A Bibliometric Analysis of the Applications of Artificial Intelligence Techniques to Engineering Design

Abstract

<ns7:p>In the era of technological sophistication, advancements and integration of artificial intelligence (AI) techniques in engineering design are revolutionizing numerous fields. Traditional processes are no longer effective in solving engineering problems. This study systematically examines scientific publications in the field of selected AI techniques in engineering design in various applications, such as deep learning, machine learning, and simulation. This mini-review also adopted a PRISMA framework-based methodology to extract data from the Scopus database and, then analyzed such data to identify research gaps and future directions in AI’s application to engineering design. A bibliometric analysis of AI in Engineering design was conducted to examine its role in engineering design, interdisciplinary collaboration, geographic distribution, and research focus. This study identifies critical research gaps and offers recommendations for future directions in AI applications for engineering design. The findings provide valuable insights into the state of the art and showcase valuable information for stakeholders to tune into the advances in AI techniques to enhance traditional engineering design processes.</ns7:p>