A review of industrial big data for decision making in intelligent manufacturing
Chunquan Li, Yaqiong Chen, Yuling Shang
Abstract
Under the trend of economic globalization, intelligent manufacturing has attracted a lot of attention from academic and industry. Related enabling technologies make manufacturing industry more intelligent. As one of the key technologies in artificial intelligence, big data driven analysis improves the market competitiveness of manufacturing industry by mining the hidden knowledge value and potential ability of industrial big data, and helps enterprise leaders make wise decisions in various complex manufacturing environments. This paper provides a theoretical analysis basis for big data-driven technology to guide decision-making in intelligent manufacturing, fully demonstrating the practicability of big data-driven technology in the intelligent manufacturing industry, including key advantages and internal motivation. A conceptual framework of intelligent decision-making based on industrial big data-driven technology is proposed in this study, which provides valuable insights and thoughts for the severe challenges and future research directions in this field.