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APPLICATION OF ARTIFICIAL NEURAL NETWORK IN PAPER INDUSTRY

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dc.contributor.author Kumar, Rajesh
dc.date.accessioned 2014-11-23T10:43:53Z
dc.date.available 2014-11-23T10:43:53Z
dc.date.issued 2008
dc.identifier Ph.D en_US
dc.identifier.uri http://hdl.handle.net/123456789/10342
dc.guide Mukherjee, S.
dc.guide Ray, A. K.
dc.description.abstract The thesis starts with introducing the operations and processes of a paper industry. From instrumentation view point these may be termed as subsystems like raw material preparation, pulping, washing of brown stock, bleaching, stock preparation, approach flow system, wet end operation, drying, calendaring and chemical recovery operation. Surface sizing, filling and coating are rather additional operations. The status of Indian ° paper mill, artificial intelligence and artificial neural network (ANN) control methodologies have been described in first chapter. A review of the literature has been presented in the second chapter for neural network and classical control applications to paper mill in particular. The chapter three deals with a comprehensive discussion on paper manufacture, operational parameters and control practice in a typical Indian paper industry. The next. three chapters discuss and analyze the results of various models of process control parameters of the wet end approach flow system including head box of paper machine control. The last chapter deals with the conclusion and recommendations on the work carried out in this present investigation. Chapter-1 introduces status of Indian paper mill and artificial neural network designing parameters. The present investigation has been planned to study the various aspects required for designing control systems using artificial neural network for wet end paper machine parameters, headbox in particular with the distinct objectives...... en_US
dc.language.iso en en_US
dc.subject PAPER TECHNOLOGY en_US
dc.subject ARTIFICIAL INTELLIGENCE en_US
dc.subject NEURAL NETWORK en_US
dc.subject PAPER INDUSTRY en_US
dc.title APPLICATION OF ARTIFICIAL NEURAL NETWORK IN PAPER INDUSTRY en_US
dc.type Doctoral Thesis en_US
dc.accession.number G14887 en_US


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