Today, with the development of artificial intelligence, its application in different areas, including production and operations, has expanded. Explainable artificial intelligence (XAI) is a new research topic that has emerged with the development of artificial intelligence. This study aimed to investigate the applications of XAI in production and operations using the systematic review approach. For this purpose, a systematic review of the most recent studies published in the Science Direct, Scopus, and Emerald knowledge bases was conducted. After screening through different stages, 29 articles were reviewed and analyzed. The results showed that publications on XAI have been on an upward trend in recent years, with a significant increase observed from 2021 to 2024. Also, the fields of engineering, production, decision-making, and computer science are the major areas in which recent studies have been published. The results also suggested that the largest scope of XAI application was observed at the organizational level, followed by the industrial level. Based on the findings, the fields of production and operations, followed by logistics and supply chain, were the most frequently studied areas. Regarding the methods used, the SHAP method was the most commonly applied method in the XAI studies, followed by Integrated Gradient and SVM methods. In general, the results of this study showed that XAI is a new field of research that is gradually developing in terms of methodology and areas of application.
