Mapping the Research Landscape and Predicting Future Growth: A Bibliometric and Time Series Study of Artificial Intelligence/Machine Learning Applications in Mechatronics Engineering Using Web of Science Data

Authors : Tülbiya Karahan, Mustafa Çakır, Mesut Yılmaz, Okan Oral

Pages : 659-678

Doi:10.18185/erzifbed.1696490

View : 80 | Download : 60

Publication Date : 2025-08-31

Article Type : Research Paper

Abstract :This study examines the impact of Artificial Intelligence (AI) and Machine Learning (ML) technologies on the fields of Mechatronics Engineering, Robotics, and Automation. Through a comprehensive bibliometric analysis of publications indexed in the Web of Science (WoS) database, the historical development, key research trends, and prominent themes of this interdisciplinary domain are revealed. Additionally, six different time series forecasting methods—ARIMA, ETS, Theta, Holt-Winters, Polynomial Regression, and Naive Model—are employed to predict the number of scientific publications for the year 2025. The analysis results indicate a growing influence of AI/ML in the field of mechatronics and a clear upward trend in publication volume. This study offers a unique perspective on the research directions in the field by quantitatively illustrating how AI and ML interact with mechatronics engineering.
Keywords : Mekatronik, Yapay Zekâ Uygulamaları, Bibliyometrik Analiz, Zaman Serisi Analizi, Yayın Eğilimleri

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