Please use this identifier to cite or link to this item: http://hdl.handle.net/10316/8180
Title: Multiscale statistical process control with multiresolution data
Authors: Reis, Marco S. 
Saraiva, Pedro M. 
Issue Date: 2006
Issue Date: 2006
Citation: AIChE Journal. 52:6 (2006) 2107-2119
Abstract: An approach is presented for conducting multiscale statistical process control that adequately integrates data at different resolutions (multiresolution data), called MR-MSSPC. Its general structure is based on Bakshi's MSSPC framework designed to handle data at a single resolution. Significant modifications were introduced in order to process multiresolution information. The main MR-MSSPC features are presented and illustrated through three examples. Issues related to real world implementations and with the interpretation of the multiscale covariance structure are addressed in a fourth example, where a CSTR system under feedback control is simulated. Our approach proved to be able to provide a clearer definition of the regions where significant events occur and a more sensitive response when the process is brought back to normal operation, when it is compared with previous approaches based on single resolution data. © 2006 American Institute of Chemical Engineers AIChE J, 2006
URI: http://hdl.handle.net/10316/8180
DOI: 10.1002/aic.10805
Rights: openAccess
Appears in Collections:FCTUC Eng.Química - Artigos em Revistas Internacionais

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