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

• Published in: Journal of pharmaceutical innovation Vol. 15; no. 3; pp. 482 - 495
• Main Authors: Li, Tianyi, Scicolone, James V., Sanchez, Eric, Muzzio, Fernando J.
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.09.2020
• Subjects: Biochemical Engineering; Biomedical and Life Sciences; Biomedicine; Biotechnology; Industrial and Production Engineering; Original Article; Pharmacology/Toxicology; Process development; Loss-in-weight feeders; Continuous manufacturing; Powder characterization
• ISSN: 1872-5120; 1939-8042
• DOI: 10.1007/s12247-019-09394-4

Purpose 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. Method 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. Results 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. Conclusion 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.