AI-driven optimization techniques for smart sustainable manufacturing in Industry 5.0 ecosystem: A comprehensive review

The integration of Artificial Intelligence (AI) driven optimization techniques is transforming smart manufacturing in the industry 5.0 landscape leading to sustainable industrial processes. This review comprehensively explores AI-driven optimization methods that enhance efficiency, resilience, and sustainability in modern manufacturing ecosystems. It highlights the role of various AI - based algorithms in optimizing production processes, energy consumption, and supply chains. Along with this, it also presents the significance of AI-driven manufacturing in improving secure production by facilitating real-time monitoring, anomaly detection, and predictive maintenance. In this work, the authors also examine how AI contributes to human-centric manufacturing, addressing challenges such as resource utilization, waste reduction, and adaptive decision-making. Key advancements, limitations, and future research directions are analyzed to provide a holistic view of AI’s transformative potential. The findings underscore the necessity of AI-driven optimization for achieving sustainable, efficient, and flexible manufacturing processes in Industry 5.0. This work serves as a significant reference for researchers, industry professionals, and policymakers seeking to leverage AI for sustainable industrial advancements. This paper presents the comprehensive synthesis of AI-driven optimization techniques represented for the emerging Industry 5.0 model, prioritizing smart sustainable manufacturing. Unlike prior reviews, it systematically compares traditional and AI-based approaches, highlights the transformative synergy of advanced technologies like AI, IoT, digital twins, and blockchain for real-time, human-centric manufacturing, and details hybrid optimization methods integrating AI algorithms. This review uniquely maps the integration of these innovations with sustainability, adaptability, and mass personalization, presenting a roadmap to help industries employ intelligent, data-driven, and eco-friendly optimization solutions for future-ready manufacturing.

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Publication Details

Journal
Alexandria Engineering Journal
Published
2026-01-20
DOI
https://doi.org/10.1016/j.aej.2026.01.016
Citations
1
Primary Topic
Digital Transformation in Industry
Type
article
Field-Weighted Citation Impact
35.67
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article

AI-driven optimization techniques for smart sustainable manufacturing in Industry 5.0 ecosystem: A comprehensive review

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1 citations
Alexandria Engineering Journal
Digital Transformation in Industry
35.67
article

AI-driven optimization techniques for smart sustainable manufacturing in Industry 5.0 ecosystem: A comprehensive review

Sita Rani, Ramesh Karnati, Vivek G. Patel, Amrindra Pal, Aman Kataria, M.K. Ranganathaswamy, Prakhar Tomar
article en
1 citations

Abstract

The integration of Artificial Intelligence (AI) driven optimization techniques is transforming smart manufacturing in the industry 5.0 landscape leading to sustainable industrial processes. This review comprehensively explores AI-driven optimization methods that enhance efficiency, resilience, and sustainability in modern manufacturing ecosystems. It highlights the role of various AI - based algorithms in optimizing production processes, energy consumption, and supply chains. Along with this, it also presents the significance of AI-driven manufacturing in improving secure production by facilitating real-time monitoring, anomaly detection, and predictive maintenance. In this work, the authors also examine how AI contributes to human-centric manufacturing, addressing challenges such as resource utilization, waste reduction, and adaptive decision-making. Key advancements, limitations, and future research directions are analyzed to provide a holistic view of AI’s transformative potential. The findings underscore the necessity of AI-driven optimization for achieving sustainable, efficient, and flexible manufacturing processes in Industry 5.0. This work serves as a significant reference for researchers, industry professionals, and policymakers seeking to leverage AI for sustainable industrial advancements. This paper presents the comprehensive synthesis of AI-driven optimization techniques represented for the emerging Industry 5.0 model, prioritizing smart sustainable manufacturing. Unlike prior reviews, it systematically compares traditional and AI-based approaches, highlights the transformative synergy of advanced technologies like AI, IoT, digital twins, and blockchain for real-time, human-centric manufacturing, and details hybrid optimization methods integrating AI algorithms. This review uniquely maps the integration of these innovations with sustainability, adaptability, and mass personalization, presenting a roadmap to help industries employ intelligent, data-driven, and eco-friendly optimization solutions for future-ready manufacturing.

Alexandria Engineering JournalVol. 137
Chandigarh University (IN), Jain University (IN), Guru Nanak Dev University (IN), Marwadi University (IN), Chitkara University (IN)
Industry, innovation and infrastructure
Openalex Percentile: Top 1%
Digital Transformation in Industry
35.67
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