Estimating capability index in multivariate processes using bootstrap sequential sampling procedures

Dharmasena, Lasitha, Zeephongsekul, P. and Abdollahian, M. 2012, Estimating capability index in multivariate processes using bootstrap sequential sampling procedures, in ISSAT 2012 : Proceedings of the 18th International Conference on Reliability and Quality in Design, International Society of Science and Applied Technologies, Piscataway, N.J., pp. 173-177.

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Title Estimating capability index in multivariate processes using bootstrap sequential sampling procedures
Author(s) Dharmasena, LasithaORCID iD for Dharmasena, Lasitha orcid.org/0000-0002-3362-4819
Zeephongsekul, P.
Abdollahian, M.
Conference name Reliability and Quality in Design. Conference (18th : 2012: Boston, Mass.)
Conference location Boston, Mass.
Conference dates 26-28 Jul. 2012
Title of proceedings ISSAT 2012 : Proceedings of the 18th International Conference on Reliability and Quality in Design
Editor(s) [Unknown]
Publication date 2012
Start page 173
End page 177
Total pages 5
Publisher International Society of Science and Applied Technologies
Place of publication Piscataway, N.J.
Keyword(s) Bootstrapping techniques
Process capability indices
Sequential sampling procedures
Yield indices
Science & Technology
Technology
Engineering, Industrial
Operations Research & Management Science
Engineering
PROCESS YIELD
Summary Capability indices in both univariate and multivariate processes are extensively employed in quality control to assess the quality status of production batches before their release for operational use. It is traditionally a measure of the ratio of the allowable process spread and the actual spread. In this paper, we will adopt a bootstrap and sequential sampling procedures to determine the optimal sample size for estimating a multivariate capability index introduced by Pearns et. al. [12]. Bootstrap techniques have the distinct advantage of placing very minimum requirement on the distributions of the underlying quality characteristics, thereby rendering them more relevant under a wide variety of situations. Finally, we provide several numerical examples where the sequential sampling procedures are evaluated and compared.
ISBN 9780976348689
Language eng
Field of Research 080699 Information Systems not elsewhere classified
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category E2.1 Full written paper - non-refereed / Abstract reviewed
ERA Research output type E Conference publication
Copyright notice ©2012, ISSAT
Persistent URL http://hdl.handle.net/10536/DRO/DU:30075151

Document type: Conference Paper
Collection: Department of Information Systems and Business Analytics
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