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Using Fuzzy Theory in %GR&R and NDC of Measurement System Analysis

机译:在测量系统分析的%GR&R和NDC中使用模糊理论

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ISO9001:2000 and TS 16949 have become the major quality system management models in present traditional and Hi-tech industries. The Measurement System Analysis (MSA) Reference Manual, on the other hand, is one of the core tools in ISO/TS 16949. MSA aims to evaluate Gauge Repeatability and Reproducibility (GR&R) where the control, monitoring, and maintenance of the measurement process are required in measurement systems so that the measurement capability could be ensured under statistical control. An ideal measurement system should present the statistical characteristic of zero error on any measured product. Nevertheless, such an ideal measurement system hardly exists. Managers therefore have to adopt such measurement systems with unsatisfactory statistical characteristics. Traditional MSA indexes are constructed with definite observed values. Nevertheless, measurements with observed values are not entirely error-free. For this reason, this study proposes to research three cases in a case company and apply the integration of Fuzzy Theory and GR&R to discuss the differences in the evaluation index GR&R and the Number of Distinct Categories (NDC). Substituting fuzzy numbers for definite numbers found that the data of %GR&R were increased and NDC was decreased after fuzzification. Such results verify that the fuzzified %GR&R and NDC become stricter in the determination criterion. The research outcomes could assist the case company in improving the reference data of measurement systems and promoting the measurement quality.
机译:ISO9001:2000和TS 16949已成为当今传统和高科技行业的主要质量体系管理模式。另一方面,《测量系统分析(MSA)参考手册》是ISO / TS 16949的核心工具之一。MSA旨在评估仪表的可重复性和可重复性(GR&R),以控制,监视和维护测量过程测量系统中需要使用这些参数,以便可以在统计控制下确保测量能力。理想的测量系统应在任何被测产品上呈现零误差的统计特征。然而,这样的理想测量系统几乎不存在。因此,管理人员必须采用统计性能不理想的此类测量系统。传统的MSA索引是用确定的观察值构造的。然而,具有观测值的测量并非完全没有错误。因此,本研究建议在一家案例公司中研究三个案例,并应用模糊理论和GR&R的集成来讨论评估指标GR&R和不同类别数(NDC)的差异。将模糊数替换为确定数,发现模糊化后%GR&R的数据增加,而NDC减少。这样的结果证明,模糊的%GR&R和NDC在确定标准上变得更加严格。研究成果可以帮助案例公司改善测量系统的参考数据并提高测量质量。

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