摘要
为了解决目前离散型工厂MES系统深层数据查询时间长以及生产环节中返工返修的信息追溯问题,通过对生产过程数据的归一化和重组等操作,针对实际产线的工序流程进行了图数据建模,实现了关系型数据和图数据的映射关系,并通过Smith-Waterman序列比对算法对返工返修产线进行归因与匹配,得到相似产线工序的最大公共子集,建立了基于图数据库存储的信息处理系统。结果表明,利用在图数据库中已建立的工序数据,重复序列检测能够有效地识别工序中的返工返修问题。
In order to solve the problems of long deep data query time and traceability of rework and repair information in the current discrete factory MES system,graph data modeling was carried out for the actual process flow of the production line through normalization and reorganization of production process data.The mapping relationship between relational data and graph data was achieved,and the Smith-Waterman sequence alignment algorithm was used to attribute and match rework and repair production lines,obtaining the maximum common subset of similar production line processes.An information processing system based on graph database storage was established.The results indicate that using the established process data in the graph database,duplicate sequence detection can effectively identify rework and repair issues in the process.
作者
徐志达
鲍敏
XU Zhida;BAO Min(School of Mechanical Engineering,Zhejiang Sci-Tech University,Hangzhou 310018,China)
出处
《自动化与仪表》
2025年第8期128-133,共6页
Automation & Instrumentation
