Artificial intelligence in green production and industrial engineering: challenges and future perspectives

This study presents key perspectives and challenges in relation to artificial intelligence in green production and industrial engineering. Numerous studies have examined the benefits of artificial intelligence for achieving operational efficiency and improved environmental performance; however, few studies have identified future perspectives and challenges. In this study, content, bibliographic and cluster analyses are conducted to extract and cluster attributes related to artificial intelligence in green production and challenges in industrial engineering from the Scopus database, and meta-analysis is used to validate the topics and refine the attributes and clusters. The entropy weighted method and fuzzy Delphi method are utilized to identify key challenges. Fuzzy decision-making trials and laboratory evaluations are performed to analyze perspectives that should be prioritized on the basis of cause-and-effect interrelationships. The results reveal that data management and analysis as well as waste and risk management are key future perspectives that must be addressed.