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

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.

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Publication Details

Journal
Erzincan Üniversitesi Fen Bilimleri Enstitüsü Dergisi
Published
2025-08-14
DOI
https://doi.org/10.18185/erzifbed.1696490
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
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article

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

Mesut Yılmaz, Okan Oral, Mustafa Çakır, Tülbiya Karahan
Erzincan Üniversitesi Fen Bilimleri Enstitüsü Dergisi
Big Data and Business Intelligence
article

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

Mesut Yılmaz, Okan Oral, Mustafa Çakır, Tülbiya Karahan
article en

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.

Erzincan Üniversitesi Fen Bilimleri Enstitüsü DergisiVol. 18(2)
İskenderun Technical University (TR)
Openalex Percentile: Top 54%
Big Data and Business Intelligence
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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 — Mesut Yılmaz, Okan Oral, et al. · Erzincan Üniversitesi Fen Bilimleri Enstitüsü Dergisi (2025) | TGRS Research Map | TGRS