Contributo in atti di convegno, 2021, ENG, 10.1115/DETC2021-71447
Trunal Patil, Lara Rebaioli, Irene Fassi
STIIMA-CNR, Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing, Consiglio Nazionale delle Ricerche, Milan, Italy
Printed circuit boards (PCBs) are made of several materials, including platinum, gold, silver, and rare earth elements, which are very valuable from a circular economy perspective. The PCB end of life management starts with the component removal, then the PCBs are shredded into small particles. Eventually, different separation methods are applied to the pulverized material to separate metals and non-metals. The corona electrostatic separation is one of the methods that can be used for this purpose since it is able to separate the conductive and non-conductive materials. However, the lack of knowledge to set the process parameters may affect the efficiency of the corona electrostatic separation process, ultimately resulting in the loss of valuable materials. The simulation of particle trajectory can be very helpful to identify the effective process parameters of the separation process. Thus, in this study, a simulation model to predict the particles trajectories in a belt type corona electrostatic separator is developed with the help of COMSOL Multiphysics and MATLAB software. The model simulates the particle behavior taking into account the electrostatic, gravitational, centrifugal, electric image, and air drag forces. Moreover, the predicted particles trajectories are used to analyze the effects of the roll electrode voltage, angular velocity of roll electrode, and size of the particles on the separation process.
IDETC/CIE 2021 - ASME 2021 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference, online, 17-20/08/2021
End of Life management, Printed Circuit Boards, Corona Electrostatic Separation, Particle Trajectory Simulation
Patil Trunal Kashinath, Fassi Irene, Rebaioli Lara
STIIMA – Istituto di Sistemi e Tecnologie Industriali Intelligenti per il Manifatturiero Avanzato
ID: 457143
Year: 2021
Type: Contributo in atti di convegno
Creation: 2021-09-30 12:42:08.000
Last update: 2022-10-05 13:06:48.000
External IDs
CNR OAI-PMH: oai:it.cnr:prodotti:457143
DOI: 10.1115/DETC2021-71447