Identifying a Loss-in-Weight Feeder Design Space Based on Performance and Material Properties

  • Tianyi Li
  • James V. ScicoloneEmail author
  • Eric Sanchez
  • Fernando J. Muzzio
Original Article



Powder properties, such as density and adhesion, can cause large variability in the flow rate of ingredients fed from feeders, which can propagate through the system. Knowing an ideal range of operation and correlating powder properties to process performance can result in faster optimization of performance, which saves time and money.


A K-Tron KT-20 pharmaceutical loss-in-weight feeder was evaluated with multiple screw types, feed rates, and materials. The material was dispensed onto a catch scale, recording mass versus time, and analyzed for relative standard deviation and deviation from the setpoint. The materials used in this work were characterized by particle size, packing, and flow properties.


Linear relationships between the feeder’s throughput capacity and material bulk density were identified for four different types of screws. Analyzing the feeder data resulted in a region where the RSD was at a minimum across a range of screw speeds. This was identified between 20–90% screw speed for coarse concave, fine concave, and coarse auger screws and 40–90% screw speed for fine auger screws.


An optimal range of operation for K-Tron KT20 feeders was identified, as well as a linear correlation between material conditioned bulk density and maximum throughput for a given material and screw type. Using both the predictable maximum throughput and the optimal screw range, an optimal design space has been identified that will save development time and money.


Loss-in-weight feeders Continuous manufacturing Powder characterization Process development 



The authors would like to thank Nikita Soni, Glinka Pereira, Kien Chau, Lan Le, and Nikhita Shetty for the assistance in this work.

Funding Information

The research was financially supported by the Janssen Ortho LLC.


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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Chemical and Biochemical EngineeringRutgers, The State University of New JerseyPiscatawayUSA
  2. 2.Advanced Technologies Center of Excellence, Janssen Supply ChainGuraboUSA

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