生产质量在线监测、诊断和控制的粗糙集模型研究

为了确保企业持续稳定的产品质量，提出了基于两种质量统计过程控制和粗糙集理论相结合的生产过程质量监测－诊断－控制集成模型。研究了统计过程控制及两种质量理论的质量在线监测和上下工序诊断模型。针对实际生产获取信息的不完备性，重点研究了不一致信息环境下基于粗糙集理论的工序质量诊断模型，分析工序中各生产参数对质量影响的可能性，度量参数对质量影响的重要程度。提出的面向用户需求的质量优化控制算法在实际应用中具有更大的适应性和可操作性。

Models of Quality Monitoring, Diagnosis and Control on Line in Manufacturing Processes

It is a key to monitor, diagnose and control quality in manufacturing processes on line to ensure products with consistent quality. The paper proposes a combined model of quality monitoring, diagnosis and control based on the monitoring data itself. Statistical process monitoring & diagnosis model with two kinds of quality theory can find out any abnormal quality and abnormal process. Rough set approach to quality diagnosis of the abnormal process has the ability to achieve the solution to quality problem and quantify the influential significance of manufacturing parameters on the quality in inconsistent and incomplete information inherent in manufacturing processes. The suggested controller based on satisfying user requirement is able to extract control rules from processing data and set new operating specifications. An implementation example of yeast production is provided to demonstrate the models are usefully applied in a real world.