ArticleScientific reports2025
Leveraging artificial intelligence for smart production management in industry 4.0.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Industry 4.0 means a paradigm shift in the manufacturing industry, which is accompanied by the combination of cyber-physical systems, the Internet of Things (IoT), and artificial intelligence (AI). Although AI holds high potential in improving an operation and real-time decision-making, several production environments are still trapped with legacy infrastructure or data silo and low adaptability. The paper is the mixed method research on strategic implementation of AI in smart production management that considers 100 surveys among manufacturing experts, 15 interviews of industry leaders. Predictive maintenance, real-time scheduling, quality control with the use of computer vision, and supply chain optimization have been discussed as some of the most important AI applications. The results indicate a high level of productivity, accuracy and decreasing downtimes, but the adoption is still limited by technical obstacles, employee resistance, and ethical issues. The paper suggests a strategic plan that involves data governance, the upskilling of the workforce, as well as policy support that is scalable to solve these issues. The study provides a theoretical approach as well as some hands-on tips to use AI in Industry 4.0 contexts encouraging a comprehensive, participatory, and sustainable approach to the process of taking a turn toward intelligent manufacturing.
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Registered trials
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