数据挖掘在精益管理效果评价中的应用

Sci. Program. Pub Date : 2022-01-10 DOI:10.1155/2022/3101614
Song Ding, Jun Li, Jiye Li
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引用次数: 0

摘要

定量评价是企业诊断的重要组成部分,促进了企业管理的科学化、现代化。目前,现有的企业管理评价方法无法完成对企业指标数据的挖掘,导致企业管理评价误差大,显著性系数低。因此,提出了数据挖掘在企业精益管理效果评价中的应用。分析了数据挖掘的过程和主要功能;采用数据挖掘算法建立精益管理效果评价指标体系,并计算指标权重。利用数据挖掘中的关联规则方法,根据企业精益管理水平评价指标和权重值的参数,通过模糊集变换思想,用隶属度来描述各指标和因素的模糊边界,构造模糊判断矩阵,通过多层复合计算得到最终评价结果。实验结果表明,本研究具有较高的显著性系数,提出的企业精益管理效果评价方法具有理想的准确性和较短的耗时。在实际应用中,累积贡献率较高,具有较高的稳定性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of Data Mining in Effect Evaluation of Lean Management
Quantitative evaluation is an important part of enterprise diagnosis, which promotes the scientific and modern management of enterprises. At present, the existing enterprise management evaluation methods cannot complete the mining of enterprise index data, which leads to large error and low significance coefficient in enterprise management evaluation. Therefore, the application of data mining in enterprise lean management effect evaluation is put forward. The process and main functions of data mining are analyzed; data mining algorithm is used to establish the evaluation index system of lean management effect and calculate the index weight. Using the association rules method in data mining, according to the parameters of enterprise lean management level evaluation index and weight value, through the fuzzy set transformation idea, the fuzzy boundary of each index and factor is described by the membership degree, the fuzzy judgment matrix is constructed, and the final evaluation result is obtained by multilayer compound calculation. Experimental results show that this study has a high significance coefficient, and the proposed evaluation method of enterprise lean management effect has ideal accuracy and short time consumption. In practical application, the cumulative contribution rate is higher and has higher stability.
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