Mapping Industry ۴.۰ Intelligence: A Bibliometric Study of AI in Production and Process Optimization

This study explores the global research landscape of artificial intelligence (AI) applications in Industry ۴.۰, focusing on production and process optimization. Utilizing a bibliometric approach, we analyzed ۱,۱۱۴ articles from Scopus and ۷۵۸ from Web of Science, published between ۲۰۲۰ and ۲۰۲۶, to map research trends, key contributors, and thematic clusters. The methodology involved keyword co-occurrence, co-authorship, and bibliographic coupling analyses using VOSviewer. Results reveal three main thematic clusters: AI-driven process optimization (e.g., 'machine learning,' 'predictive maintenance'), IoT and resource management (e.g., 'internet of things,' 'resource allocation'), and advanced neural networks (e.g., 'convolutional neural networks'). China, India, and the United States emerged as leading contributors, with ۲۲۳, ۱۵۷, and ۱۱۶ articles, respectively. Key organizations, such as Beijing University of Posts and Telecommunications, and authors like Guizani, Mohsen, demonstrated significant impact. The findings highlight the growing integration of AI and IoT in smart manufacturing, with a focus on efficiency and predictive maintenance. This study provides a comprehensive overview of research trends and collaboration networks, offering insights for future Industry ۴.۰ research.

کلیدواژه ها:

Industry ۴.۰ ، artificial intelligence ، smart manufacturing ، predictive maintenance ، internet of things