Abstract: In view of the difficulties in evaluation and early warning of abnormal production loss for minicar rear axle key process,an abnormal production loss evaluation and early warning method was put forward,which integrated real-time acquisition of key process'abnormal production information with grey fuzzy evaluation of production abnormal loss and early warning of abnormal production loss.The abnormal events of minicar rear axle key process were classified,and an evaluation index system of key process abnormal production was established.The key technologies such as evaluation method of abnormal production loss based on grey fuzzy evaluation and the early warning method of abnormal production loss based on RBF neural networks were studied.The research results were successfully applied in a minicar rear axle product enterprise,and good effects was achieved.

Key words: minicar rear axle, key process, production abnormal loss, neural networks, evaluation, early warning

摘要： 针对微车后桥关键工序生产异常损失评估及预警困难等问题,提出一种集关键工序生产异常信息实时采集、生产异常损失评估、生产异常损失预警为一体的微车后桥关键工序生产异常损失评估及预警方法。对微车后桥关键工序生产异常事件进行了分类,建立了关键工序生产异常损失的评价指标体系,并对基于灰色模糊评判的关键工序生产异常损失评估、基于径向基函数神经网络的关键工序生产异常损失预警等关键技术进行了研究。将以上研究成果在重庆某后桥生产工厂进行应用验证,取得了良好的效果。

关键词: 微车后桥, 关键工序, 生产异常损失, 径向基函数神经网络, 评估, 预警