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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM28351

Enabling Circular Economy through Integrated Digital Twins: A Framework for AI-Driven Business Transformation

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM28351

Volume:

8 |

1 |

Jan 2024

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM28351

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

GGA

Gladrin Gideon Aroul

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Abstract

Enabling Circular Economy through Integrated Digital Twins (CAT-I): This study aims to solve this problem through the innovative framework of Circular-AI Twin Integration (CAT-I). This research’s problem emerges from addressing the inefficiencies of linear economic models and is a very complex solution incorporating Digital Twins integration with AI to control material flows. The goal is to operationalize, develop, and validate the CAT-I frameworks by offering a structured pathway for organizations moving along with circular business approaches. The approach utilizes a design science research methodology that includes literature reviews, expert consultations, and iterative prototyping. The following results indicate the effectiveness of CAT-I to promote resource efficiency, reduce waste, and encourage sustainable practices. Advantages can include the possibility that firms could adopt the principles of the circular economy, providing benefits to sustainability and the economy. A transformational solution such as the CAT-I framework leads businesses to a sustainable and circular future.

KEYWORDS

Circular Economy Digital Twin Technology Artificial Intelligence Sustainability Resource Efficiency

Cite This Article

Gladrin Gideon Aroul, "Enabling Circular Economy through Integrated Digital Twins: A Framework for AI-Driven Business Transformation," International Journal of Scientific Research in Engineering and Management, vol. 8, no. 1, Jan 2024. https://doi.org/10.55041/IJSREM28351

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12/31/45316

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