-
Tytuł:
-
Product quality evaluation by confidence intervals of process yield index.
-
Autorzy:
-
Chen KS; Department of Industrial Engineering and Management, National Chin-Yi University of Technology, Taichung, 411030, Taiwan, ROC.; Department of Business Administration, Chaoyang University of Technology, Taichung, 41349, Taiwan, ROC.; Institute of Innovation and Circular Economy, Asia University, Taichung, 41354, Taiwan, ROC.
Hsu CH; Department of Business Administration, Asia University, Taichung, 41354, Taiwan, ROC. .
Chiou KC; Department of Finance, Chaoyang University of Technology, Taichung, 41349, Taiwan, ROC.
-
Źródło:
-
Scientific reports [Sci Rep] 2022 Jun 22; Vol. 12 (1), pp. 10508. Date of Electronic Publication: 2022 Jun 22.
-
Typ publikacji:
-
Journal Article
-
Język:
-
English
-
Imprint Name(s):
-
Original Publication: London : Nature Publishing Group, copyright 2011-
-
MeSH Terms:
-
Confidence Intervals*
-
References:
-
Math Biosci Eng. 2020 Nov 3;17(6):7605-7620. (PMID: 33378911)
-
Entry Date(s):
-
Date Created: 20220622 Date Completed: 20220624 Latest Revision: 20220825
-
Update Code:
-
20240105
-
PubMed Central ID:
-
PMC9217850
-
DOI:
-
10.1038/s41598-022-14595-y
-
PMID:
-
35732640
-
Statistical techniques have a beneficial effect on measuring process variability, analyzing the variability concerning product requirements, and eliminating the variability in product manufacturing. Process capability indices (PCIs) are not only easy to understand but also able to be directly employed by the manufacturing industry. The process yield index offers accurate measurement of the process yield, and it is a function of two unilateral six sigma quality indices. This paper initiates to develop the confidence intervals of the process yield index by using joint confidence regions of two unilateral six sigma quality indices for all quality characteristics of a product. Then integrate these joint confidence regions to find the confidence intervals of the product yield index. All manufacturing industries can use these confidence intervals to make statistical inferences to assess whether the process capability of the product and all quality characteristics has reached the required level, and to grasp the opportunities for improvement. An illustrated example on driver integrated circuit of micro hard disk is provided.
(© 2022. The Author(s).)
Zaloguj się, aby uzyskać dostęp do pełnego tekstu.
