Show simple item record

dc.contributor.authorRuiz Miguel, Santiago 
dc.contributor.authorOrtiz Fernández, Mª Cruz 
dc.contributor.authorSarabia Peinador, Luis Antonio 
dc.contributor.authorSánchez Pastor, Mª Sagrario 
dc.date.accessioned2018-10-22T09:46:15Z
dc.date.issued2018-11
dc.identifier.issn0169-7439
dc.identifier.urihttp://hdl.handle.net/10259/4973
dc.description.abstractIn the context of the paradigms founding the Quality by Design and Process Analytical Technology initiatives, the work herein presents a computational approach to support the decision-making process, in particular, about the feasibility of a product defined for some a priori given quality characteristics. The approach is based on the computation of the pareto-optimal front when simultaneously minimizing the expected differences between the predicted and the desired characteristics. Thus, the feasibility is tackled as an optimization problem with the novelty of doing so simultaneously for all the characteristics, preserving the correlation structure, but by separately handling each individual characteristic. With data from a low-density polyethylene production process, with fourteen process variables and five measured characteristics of the final polyethylene, solutions are found to define the Design Space for targeted quality characteristics on the product, and without the need of explicitly inverting the PLS (Partial Least Squares) prediction model fitted to the process.en
dc.description.sponsorshipJunta de Castilla y León (BU012P17), and also Spanish MINECO and Agencia Estatal de Investigación under research projects CTQ2014-53157-R, and CTQ2017-88894-Ren
dc.format.mimetypeapplication/pdf
dc.language.isoenges
dc.publisherElsevieren
dc.relation.ispartofChemometrics and Intelligent Laboratory Systems. 2018, V. 182, p. 70-78en
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectProcess analytical technologyen
dc.subjectQuality by designen
dc.subjectPartial least squaresen
dc.subjectPareto optimalityen
dc.subjectProcess decision makingen
dc.subjectIndustrial processesen
dc.subject.otherQuímica analíticaes
dc.subject.otherChemistry, Analyticen
dc.titleA computational approach to partial least squares model inversion in the framework of the process analytical technology and quality by design initiativesen
dc.typeArtículoes
dc.typeinfo:eu-repo/semantics/article
dc.date.embargo2020-11
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.relation.publisherversionhttps://doi.org/10.1016/j.chemolab.2018.08.014
dc.identifier.doi10.1016/j.chemolab.2018.08.014
dc.relation.projectIDinfo:eu-repo/grantAgreement/JCyL/BU012P17
dc.relation.projectIDinfo:eu-repo/grantAgreement/MINECO/CTQ2014-53157-R
dc.relation.projectIDinfo:eu-repo/grantAgreement/MINECO/CTQ2017-88894-R
dc.type.hasVersioninfo:eu-repo/semantics/acceptedVersionen


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record