The past decade has witnessed an exodus toward smart and lean manufacturing methods. The trend includes integrating intelligent methods into sustainable manufacturing systems purposely to improve the machining efficiency, reduce waste and also optimize productivity. Manufacturing systems have seen transformations from conventional methods, leaning towards smart manufacturing in line with the industrial revolution 4.0. Since the manufacturing process encompasses a wide range of human development capacity, it is essential to analyze its developmental trends, thereby preparing us for future uncertainties. In this work, we have used a Bibliometric analysis technique to study the developmental trends relating to machining, digital twins and artificial intelligence techniques. The review comprises the current activities in relation to the development to this area. The article comprises a Bibliometric analysis of 464 articles that were acquired from the Web of Science database, with a search period until November 2024. The method of obtaining the data includes retrieval from the database, qualitative analysis and interpreting the data via visual representation. The raw data obtained were redrawn using the origin software, and their visual interpretations were represented using the VOSviewer software (VOSviewer_1.6.19). The results obtained indicate that the number of publications related to the searched keywords has remarkably increased since the year 2018, achieving a record maximum of over 80 articles in 2024. This is indicative of its increasing popularity. The analysis of the articles was conducted based on the author countries, journal types, journal names, institutions, article types, major and micro research areas. The findings from the analysis are meant to provide a bibliometric explanation of the developmental trends in machining systems towards achieving the IR 4.0 goals. Additionally, the results would be helpful to researchers and industrialists that intend to achieve optimum and sustainable machining using digital twin technologies.
Intelligent factories provide flexible and adaptive production processes, offering significant competitive advantages to manufacturers and are widely studied in industrial production. Information technology is recognized as a key factor influencing the production efficiency and intelligence of Intelligent factories. However, current research has primarily focused on the operational processes of intelligent factories, with limited analysis of information technology. To address this gap, this paper conducts a bibliometric analysis of information technology in intelligent factories, along with a review of its development and applications. Firstly, the data collection and visualization methods of bibliometrics are introduced. Secondly, bibliometric analyses are performed using platforms such as VOSviewer and Scimago to investigate co-authorship, co-citation, and contributions from countries and institutions in the field of information technology for intelligent factories. Finally, a framework for information technology in intelligent factories is established, summarizing its development in terms of information acquisition, transmission, processing, management, and control. This paper aims to assist scholars in understanding the development trends of intelligent factory technology and enhancing the informatization level of intelligent factories.