In order to help enterprises identify product problems and design defects and improve product satisfaction, it is necessary to analyze the product quality of discrete manufacturing industry with big data. This paper describes the characteristics of product quality big data in manufacturing industry, summarizes the research progress and development trends of product quality analysis in discrete manufacturing industry at home and abroad from four aspects of data acquisition and processing, quality prediction, quality control and quality traceability, points out the challenges of various theoretical methods under the background of big data, and discusses the solutions and development trends to deal with these challenges. The results show that the analysis can provide a reference for further research.