Application of Machine Learning for Sustainability in Manufacturing Supply Chain Industry 4.0 Perspective: A Bibliometric Based Review for Future Research

Machine learning plays a vital role in the manufacturing supply chain because it is key to solving sustainability problems and managing the massive quantity of data produced by various industrial activities. Therefore, the current study's objective is to provide a systematic and bibliometrically based overview of how machine learning (ML) methods are applied to the sustainability of the manufacturing supply chain. In the current study, the authors employ a bibliometric review methodology that focuses on the statistical analysis of published scientific documents with a neutral objective of the current status and potential for future research in machine learning applications in the sustainable manufacturing supply chain. The present study demonstrates how the industrial sector might resolve supply chain challenges using ML approaches. A framework for ML-Supply chains is suggested in light of the results. Researchers, decision-makers, and practitioners will find the framework helpful in guiding the effective management of industrial supply chain practices. The body of research that is currently accessible does not offer a thorough and bibliometric analysis of the prospects for ML approaches in industrial supply chains with a framework. The bibliometric examination of machine learning applications in the industrial supply chain is covered in this paper, which further enhances its novelty.