Shrink tunnels are machines consisting of an industrial oven and conveyor belt that are widely used for polymeric packaging applications. A constant stream of manufacturing products, enveloped by a thin plastic film, is fed to the oven cavity via the conveyor belt. The heat within the cavity shrinks the plastic, creating the packs. Several conflicting control specifications characterize the heat shrinking process: the oven must work in a tight temperature range, the heat dissipation due to the insertion of products in the cavity must be minimal, and energy saving. In this work, we propose an Economic Model Predictive Control (EMPC) strategy that tackles all these objectives while handling actuator limitations. A thorough simulation study is carried out to tune the EMPC to maximize the performances while minimizing energy expenditure.

(2024). Towards energy-efficient shrink tunnels by means of Economic Model Predictive Control . Retrieved from https://hdl.handle.net/10446/287752

Towards energy-efficient shrink tunnels by means of Economic Model Predictive Control

Pitturelli, Leandro;Previtali, Davide;Ferramosca, Antonio;Previdi, Fabio
2024-01-01

Abstract

Shrink tunnels are machines consisting of an industrial oven and conveyor belt that are widely used for polymeric packaging applications. A constant stream of manufacturing products, enveloped by a thin plastic film, is fed to the oven cavity via the conveyor belt. The heat within the cavity shrinks the plastic, creating the packs. Several conflicting control specifications characterize the heat shrinking process: the oven must work in a tight temperature range, the heat dissipation due to the insertion of products in the cavity must be minimal, and energy saving. In this work, we propose an Economic Model Predictive Control (EMPC) strategy that tackles all these objectives while handling actuator limitations. A thorough simulation study is carried out to tune the EMPC to maximize the performances while minimizing energy expenditure.
2024
Pitturelli, Leandro; Previtali, Davide; Ferramosca, Antonio; Previdi, Fabio
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10446/287752
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