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    • 4. 发明申请
    • DETECTING ANOMALIES IN FIELD FAILURE DATA
    • 检测现场故障数据中的异常
    • US20110137711A1
    • 2011-06-09
    • US12630866
    • 2009-12-04
    • Satnam SinghPulak BandyopadhyayCalvin E. Wolf
    • Satnam SinghPulak BandyopadhyayCalvin E. Wolf
    • G06Q10/00G06F15/00
    • G06Q10/06G06F11/079G06Q10/0639G06Q10/20G07C5/0808
    • A method of detecting anomalies in the service repairs data of equipment. A failure mode-symptom correlation matrix correlates failure modes to symptoms. Diagnostic trouble codes are collected for an actual repair for the equipment. The diagnostic trouble codes are provided to a diagnostic reasoner for identifying failure modes. Diagnostic assessment is applied by the diagnostic reasoner for determining the recommended repairs to perform on the equipment in response to identifying the failure modes. Each of the recommended repairs is compared with the actual repair used to repair the equipment. A mismatch is identified in response to any recommended repair not matching the actual repair. Reports are generated for displaying all of the identified mismatches. The reports are analyzed for determining repair codes having an increase in a number of anomalies. Service centers are alerted of a correct repair for the identified failure mode.
    • 检测设备维修数据中异常的方法。 故障模式 - 症状相关矩阵将故障模式与症状相关联。 收集诊断故障代码以进行设备的实际维修。 诊断故障代码被提供给用于识别故障模式的诊断推理器。 诊断评估由诊断推理器应用,用于确定对设备执行的建议修理以响应识别故障模式。 将每个推荐的维修与用于维修设备的实际维修进行比较。 鉴于任何推荐的维修与实际维修不匹配,确定不匹配。 生成报告以显示所有已识别的不匹配。 分析报告以确定具有异常数量增加的修复代码。 提醒服务中心对所识别的故障模式进行正确修复。