关键词: 质量控制, 模糊推理系统, 异常诊断, 模糊算子, 异因排序

Abstract: Aiming at the uncertain and vague problems during quality control and diagnosis process, a Fuzzy Inference System (FIS) was developed based on fuzzy logic. This system was composed of six fuzzy inference sub-modules and one aggregation module. Each module took the control charts'abnormity pattern data as input. Abnormity pattern presence degree was determined through input fuzzification. By defuzzifying the inference result through centroid method, the contribution intensity of corresponding cause to the input abnormity was obtained in each module. All the evidence supporting each cause from all the modules was aggregated by using fuzzy connective operators, and the causes were sequenced according to the final aggregation results. The assignable causes search could begin with the cause with the highest priority when process went out of control. Finally, an application example was given. By comparing to the quality software Minitab for the same process data, the application result illustrated that the system could detect the abnormity which Minitab couldnt. Corresponding examining suggestions were also presented.

Key words: quality control, fuzzy inference system, abnormity diagnosis, fuzzy operators, assignable causes ranking