Multi-tier supply chains in Industry 4.0 are critical emerging issues today. This article briefly examines the Industry 4.0 policies in different countries. In order to decide on a better model and the number of topics in the model, a comparative test of the coherence value for two machine learning classification methods based on Latent Dirichlet Allocation was conducted. Subsequently, the article combines the traditional literature review method with a survey article referring to Industry 4.0 and multi-tier supply chain, indexed by science citation index expanded (SCI-EXPANDED) and social sciences citation index (SSCI) during 2009-2018. The research direction, research type, and research approaches of each paper were extracted, and the topics of all the articles were classified by machine learning, which provides feasible routes and valuable research directions for researchers in this field. Afterward, the research status and future research directions were identified. The combination of natural language processing in machine learning to classify research topics and traditional literature review to investigate article details greatly improved the objectivity and scientificity of the study and laid a solid foundation for further researc