数据驱动下的智能制造企业供应商效率评价  

Data-Driven Supplier Efficiency Evaluation on Intelligent Manufacturing Enterprises

作　　者：陈诚 石莉[1] 石梅 丁雪红 CHEN Cheng;SHI Li;SHI Mei;DING Xue-Hong(College of Computer Science and Technology,Huaibei Normal University,Huaibei 235000,China)

机构地区：[1]淮北师范大学计算机科学与技术学院,淮北235000

出　　处：《计算机系统应用》2020年第5期1-10,共10页Computer Systems & Applications

基　　金：国家自然科学基金(71801108);安徽省高校自然科学基金(KJ2017A391,KJ2018B04,KJ2019B04)。

摘　　要：智能制造环境下,供应商效率评价对于智能制造企业的发展至关重要.本文根据智能制造企业供应商的特点、评价指标体系构建原则和文献总结,构建智能制造企业供应商效率评价指标体系.通过AHP-熵值法确定各评价指标的权重,利用调研收集到的企业数据,结合BP神经网络对效率型供应商进行效率等级划分,并提出改善意见以及相应的激励策略,以此促进企业与供应商的进一步合作交流.案例分析结果表明,此方法对于供应商效率评价具有较强的实用性.Under the environment of intelligent manufacturing,supplier efficiency evaluation is very important for the development of intelligent manufacturing enterprises.This study constructs the supplier efficiency evaluation index system of intelligent manufacturing enterprises according to the characteristics of suppliers,the construction principles of evaluation index system,and literature summary.The weights of each index are determined by AHP-entropy method,and the supplier is graded by using the enterprise data of subject cooperation and BP neural network.The improvement suggestions for suppliers are put forward and further cooperation and communication between enterprises and suppliers are promoted.The example results show that this method has strong practicability for supplier efficiency evaluation.

关 键 词：智能制造 数据驱动 BP神经网络 供应商效率 AHP-熵值法 

分 类 号：F426.6[经济管理—产业经济] F274