Consiglio Nazionale delle Ricerche

Tipo di prodottoArticolo in rivista
TitoloA computer-aided methodology for the optimization of electrostatic separation processes in recycling
Anno di pubblicazione2016
  • Elettronico
  • Cartaceo
Autore/iM. Borrotti, A. Pievatolo, I. Critelli, A. Degiorgi, and M. Colledani
Affiliazioni autoriInstitute of Applied Mathematics and Information Technologies National Research Council of Italy Milan Italy; Department of Mechanical Engineering Politecnico di Milano Milan Italy
Autori CNR e affiliazioni
  • inglese
AbstractThe rapid growth of technological products has led to an increasing volume of waste electrical and electronic equipments (WEEE), which could represent a valuable source of critical raw materials. However, current mechanical separation processes for recycling are typically poorly operated, making it impossible to modify the process parameters as a function of the materials under treatment, thus resulting in untapped separation potentials. Corona electrostatic separation (CES) is one of the most popular processes for separating fine metal and nonmetal particles derived from WEEE. In order to optimize the process operating conditions (i.e., variables) for a given multi-material mixture under treatment, several technological and economical criteria should be jointly considered. This translates into a complex optimization problem that can be hardly solved by a purely experimental approach. As a result, practitioners tend to assign process parameters by few experiments based on a small material sample and to keep these parameters fixed during the process life-cycle. The use of computer experiments for parameter optimization is a mostly unexplored area in this field. In this work, a computer-aided approach is proposed to the problem of optimizing the operational parameters in CES processes. Three metamodels, developed starting from a multi-body simulation model of the process physics, are presented and compared by means of a numerical and simulation study. Our approach proves to be an effective framework to optimize the CES process performance. Furthermore, by comparing the predicted response surfaces of the metamodels, additional insight into the process behavior over the operating region is obtained.
Lingua abstractinglese
Altro abstract-
Lingua altro abstract-
Pagine da133
Pagine a148
Pagine totali-
RivistaApplied stochastic models in business and industry (Print)
Attiva dal 1999
Editore: John Wiley & Sons, - Chichester
Paese di pubblicazione: Regno Unito
Lingua: inglese
ISSN: 1524-1904
Titolo chiave: Applied stochastic models in business and industry (Print)
Titolo proprio: Applied stochastic models in business and industry. (Print)
Titolo abbreviato: Appl. stoch. models bus. ind. (Print)
Numero volume della rivista32
Fascicolo della rivista1
Verificato da refereeSì: Internazionale
Stato della pubblicazionePublished version
Indicizzazione (in banche dati controllate)
  • Scopus (Codice:2-s2.0-84956589579)
  • ISI Web of Science (WOS) (Codice:000369134600010)
Parole chiaveArtificial neural networks, Design of computer experiments, Kriging, Response surface, WEEE
Link (URL, URI)
Titolo parallelo-
Scadenza embargo-
Data di accettazione16/07/2015
Note/Altre informazioniOnline: 13/08/2015
Strutture CNR
  • IMATI — Istituto di matematica applicata e tecnologie informatiche "Enrico Magenes"
  • STIIMA — Istituto di Sistemi e Tecnologie Industriali Intelligenti per il Manifatturiero Avanzato
Moduli/Attività/Sottoprogetti CNR
  • SP.P01.038.001 : Product service systems and new business models
Progetti Europei-
A computer-aided methodology for the optimization of electrostatic separation processes in recycling (documento privato )
Descrizione: Articolo pubblicato
Tipo documento: application/pdf