作　　者： ; ; ; ;

机构地区： 华南理工大学机械与汽车工程学院

出　　处： 《华南理工大学学报（自然科学版）》 2009年第8期1-7,共7页

摘　　要： 提出基于两种质量统计过程控制和粗糙集理论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,发展了一种新的基于粗糙集理论的工序质量诊断模型,以度量生产参数对工序质量影响的可能性和重要性.采用的面向用户需求的质量优化控制算法在实际应用中具有较强的可操作性.研究方法在酵母生产过程的应用验证了模型的正确性. Based on the statistical process control with two quality theories and the rough set theory, an integrated model of quality monitoring, diagnosis and control is proposed for the manufacturing process. In the investigation, the on-line quality monitoring and abnormal process diagnosis model based on the statistical process control with two quality theories is dealt with, and a new rough set-based quality diagnosis model is proposed to quantify the proba- bility and importance of the effects of manufacturing parameters on the quality, thus overcoming the information in- consistency and incompleteness inherent in manufacturing processes. Moreover, an optimal control algorithm of produefion quality oriented to user requirements is presented, which is then proved feasible. The correctness of the proposed models is finally verified by an application to yeast production.

关 键 词： 质量监测 质量诊断 质量控制 统计过程控制 粗糙集理论

领　　域： [机械工程]