Integrating artificial intelligence and sustainable materials for smart eco innovation in production

The growing connection between AI and eco-friendly materials has made it possible to completely change the way things are made today so that they are smart, resourceful, and safe. The research investigates the potential of AI optimization in advancing the utilization of sustainable materials to enhance energy efficiency and diminish waste production, operational costs, and carbon footprint, in response to the imperative to alleviate climate change effects, lower production expenses, and preserve natural resources. This paper proposes a new concept that intertwines AI predictive analytics and sustainability material selection based on the extensive use of case studies and synthetic datasets to test the use scenario. The results show a significant increase in efficiency based on performance indicators and the future possibilities of waste and zero manufacturing and the circular economy. The findings provide actionable insights for policymakers, industry leaders, and researchers seeking to integrate advanced digital intelligence with eco-innovative production strategies, thereby paving the way for scalable, adaptable, and future-ready manufacturing ecosystems.

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Publication Details

Journal
Scientific Reports
Published
2025-10-22
DOI
https://doi.org/10.1038/s41598-025-20803-2
Citations
6
Primary Topic
Sustainable Supply Chain Management
Type
article
Field-Weighted Citation Impact
13.36

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article

Integrating artificial intelligence and sustainable materials for smart eco innovation in production

Himanshu Dhumras, Varun Shukla, Xingsi Xue, Garima Thakur
6 citations
Scientific Reports
Sustainable Supply Chain Management
13.36
article

Integrating artificial intelligence and sustainable materials for smart eco innovation in production

Himanshu Dhumras, Varun Shukla, Xingsi Xue, Garima Thakur
article en
6 citations

Abstract

The growing connection between AI and eco-friendly materials has made it possible to completely change the way things are made today so that they are smart, resourceful, and safe. The research investigates the potential of AI optimization in advancing the utilization of sustainable materials to enhance energy efficiency and diminish waste production, operational costs, and carbon footprint, in response to the imperative to alleviate climate change effects, lower production expenses, and preserve natural resources. This paper proposes a new concept that intertwines AI predictive analytics and sustainability material selection based on the extensive use of case studies and synthetic datasets to test the use scenario. The results show a significant increase in efficiency based on performance indicators and the future possibilities of waste and zero manufacturing and the circular economy. The findings provide actionable insights for policymakers, industry leaders, and researchers seeking to integrate advanced digital intelligence with eco-innovative production strategies, thereby paving the way for scalable, adaptable, and future-ready manufacturing ecosystems.

Scientific ReportsVol. 15(1)
Chandigarh University (IN), Yango University (CN), Fujian University of Technology (CN), Punjab Engineering College (IN), Indian Institute of Technology Kanpur (IN)
National Natural Science Foundation of China
Openalex Percentile: Top 2%
Sustainable Supply Chain Management
13.36
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