The talk will deal with the identification of a reduced black box LTI MIMO model of a wood chip refining process operating in closed loop. This specific fiber extraction process is dedicated to the production of Mediumdensity Fiberboard (MDF). The model is design to predict the behavior of the two main quantities from the energy consumption perspective: the motor current of the refiner and the motor current of the plug screw. In the next steps, the obtained model will be employed for the economic multiobjective optimization of the process, that aims at minimizing energy consumption, maximizing the fiber quality, and ensuring compliance with the production constraint. This research activity is carried out within the EU project E2COMATION, Life-cycle optimization of industrial energy efficiency.

Energy-aware black box MIMO model identification of wood chips refining process operating in closed loop

Roberto Boffadossi;Marco Leonesio;
2022

Abstract

The talk will deal with the identification of a reduced black box LTI MIMO model of a wood chip refining process operating in closed loop. This specific fiber extraction process is dedicated to the production of Mediumdensity Fiberboard (MDF). The model is design to predict the behavior of the two main quantities from the energy consumption perspective: the motor current of the refiner and the motor current of the plug screw. In the next steps, the obtained model will be employed for the economic multiobjective optimization of the process, that aims at minimizing energy consumption, maximizing the fiber quality, and ensuring compliance with the production constraint. This research activity is carried out within the EU project E2COMATION, Life-cycle optimization of industrial energy efficiency.
2022
Istituto di Sistemi e Tecnologie Industriali Intelligenti per il Manifatturiero Avanzato - STIIMA (ex ITIA)
Sustainable manufacturing
Model identification
Simulation Error Minimization
wood chip refiner
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/447952
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