METHODICAL APPROACHES TO PROCESS CAPABILITY ANALYSIS IN THE CASES OF NON-NORMAL DISTRIBUTIONS OF MONITORED QUALITY CHARACTERISTIC

1 NEPRAŠ Karel
Co-authors:
1 PLURA Jiří
Institution:
1 VSB - Technical University of Ostrava, Faculty of Metallurgy and Materials Engineering, Ostrava, Czech Republic, EU
Conference:
25th Anniversary International Conference on Metallurgy and Materials, Hotel Voronez I, Brno, Czech Republic, EU, May 25th - 27th 2016
Proceedings:
Proceedings 25th Anniversary International Conference on Metallurgy and Materials
Pages:
1950-1955
ISBN:
978-80-87294-67-3
ISSN:
2694-9296
Published:
14th December 2016
Proceedings of the conference were published in Web of Science and Scopus.
Metrics:
73 views / 48 downloads
Abstract

Evidence of production process capability is one of the basic requirements for automotive industry suppliers including metallurgical companies. From this reason these suppliers must perform process capability analysis. While in the cases of normal distribution of monitored quality characteristic the methodology of process capability analysis is practically uniform, in the cases, when data are not normally distributed, individual producers use different approaches. This fact may cause different results of process capability analysis. This paper deals with analysis of methodical approaches used by selected automotive producers for process capability analysis in the cases of non-normal distributions of monitored quality characteristic. Process capability analysis is performed using selected strategies for data with different skewness. Analysis of different process capability indices is done and achieved results are compared with other possibilities of process capability analysis in the cases of data non-normality.

Keywords: Process capability, methodology, non-normality.

© This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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