Research Note: What can fuzziness do for capability analysis based on fuzzy data

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CHEN S.M.; Hung T.M.

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Journal Paper

Paper Information

Journal: Scientia Iranica Year:2021 | Volume:28 | Issue:2 (Transactions E: Industrial Engineering) Page(s): 1049-1064

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Title

Research Note: What can fuzziness do for capability analysis based on fuzzy data

Author(s)

CHEN S.M. | Hung T.M. | Issue Writer Certificate

Keywords

Fuzzy set

Lower membership function

Upper membership function

Process incapability index

Abstract

One advantage of Process incapability index over the classical process capability index is that it provides uncontaminated separation between process accuracy and process precision. However, the value of the index is difficult to determine accurately when process parameters cannot be determined precisely. In such a case, Fuzzy set theory can be applied to obtain more flexible and sensitive information. In this paper, a fuzzy Process incapability index is proposed when the specification limits are assumed to be type-2 fuzzy. When the process mean and variance are unknown and when the observations are measured imprecisely, three fuzzy estimators are considered. A simulation study is conducted based on the Thin-Film-Transistor Liquid-Crystal Display (TFT-LCD) fuzzy process. By applying the total integral value method to the membership function of a fuzzy index, it becomes easier to make a comparison of the quality of different processes.

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APA: Copy

CHEN, S.M., & Hung, T.M.. (2021). Research Note: What can fuzziness do for capability analysis based on fuzzy data. SCIENTIA IRANICA, 28(2 (Transactions E: Industrial Engineering)), 1049-1064. SID. https://sid.ir/paper/978295/en

Vancouver: Copy

CHEN S.M., Hung T.M.. Research Note: What can fuzziness do for capability analysis based on fuzzy data. SCIENTIA IRANICA[Internet]. 2021;28(2 (Transactions E: Industrial Engineering)):1049-1064. Available from: https://sid.ir/paper/978295/en

IEEE: Copy

S.M. CHEN, and T.M. Hung, “Research Note: What can fuzziness do for capability analysis based on fuzzy data,” SCIENTIA IRANICA, vol. 28, no. 2 (Transactions E: Industrial Engineering), pp. 1049–1064, 2021, [Online]. Available: https://sid.ir/paper/978295/en

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