Show simple item record

dc.contributor.authorHarrou, Fouzi
dc.contributor.authorSun, Ying
dc.date.accessioned2017-02-05T07:08:03Z
dc.date.available2017-02-05T07:08:03Z
dc.date.issued2017-01-20
dc.identifier.citationHarrou F, Sun Y (2016) PLS-based memory control scheme for enhanced process monitoring. 2016 IEEE 14th International Conference on Industrial Informatics (INDIN). Available: http://dx.doi.org/10.1109/INDIN.2016.7819208.
dc.identifier.doi10.1109/INDIN.2016.7819208
dc.identifier.urihttp://hdl.handle.net/10754/622826
dc.description.abstractFault detection is important for safe operation of various modern engineering systems. Partial least square (PLS) has been widely used in monitoring highly correlated process variables. Conventional PLS-based methods, nevertheless, often fail to detect incipient faults. In this paper, we develop new PLS-based monitoring chart, combining PLS with multivariate memory control chart, the multivariate exponentially weighted moving average (MEWMA) monitoring chart. The MEWMA are sensitive to incipient faults in the process mean, which significantly improves the performance of PLS methods and widen their applicability in practice. Using simulated distillation column data, we demonstrate that the proposed PLS-based MEWMA control chart is more effective in detecting incipient fault in the mean of the multivariate process variables, and outperform the conventional PLS-based monitoring charts.
dc.description.sponsorshipThis publication is based upon work supported by the King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) under Award No: OSR-2015-CRG4-2582.
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.relation.urlhttp://ieeexplore.ieee.org/document/7819208/
dc.rights(c) 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
dc.subjectComputational modeling
dc.subjectControl charts
dc.subjectData models
dc.subjectFault detection
dc.subjectMathematical model
dc.subjectMonitoring
dc.subjectProcess control
dc.titlePLS-based memory control scheme for enhanced process monitoring
dc.typeConference Paper
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentStatistics Program
dc.identifier.journal2016 IEEE 14th International Conference on Industrial Informatics (INDIN)
dc.eprint.versionPost-print
kaust.personHarrou, Fouzi
kaust.personSun, Ying
kaust.grant.numberOSR-2015-CRG4-2582
refterms.dateFOA2018-06-14T07:57:55Z
dc.date.published-online2017-01-20
dc.date.published-print2016-07


Files in this item

Thumbnail
Name:
INDIN2016_PD-009717.pdf
Size:
407.0Kb
Format:
PDF
Description:
Accepted Manuscript

This item appears in the following Collection(s)

Show simple item record