Statistical Hypothesis Testing for Asymmetric Tolerance Index
| Autor: | Chang-Hsien Hsu, Kuen-Suan Chen, Wei-Zong Chen, Shui-Chuan Chen |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Technology
0209 industrial biotechnology Index (economics) QH301-705.5 QC1-999 02 engineering and technology 01 natural sciences Standard deviation process capability indices 010104 statistics & probability 020901 industrial engineering & automation Statistics General Materials Science statistical hypothesis testing Biology (General) 0101 mathematics QD1-999 Instrumentation Mathematics Confidence region Statistical hypothesis testing Fluid Flow and Transfer Processes Physics Process Chemistry and Technology Feasible region General Engineering Process (computing) Function (mathematics) Engineering (General). Civil engineering (General) quality characteristics Confidence interval Computer Science Applications Chemistry confidence interval TA1-2040 asymmetric tolerance |
| Zdroj: | Applied Sciences, Vol 11, Iss 6249, p 6249 (2021) Applied Sciences Volume 11 Issue 14 |
| ISSN: | 2076-3417 |
| DOI: | 10.3390/app11146249 |
| Popis: | Many of the nominal-the-best quality characteristics of important machine tool components, such as inner or outer diameters, have asymmetric tolerances. An asymmetric tolerance index is a function for the average of the process and the standard deviation. Unfortunately, it is difficult to obtain the 100(1−α)% confidence interval of the index. Therefore, this study adopts Boole’s inequality and DeMorgan’s theorem to find the combined confidence region for the average of the process as well as the standard deviation. Next, using the asymmetric tolerance index for the target function and the combined confidence region for the feasible region, this study applies mathematical programming to find the confidence interval as well as employs this confidence interval for statistical hypothesis testing. Lastly, this study demonstrates the applicability of the proposed approach with an illustrative example. |
| Databáze: | OpenAIRE |
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