This paper makes a study of the cause of manufacturing fault,develops the and/or- fault-tree of manufacturing quality fault for MC,and presents a new concept of faint manufacturing quality fault(FMQF)and the decision making tree with which the fault of manufacturing system would be found out from FMQF.An approach to identification of FMQF,based on fuzzy set theory,is presented,which can be used for estimating the status of equipment with the deviation of control charts.Based on the study above,an expert system for the flexible manufacturing system's FMQF detection and prediction is built.
To discover the knowledge of fault diagnosis in maintenance record of flexible manufacture system(FMS) equipment. An algorithm (process) was presented, which consists of ① preparatory phase in which some items in maintenance record are selected and decomposed into associated concepts and attributes, and ② discovering and establishing process, in which some possible relationships between the concepts and attributes can be established and knowledge is formulated. The rich diagnosis knowledge in maintenance record was captured through applying the method. An application of the method to the diagnosis system for FMS equipment showed that the approach is correct and effective.
The fault diagnosis model for FMS based on multi layer feedforward neural networks was discussed An improved BP algorithm,the tactic of initial value selection based on genetic algorithm and the method of network structure optimization were presented for training this model ANN(artificial neural network)fault diagnosis model for the robot in FMS was made by the new algorithm The result is superior to the rtaditional algorithm
