Deep-level quality management based on big data analytics with case study

The Big data analytics gives new chances to the enterprises to enhance their management and manufacturing levels. A solution with case study is proposed to accomplish deep-level quality management based on big data analytics. First, the implementation of big data analytics based on industrial process data is illustrated with case study illustration. Through the analysis and feature extraction of off-line data, the corresponding reference model library is constructed, which can be used for real-time processing of unlabeled data in the industrial field. The cluster, outlier and other data indicators we can get from the calculation and analysis would have a certain guiding significance for the enterprise's deep-level quality management. Then, the distributed memory computing engine based on Spark, and the implementation of web application platform based on Spring MVC framework is also described. This can help to get higher performance and unrestricted abilities for data analytics. Meanwhile, good visibility and human-data interface can be achieved.