大数据在拧紧数据分析中的应用

Application of Big Data in Tightening Data Analysis

拧紧问题分析是提升拧紧质量的重要手段,目前的方法为人工查看拧紧曲线,然后运用专业能力分析,费时费力,且拧紧问题分析准确率依赖分析人员经验。通过引入大数据技术,将拧紧曲线进行聚类,生成多个拧紧数据场景(后文简称拧紧场景或场景),并对拧紧场景进行人工标注(缺陷类型),最终由质保对各拧紧场景进行最终审核认证,得到可指导人员分析拧紧缺陷的拧紧场景。通过采用认证的拧紧场景对拧紧曲线进行分析,可以节省查看拧紧曲线和分析拧紧缺陷的时间,提高解决问题的时效性,不依赖分析人员的经验,能够快速提升车间的拧紧合格率。

Tightening problem analysis is an important means to improve the quality of tightening.The current method is to check the tightening curve manually,then professional ability is used to analyze it,which is timeconsuming and labor-intensive,and the accuracy of tightening problem analysis depends on the experience of the analyst.Through the introduction of big data technology,the tightening curves are clustered to generate multiple tightening data scenarios(hereinafter referred to as tightening scenes or scenes),and the tightening scenes are manually marked(defect types),and finally each tightening scene is reviewed and confirmed by the quality assurance department,which can guide personnel to analyze tightening defects.Using certified tightening scenarios to analyze tightening curves can save time for viewing tightening curves and analyzing tightening defects,improve the timeliness of problem solving and the tightening qualification rate in the workshop without relying on the experience of analysts.