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AI-Driven Optimization for A Sustainable and Efficient Manufacturing System

  • Jul 1, 2026
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Abstract Book of the 11th International Conference on Management, Economics and Finance

Year: 2026

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AI-Driven Optimization for A Sustainable and Efficient Manufacturing System

Anas Mouchane, Imane Daha Belghiti, Abdelali El Mounadi, Chaimae Saadi

ABSTRACT:

In the evolving Industry 5.0 era, the integration of AI-driven optimization and smart manufacturing is facilitating the development of efficient and sustainable industrial processes. However, empirical frameworks for measuring the efficiency of these transitions using global datasets remain fragmented. As the manufacturing industry firms appear to struggle the most, either not or marginally benefiting from this evolving technological advancement. All this considering that the manufacturing industry is a high impact sector, without which no product will exist, including Artificial intelligence itself, as it works primarily based on microchips and computers that have been manufactured in a factory somewhere around the globe. This study contributes by applying structural modeling to World Bank economic indicators, effectively investigating the potential relationship between different factors impacting AI implementation in the manufacturing environments. Employing Exploratory Factor Analysis (EFA) reveals a three-factor structure that accounts for 69.1% of the total data set variance. Preliminary findings indicate a robust model fit, with chi-square/df ratio of 2.73, an excellent SRMR of 0.024, and a very strong CFI of 0.972. The resulting analysis suggests that AI implementation in the industrial environment is specifically and typically related to the company’s bank financing access. Associated factors were identified as Factor 1- Financial Inclusion and Bank Access, Factor 2- Technological advancement and innovation, and Factor 3- Companies expansion potential. These research findings provide a roadmap for policymakers and consultants to optimize sustainable industrial processes and found a strategic framework facilitating the AI driven optimization for sustainable and efficient manufacturing.

Keywords: Artificial Intelligence, Industry 5.0, World Bank Data, Factor Analysis, Smart Manufacturing