基于概念格的关联规则在排产管理的应用

Application of association rule based on concept lattice for scheduling management

针对汽车冲压厂生产数据量急剧增加的问题,研究了如何在冲压厂生产信息数据中运用基于概念格的关联规则挖掘技术,采用横向拆分与纵向合并的策略构造概念格,将普通概念格转化为量化概念格来生成关联规则。实验结果表明,该方法具有较高的挖掘效率,且能有效地寻找数据间隐藏的信息。从而为企业排产管理提供理论依据,达到优化排产的目的,在实际应用中取得了良好的分析效果。

Aimed at the problem that production data volume has increased dramatically in automotive stamping,how to use association rule mining based on concept lattice in production information data is explored. The concept lattice is structured with the strategy of horizontal split and vertical merge, and the association rules are generated by transforming ordinary concept lattice into quantitative concept lattice. The example results show that this method has high mining effi-ciency and the hidden information among data can be discovered effectively. The theoretical basis of scheduling guidance for companies is provided, and the purpose of optimizing scheduling is also realized. Furthermore, effective analytical results are obtained in the practical application.