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@article{196431,
        author = {Jaiprakash Singh Yadav and Tripty Yadav},
        title = {Carbon footprint reduction using AI-based process optimization in Modern Manufacturing: A Data-Driven Approach},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {4244-4248},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=196431},
        abstract = {The manufacturing sector is one of the largest contributors to global [1] carbon emissions due to energy-intensive processes and inefficient resource utilization. The integration of Artificial Intelligence into manufacturing systems has opened new pathways for reducing environmental impact while maintaining productivity. This paper presents a comprehensive study on AI-based process optimization for carbon footprint reduction. A multi-layered framework is proposed, supported by a mathematical model and an industrial case study. The results demonstrate that AI-driven optimization can reduce energy consumption and emissions by up to 20–30%. Challenges, limitations, and future research opportunities are also discussed.},
        keywords = {AI, Carbon Emissions, Smart Manufacturing, Sustainability, Process Optimization},
        month = {April},
        }