Application of Data Mining in the Evaluation of Enterprise Lean Management Effect
Author(s) -
Jinpeng Yang,
Ying Liu
Publication year - 2021
Publication title -
scientific programming
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.269
H-Index - 36
eISSN - 1875-919X
pISSN - 1058-9244
DOI - 10.1155/2021/4774140
Subject(s) - computer science , enterprise information system , lean manufacturing , enterprise data management , enterprise software , process management , interface (matter) , knowledge management , data mining , business , manufacturing engineering , engineering , bubble , maximum bubble pressure method , parallel computing
In order to improve the effect of enterprise lean management, this study proposes a lean data mining algorithm based on the characteristics of lean data in enterprise management. This study connects data mining and lean production to study the data of enterprise management operation, proposes an intelligent data processing model suitable for modern enterprise management, and constructs the model function module in combination with the enterprise operation management process. Moreover, this study constructs an evaluation system for the effect of enterprise lean management based on data mining. The system provides a human-computer interaction interface, and operators can use various functions and services provided by the system through a visual interface. Through experimental research, it can be known that the enterprise lean effect evaluation system based on data mining proposed in this study can play an important role in enterprise lean management.
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