摘要
研究了混凝土企业的生产现状及混凝土质量影响因素,提出了结构化、半结构化和非结构化分类方法。进而在质量管理戴明循环方法基础上提出了加速PDCA循环的理论。文中基于生产实时数据,综合混凝土生产人员素质、环境影响、设备性能等非结构化因素,采用自适应神经模糊推理系统(ANFIS)方法,建立了混凝土抗压强度模型,成功地预测改进措施对质量的影响程度与趋势,用于加速PDCA循环中检查(C)→处理(A)的过程。
This paper researched on the quality management in current concrete corporations, finding out the structured, semi-structured and un- structured factors which influence the concrete quality. An artificial intelligence model-ANFIS was built to predict the strength of concrete com- pressive strength and to accelerate the Check （C）→Action （A） process in PDCA cycle. All of the data used in this model were collected in the real production process, which incorporated the human factors, environmental factors and equipment factors. A satisfactory predicted result was achieved. The artificial intelligence model made the foundation of the quantifying process of concrete industry.
出处
《科技和产业》
2013年第10期161-165,共5页
Science Technology and Industry
