On monitoring of multiple non-linear profiles

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dc.contributor.author Chou, Shih-Hsiung
dc.contributor.author Chang, Shing I.
dc.contributor.author Tsai, Tzong-Ru
dc.date.accessioned 2014-12-03T20:21:23Z
dc.date.available 2014-12-03T20:21:23Z
dc.date.issued 2014-12-03
dc.identifier.uri http://hdl.handle.net/2097/18783
dc.description.abstract Most state-of-the-art profile monitoring methods involve studies of one profile. However, a process may contain several sensors or probes that generate multiple profiles over time. Quality characteristics presented in multiple profiles may be related multiple aspects of product or process quality. Existing charting methods for simultaneous monitoring of each multiple profile may result in high false alarm rates. Or worse, they cannot correctly detect potential relationship changes among profiles. In this study, we propose two approaches to detect process shifts in multiple non-linear profiles. A simulation study was conducted to evaluate the performance of the proposed approaches in terms of average run length under different process shift scenarios. Pros and cons of the proposed methods are discussed. A guideline for choosing the proposed methods is introduced. In addition, a hybrid method combining the salient points of both approaches is explored. Finally, a real-world data-set from a vulcanisation process is used to demonstrate the implementation of the proposed methods. en_US
dc.language.iso en_US en_US
dc.relation.uri http://www.tandfonline.com/doi/full/10.1080/00207543.2013.867088#.VDVDSfnF8k0 en_US
dc.rights This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Production Research on 16 Dec 2013, available online: http://www.tandfonline.com/doi/full/10.1080/00207543.2013.867088#.VDVDSfnF8k0. en_US
dc.subject Big Data en_US
dc.subject Profile Analysis en_US
dc.subject Multiple Profiles Analysis en_US
dc.subject Multivariate SPC en_US
dc.subject Multivariate EWMA en_US
dc.title On monitoring of multiple non-linear profiles en_US
dc.type Article (author version) en_US
dc.date.published 2014 en_US
dc.citation.doi 10.1080/00207543.2013.867088 en_US
dc.citation.epage 3224 en_US
dc.citation.issue 11 en_US
dc.citation.jtitle International Journal of Production Research en_US
dc.citation.spage 3209 en_US
dc.citation.volume 52 en_US
dc.contributor.authoreid changs en_US

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