Smart Manufacturing Infrastructure, Sustainable Electronics Supply Chain

Abstract

This technical article examines the transformative role of Artificial Intelligence in developing sustainable supply chains within the electronics manufacturing sector. The article explores how AI technologies are revolutionizing sustainability practices across the industry, from resource optimization to waste management. By analyzing current challenges, AI-enabled solutions, and implementation frameworks, this research demonstrates how advanced technologies are enabling manufacturers to achieve significant improvements in environmental performance while maintaining operational efficiency. The article encompasses various aspects of sustainability, including supply chain transparency, resource utilization, carbon footprint reduction, and organizational transformation, providing a comprehensive overview of how AI is reshaping the future of sustainable electronics manufacturing.

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References

Dr. Kees Balde, "Findings From the Global E-waste Monitor," UNITAR-SCYCLE Programme, 2024. [Online]. Available: https://unece.org/sites/default/files/2024-06/S6_1_E-waste%20monitor%202024.pdf

Marcel Matthess, et al., "The impact of digitalization on energy intensity in manufacturing sectors – A panel data analysis for Europe," Journal of Cleaner Production, Volume 397, 15 April 2023, 136598. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S0959652623007564 DOI: https://doi.org/10.1016/j.jclepro.2023.136598

Circular Electronics Partnership, "Circular Electronics Roadmap 2.0," CEP, 2024. [Online]. Available: https://cep2030.org/wp-content/uploads/2024/04/CEP-Roadmap-2.0.pdf

A.R. Balkenende, C.A. Bakker, "Developments and Challenges in Design for Sustainability of Electronics," International Journal of Sustainable Manufacturing, vol. 15, no. 2, pp. 167-189, 2024. [Online]. Available: https://ebooks.iospress.nl/volumearticle/39947

Jumba K Kato, "Integrating AI and IoT for Smart Manufacturing," Research Invention Journal Of Biological And Applied Sciences 3(3):30-33, 2024. [Online]. Available: https://www.researchgate.net/publication/384188982_Integrating_AI_and_IoT_for_Smart_Manufacturing

Mohsen Soori, "Blockchains for industrial Internet of Things in sustainable supply chain management of industry 4.0, a review," Sustainable Manufacturing and Service Economics,Volume 3, 2024, 100026. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S2667344424000094 DOI: https://doi.org/10.1016/j.smse.2024.100026

Dimple Patil, "Artificial intelligence-driven predictive maintenance in manufacturing: Enhancing operational efficiency, minimizing downtime, and optimizing resource utilization," International Journal of Smart Manufacturing, vol. 12, no. 4, pp. 412-436, 2024. [Online]. Available: https://www.researchgate.net/publication/385885091_Artificial_intelligence-driven_predictive_maintenance_in_manufacturing_Enhancing_operational_efficiency_minimizing_downtime_and_optimizing_resource_utilization DOI: https://doi.org/10.2139/ssrn.5057406

Mahboubeh Motadayen, et al., "Advancing Sustainability: Biodegradable Electronics and New Materials through AI and Machine Learning," ChemRxiv, preprint, 2024. [Online]. Available: https://chemrxiv.org/engage/api-gateway/chemrxiv/assets/orp/resource/item/6600d3d766c1381729bde24a/original/advancing-sustainability-biodegradable-electronics-and-new-materials-through-ai-and-machine-learning.pdf DOI: https://doi.org/10.26434/chemrxiv-2024-8vlmz

Lakshmi Shankar Iyer, "AI enabled applications towards intelligent transportation," Transportation Engineering, Volume 5, September 2021, 100083. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S2666691X21000397 DOI: https://doi.org/10.1016/j.treng.2021.100083

Tanveer Ahmad, et al., "Artificial intelligence in sustainable energy industry: Status Quo, challenges and opportunities," Journal of Cleaner Production,Volume 289, 20 March 2021, 125834. [Online]. Available: https://www.sciencedirect.com/science/article/abs/pii/S0959652621000548 DOI: https://doi.org/10.1016/j.jclepro.2021.125834

F. Jovane, et al., "The incoming global technological and industrial revolution towards competitive sustainable manufacturing," CIRP Annals,Volume 57, Issue 2, 2008, Pages 641-659,. [Online]. Available: https://www.sciencedirect.com/science/article/abs/pii/S0007850608001959 DOI: https://doi.org/10.1016/j.cirp.2008.09.010

Dharmendra Hariyani, et al., "Organizational barriers to the sustainable manufacturing system: A literature review," Environmental Challenges,Volume 9, December 2022, 100606. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S2667010022001627 DOI: https://doi.org/10.1016/j.envc.2022.100606

Meng-Leong How, et al., "Forging the Future: Strategic Approaches to Quantum AI Integration for Industry Transformation," Sustainability and Digital Transformation, vol. 5, no. 1, pp. 15-32, 2024. [Online]. Available: https://www.mdpi.com/2673-2688/5/1/15

Marco Garetti, "Sustainable manufacturing: trends and research challenges," Production Planning & Control, vol. 35, no. 4, pp. 412-436, 2024. [Online]. Available: https://www.tandfonline.com/doi/abs/10.1080/09537287.2011.591619