Industrial ovens are pivotal in manufacturing, particularly food processing, electronics, and materials fabrication. In this context, temperature control algorithms must satisfy demanding control specifications, among which: setpoint tracking, disturbance rejection, energy saving, and actuator limitations. Specifically, one of the critical challenges in industrial ovens is achieving a uniform temperature distribution within the oven cavity, especially in the presence of disturbances. This paper focuses on a particular kind of industrial ovens installed in shrink tunnels, which are employed in manufacturing applications for polymeric packaging. In these applications, temperature uniformity is a key factor in determining the quality of the packages resulting from the heat shrinking process, making it a major concern. Consequently, we propose three Model Predictive Control (MPC) strategies for shrink tunnels aimed for temperature uniformity: an MPC for tracking (as a baseline), and two zone-based MPCs that steer the oven temperatures towards either a fixed or an adaptive range rather than a single target point. All control strategies are thoroughly and experimentally validated on a shrink tunnel workbench installed in a manufacturing facility. Specifically, we adopt the Rapid Control Prototyping (RCP) paradigm to speed up controller implementation and performance assessment. Experimental results demonstrate that the zone-based MPC strategies significantly improve the temperature uniformity within the oven cavity compared to the MPC for tracking formulation.
(2025). Optimizing industrial oven temperature uniformity: A model predictive control framework with rapid control prototyping [journal article - articolo]. In CONTROL ENGINEERING PRACTICE. Retrieved from https://hdl.handle.net/10446/302885
Optimizing industrial oven temperature uniformity: A model predictive control framework with rapid control prototyping
Previtali, Davide;Previdi, Fabio;Ferramosca, Antonio
2025-06-05
Abstract
Industrial ovens are pivotal in manufacturing, particularly food processing, electronics, and materials fabrication. In this context, temperature control algorithms must satisfy demanding control specifications, among which: setpoint tracking, disturbance rejection, energy saving, and actuator limitations. Specifically, one of the critical challenges in industrial ovens is achieving a uniform temperature distribution within the oven cavity, especially in the presence of disturbances. This paper focuses on a particular kind of industrial ovens installed in shrink tunnels, which are employed in manufacturing applications for polymeric packaging. In these applications, temperature uniformity is a key factor in determining the quality of the packages resulting from the heat shrinking process, making it a major concern. Consequently, we propose three Model Predictive Control (MPC) strategies for shrink tunnels aimed for temperature uniformity: an MPC for tracking (as a baseline), and two zone-based MPCs that steer the oven temperatures towards either a fixed or an adaptive range rather than a single target point. All control strategies are thoroughly and experimentally validated on a shrink tunnel workbench installed in a manufacturing facility. Specifically, we adopt the Rapid Control Prototyping (RCP) paradigm to speed up controller implementation and performance assessment. Experimental results demonstrate that the zone-based MPC strategies significantly improve the temperature uniformity within the oven cavity compared to the MPC for tracking formulation.File | Dimensione del file | Formato | |
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