To solve the problems in the quality control and improvement of coiled tubing steel strips production, such as scattered and inefficient production data, difficult performance fluctuation factor analysis, complex mult...To solve the problems in the quality control and improvement of coiled tubing steel strips production, such as scattered and inefficient production data, difficult performance fluctuation factor analysis, complex multivariate statistical analysis, and low accuracy and difficulty in mechanical property prediction, an industrial data analysis platform for coiled tubing steel strips production has been preliminarily developed.As the premise and foundation of analysis, industrial data collection, storage, and utilization are realized by using multiple big data technologies.With Django as the agile development framework, data visualization and comprehensive analyses are achieved.The platform has functions including overview survey, stability analysis, comprehensive analysis(such as exploratory data analysis, correlation analysis, and multivariate statistics),precise steel strength prediction, and skin-passing process recommendation.The platform is helpful for production overviewing and prompt responding, laying a foundation for an in-depth understanding of product characteristics and improving product performance stability.展开更多
文摘To solve the problems in the quality control and improvement of coiled tubing steel strips production, such as scattered and inefficient production data, difficult performance fluctuation factor analysis, complex multivariate statistical analysis, and low accuracy and difficulty in mechanical property prediction, an industrial data analysis platform for coiled tubing steel strips production has been preliminarily developed.As the premise and foundation of analysis, industrial data collection, storage, and utilization are realized by using multiple big data technologies.With Django as the agile development framework, data visualization and comprehensive analyses are achieved.The platform has functions including overview survey, stability analysis, comprehensive analysis(such as exploratory data analysis, correlation analysis, and multivariate statistics),precise steel strength prediction, and skin-passing process recommendation.The platform is helpful for production overviewing and prompt responding, laying a foundation for an in-depth understanding of product characteristics and improving product performance stability.
