(239b) Predicting Feeder Performance during Hopper Refill Based on Material Flow Properties | AIChE

(239b) Predicting Feeder Performance during Hopper Refill Based on Material Flow Properties


Li, T. - Presenter, Rutgers University
Muzzio, F., Rutgers, The State University of New Jersey
Glasser, B., Rutgers University
Wang, Y., Rutgers University
Purpose: Loss-in-weight feeder plays a vital role in continuous powder processing. Periodic hopper refill of the feeder, which is needed for continuous operation, can lead to inconsistent and poor feeding performance. Importantly, feeder’s feedrate deviation caused by hopper refill is strongly dependent on material flow properties. The purpose of this work is to develop a methodology that identifies predictive correlation between material flow properties and feeder’s performance during hopper refill. Method: The proposed methodology includes techniques to characterize material flow properties, methods to quantify loss-in-weight feeder’s feeding performance during hopper refill, and predictive multivariate analysis. Six calibration materials with varying flow properties were firstly characterize by five techniques, which provides 30 flow indices. Two approaches to correlate feeding performance and material flow properties were discussed in the study: principal component analysis, followed by similarity scoring (PCA-SS), and partial least squares regression (PLSR). Results: Experimental results shows that feeder’s maximum feedrate deviation, deviation time and total deviation caused by hopper refill are all heavily dependent on material flow properties. Both statistical approaches were validated by testing an additional material. The predicted results were in good agreement with the experimental results. Conclusion: The work shows efficient approaches to correlate material flow properties with feeder's performance during hopper refill using multivariate analysis. This work is essential for early phase feeder work development when time and amount of material is limited.  


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