## 4 Discussion  
The results show that the results of the simulations and experimental results are in good agreement. The trends of measured and simulated pressure drops as the air velocity at the filter inlet changes are parallel. The deviation between the curves could be related to the uncertainty in the air velocity measurement with the KIMO sensor, which, due to space constraints, was installed close to a curve. More significant deviations are observed for the pressure drops for case 8, which could be related to the fact that coating the sleeve with the food-grade film is not perfectly equivalent to clogging the sleeve evenly. Obviously, this difference increases as the level of fouling increases, and this is why deviation is more pronounced for case 8 than for case 6.  
The velocity trends at the measured point inside the filter are also in agreement. There are more significant deviations in this case, and this may be mainly related to three aspects, which may also explain why the deviations increase as the air flow rate at the filter inlet increases:  
1. The data extracted from the simulation is exclusively related to the tangential component of the velocity vector, while the anemometer reading, although correctly positioned, without taking into account human error, is partially affected by the other velocity components, due to its construction characteristics.
2. The way the sleeves are constrained to the head of the filter allows them to oscillate, given even the 3 m length, is not constrained to the base or anywhere else. The oscillation can impact the flow field distribution, even significantly affecting the velocity value measured by the sensor.
3. The presence of areas completely obstructed by the film alternating with completely clean areas affects airflow differently than a sleeve that is uniformly obstructed.  
Thus, it can be concluded that the experimental results confirm the correlations between pressure drops and air flow rate and between the measured velocity at the identified point inside the filter and air flow rate. They also confirm that pressure drops increase as sleeve clogging increases and that the air velocity at the identified point inside the filter increases if clogging proceeds in a standard manner.  
In this study, it was not possible to validate the model for the real-time adjustment of the sequence and frequency of compressed air jets, whose results are reported in Table 9. In fact, by using food-grade film to artificially reproduce sleeve clogging, compressed air injections would have been ineffective. It will be necessary in future activities to test and validate this model in a real production setting in order to verify the effectiveness of the proposed method and to optimize both the sequence and the frequency based on experimental evidence.  
The digital twin developed, demonstrated that it can accurately predict the sleeves' RUL and identify failures. At present, it has been trained with data under normal clogging conditions. Future activities will have to focus on experimenting with many more operating conditions to increase its robustness to make it industrially viable. Moreover, simulation results can be used to expand the capabilities of the digital twin by providing data that are of great operational interest but would be physically difficult to acquire (e.g., the upward velocity within the sleeves, the impact velocity against the sleeves, the flow rate filtered by each sleeve, etc.).