Neural network model-based paper machine marginal cost curves

Patrinos, P; Sarimveis, H; Retsina, T; Rutherford, SR; Alexandridis, A

dc.contributor.author	Patrinos, P	en
dc.contributor.author	Sarimveis, H	en
dc.contributor.author	Retsina, T	en
dc.contributor.author	Rutherford, SR	en
dc.contributor.author	Alexandridis, A	en
dc.date.accessioned	2014-03-01T02:50:34Z
dc.date.available	2014-03-01T02:50:34Z
dc.date.issued	2006	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/35144
dc.relation.uri	http://www.scopus.com/inward/record.url?eid=2-s2.0-33845811443&partnerID=40&md5=e4e98c58edd9a8e9ac76fe75c24152eb	en
dc.subject.other	Energy costs	en
dc.subject.other	Marginal cost curves	en
dc.subject.other	Computer architecture	en
dc.subject.other	Costs	en
dc.subject.other	Mathematical models	en
dc.subject.other	Optimization	en
dc.subject.other	Productivity	en
dc.subject.other	Radial basis function networks	en
dc.subject.other	Papermaking machinery	en
dc.subject.other	Costs	en
dc.subject.other	Mathematical Models	en
dc.subject.other	Neural Networks	en
dc.subject.other	Optimization	en
dc.subject.other	Paper Machines	en
dc.subject.other	Productivity	en
dc.title	Neural network model-based paper machine marginal cost curves	en
heal.type	conferenceItem	en
heal.publicationDate	2006	en
heal.abstract	In this paper we present a methodology for developing paper machine marginal cost curves, which include variable material and energy costs, fixed costs and overhead costs. The methodology is based on the radial basis function (RBF) neural network architecture and takes into account the complex interactions between the different mill departments. The outcome of the proposed method is the calculation of marginal costs for different paper machine production rates and different grades. The resulting cost curves can be used to take optimal decisions regarding paper machine loadings and optimize production allocation.	en
heal.journalName	2005 TAPPI Engineering, Pulping, Environmental Conference - Conference Proceedings	en
dc.identifier.volume	2006	en