DocumentCode :
2857333
Title :
Process capability analysis for non-normal distribution with lower specification limit
Author :
Korkusuz, Duygu ; Raharjo, Hendry ; Bergman, Bo
Author_Institution :
Dept. of Technol. Manage. & Econ., Chalmers Univ. of Technol., Gothenburg, Sweden
fYear :
2011
fDate :
6-9 Dec. 2011
Firstpage :
1466
Lastpage :
1470
Abstract :
Process capability analysis is an important element of any quality improvement initiative. However, estimating process capability is often problematic when it comes to non-normal distributions since the conventional methods sometimes give misleading results. In this paper, a new method for estimating process capability of non-normal distribution with only lower specification limit is proposed. The proposed method only considers the left tail of the distribution rather than taking all of the data points. For estimating the process capability, it employs least squares technique and normal approximation to the selected observations from the left tail. Here, the proposed method is only tested on lognormal distribution. Simulations and real-world data analysis are used for verification and validation purpose, respectively. An easy and practical guideline is also developed.
Keywords :
least squares approximations; log normal distribution; process capability analysis; quality control; least squares technique; log normal distribution; nonnormal distribution; normal approximation; process capability analysis; quality improvement initiative; specification limit; Accuracy; Data mining; Guidelines; Least squares approximation; Log-normal distribution; Wind turbines; Process capability analysis; log-normal distribution; lower specification limit;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Engineering and Engineering Management (IEEM), 2011 IEEE International Conference on
Conference_Location :
Singapore
ISSN :
2157-3611
Print_ISBN :
978-1-4577-0740-7
Electronic_ISBN :
2157-3611
Type :
conf
DOI :
10.1109/IEEM.2011.6118160
Filename :
6118160
Link To Document :
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