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New Approach to Evaluate the Lubrication Process in Various Granule Filling Levels and Rotating Mixer Sizes Using a Thermal Effusivity Sensor
被引:4
|作者:
Uchiyama, Jumpei
[1
]
Aoki, Shigeru
[1
]
Uemoto, Yoshifumi
[2
]
机构:
[1] Eisai & Co Ltd, Japan Technol, Global Demand Chain Technol, New Chem Ent Demand Chain Unit,Eisai Demand Chain, Gifu 5016195, Japan
[2] Eisai & Co Ltd, Global Formulat Japan Pharmaceut Sci Technol, Gifu 5016195, Japan
关键词:
lubrication process mechanism;
process analytical technology;
thermal effusivity;
monitoring lubrication process;
magnesium stearate;
NEAR-INFRARED SPECTROSCOPY;
POWDER BLEND HOMOGENEITY;
FILM COATING PROCESS;
BOHLE BIN-BLENDER;
MAGNESIUM STEARATE;
SCALE-UP;
COMPRESSED TABLETS;
DISSOLUTION RATE;
MIXING TIME;
PREDICTION;
D O I:
10.1248/cpb.c14-00634
中图分类号:
R914 [药物化学];
学科分类号:
100701 ;
摘要:
The principles of thermal effusivity are applied to an understanding of the detailed mechanisms of the lubrication process in a rotating mixer. The relationships and impact of the lubrication process by the pattern of powder flow, the filling level, and the rotating mixer size were investigated. Thermal effusivity profiles of the lubrication process, as obtained, indicate that lubrication is a two-phase process. The intersection point of the first and second phases (IPFS) is influenced by changing the filling level, thus changing the resulting number of avalanche flows created. The slope of the second phase (SSP) is influenced by the relationship between the number and the length of avalanche flows. Understanding this difference between the first and second phases is important to successfully evaluate the impact of proposed changes in the lubrication process. From this knowledge, a predictive model of the lubrication profile can be generated to allow an evaluation of proposed changes to the lubrication process. This model allows estimation of the lubrication profile at different filling levels and in different rotating mixer sizes. In this study, the actual lubrication profile almost coincides with the model predicted lubrication profile. Based on these findings, it is assumed that lubrication profiles at a commercial scale can be predicted from data generated at the laboratory scale. Further, it is assumed that changes in the filling level can also be estimated from the laboratory or current data.
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页码:164 / 179
页数:16
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