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An attribute studentized fuzzy interval-valued chart based on normalized transformation
The International Journal of Electrical Engineering & Education Pub Date : 2021-01-14 , DOI: 10.1177/0020720920984005
Chih-Ching Yang 1 , Enas Abdulhay 2
Affiliation  

The attribute data, in general, is as important as variable data for data analysis and quality control which can offer more information and modify the error. And to change the type of multiple observations is applied to enhance the effect of control chart. In this thesis, the approach of normalized transformation would be employed to transfer the attribute data become variable data and extend the data type of interval observation. Using the transfer result construct a new control chart, attribute studentized fuzzy interval-valued (ASFIV) chart, with attribute fuzzy interval-valued data which is used to control the shift of quality characteristics for the manufacturing, electrical industry, traditional industry, education science and management fields where quality characteristics include the education score, sales satisfaction, numbers of defective product and so on. The ASFIV chart with interval observation of quality characteristic can point out the variation and degree of shift for the controlled characteristic in various industries. As the interval-valued quality characteristic, to be more specific, is generated which is faster detection the shift than the approach of traditional control chart. Moreover, the numerical studies are used to explain the significant consequent for application of the new ASFIV chart in this study. As such, the studentized fuzzy chart by attribute interval-valued observations could obtain the effective measurement outcome by the attribute data for the practical phenomena and provide related information for decision making of education policy, performance management and sustainable development of industry etc.



中文翻译:

基于归一化变换的属性学生化模糊区间值图

通常,属性数据与变量数据一样重要,以进行数据分析和质量控制,可以提供更多信息并修改错误。并为改变多个观测值的类型而应用,以增强控制图的效果。本文采用归一化变换的方法将属性数据转换为变量数据,并扩展了区间观测的数据类型。使用转移结果构造一个新的控制图,即属性学生化模糊区间值(ASFIV)图,以及属性模糊区间值数据,该数据用于控制制造业,电气行业,传统行业,教育科学的质量特征的变化和管理领域,其质量特征包括教育程度,销售满意度,不良产品的数量等。带有间隔观察质量特征的ASFIV图可以指出各个行业中受控特征的变化和变化程度。更具体地说,随着区间值质量特性的产生,比传统控制图的方法更快地检测到偏移。此外,数值研究用于解释在本研究中应用新ASFIV图表的重要结果。这样,通过属性间隔值观测的学生化模糊图可以通过属性数据获得针对实际现象的有效测量结果,并为教育政策的决策,绩效管理和产业的可持续发展等提供相关信息。带有间隔观察质量特征的ASFIV图可以指出各个行业中受控特征的变化和变化程度。更具体地说,随着区间值质量特性的产生,比传统控制图的方法更快地检测到偏移。此外,数值研究用于解释在本研究中应用新ASFIV图表的重要结果。这样,通过属性间隔值观测的学生化模糊图可以通过属性数据获得针对实际现象的有效测量结果,并为教育政策的决策,绩效管理和产业的可持续发展等提供相关信息。带有间隔观察质量特征的ASFIV图可以指出各个行业中受控特征的变化和变化程度。更具体地说,随着区间值质量特性的产生,比传统控制图的方法更快地检测到偏移。此外,数值研究用于解释在本研究中应用新ASFIV图表的重要结果。这样,通过属性间隔值观测的学生化模糊图可以通过属性数据获得针对实际现象的有效测量结果,并为教育政策的决策,绩效管理和产业的可持续发展等提供相关信息。

更新日期:2021-01-14
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