多品种小批量制造过程工序质量动态控制方法研究  

Research on dynamic quality control method of multi-variety and small-batch manufacturing Process

作　　者：宋承轩 吉卫喜 Song Chengxuan;Ji Weixi(Jiangnan University,Wuxi 214122,Jiangsu,China)

机构地区：[1]江南大学机械工程学院

出　　处：《现代制造工程》2019年第6期30-36,共7页Modern Manufacturing Engineering

基　　金：江苏省产学研联合创新资金项目(BY2014023-30)

摘　　要：针对某电梯零/部件制造企业对产品制造过程工序质量可控性的要求,结合电梯零/部件制造企业多品种小批量机加工车间存在的质量样本数据少且数据实时采集困难、质量状态实时监控及预警不准确等问题,提出了集制造过程质量数据智能采集、工序质量实时监测以及质量预警三层技术的多品种小批量制造过程工序质量动态控制方法。对其中基于无线射频识别(RFID)的产品工序质量数据实时采集方法、基于多图联合控制的小样本统计过程控制(SPC)工序质量控制方法以及基于T-S模糊神经网络的工序质量预警方法进行了研究。最后,通过实例验证了该制造过程工序质量动态控制方法的可行性。Concerning the process quality control requirements for an elevator parts and components manufacturing enterprise, combined with the issues in the elevator parts and components of multi-variety and small-batch processing plant that the lack of the sample data of the quality, the acquisition difficulties of the real-time data, and the real-time monitoring of quality status and early warning are not accurate, and so on. Puts forward a dynamic control method of multi-variety and small-batch manufacturing process quality, which combines the intelligent collection of manufacturing process quality data, real-time monitoring of process quality and quality warning. Then, studying the real-time acquisition method of process quality data based on RFID, the quality control method of small sample SPC process based on multi-graph joint control and the process quality warning method based on T-S fuzzy neural network. Finally, an example is given to demonstrate the feasibility of the dynamic control method of the manufacturing process quality.

关 键 词：多品种小批量 统计过程控制 模糊神经网络 工序质量控制 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]