摘要
国内很多制造型企业在推行精益生产时效果并不令人满意,主要表现为精益化不足和精益化过度,而要做到恰到好处的精益化,准确了解企业自身精益生产水平就显得非常重要。把模糊理论和神经网络技术应用于对企业精益生产水平的评价,建立科学、系统的精益生产水平评价指标体系,构建模糊神经网络评价模型。实例分析表明,网络模型的实际输出值与预测输出值相差不大,表明该模型具有较高的预测精度。测试结果进一步验证模型的可靠性和有效性。
The effect of implementation of lean production in many domestic manufacturing enterprises is not satisfactory- due to lean insufficiency and lean excess, it is very important to understand the level of lean production of enterprises. A scientific and systematic evaluation index system of lean production, level is established, and a fuzzy neural network evalua- tion model is constructed, applying fuzzy theory and artificial neural network technology for the evaluation of the level of lean production. The example analysis shows that, the actual output value of the network model is not much different from the predicted output value, it shows that the model has high prediction accuracy. The test results further verify the reliabili- ty and validity of the model.
作者
王黎
蒋国璋
向锋
Wang Li;Jiang Guozhang;Xiang Feng(Key Laboratory of Metallurgical Equipment and Control Technology;Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering, Wuhan University of Science and Technology, Wuhan 430081, China)
出处
《科技管理研究》
CSSCI
北大核心
2018年第12期114-118,共5页
Science and Technology Management Research
基金
国家自然科学基金项目"钢铁生产混合流程智能调度及其知识网系统的研究"(71271160)
关键词
精益生产
模糊理论
神经网络
评价模型
lean production
fuzzy theory
neural network
evaluation model
