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浙江大学学报(工学版)
Journal of ZheJiang University (Engineering Science)  2020, Vol. 54 Issue (2): 374-380    DOI: 10.3785/j.issn.1008-973X.2020.02.019
Mechanical and Energy Engineering     
Quality consistency evaluation method for granules in fluidized bed granulation based on powder properties
Jie ZHAO1(),Hai-bin QU1,*(),Geng TIAN2,Yan-ding WEI2
1. Pharmaceutical Informatics Institute, Zhejiang University, Hangzhou 310058, China
2. Key Laboratory of Advanced Manufacturing Technology of Zhejiang Province, Zhejiang University, Hangzhou 310027, China
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Abstract  

The physical properties of stackability, compressibility and flowability were comprehensively characterized by micromeritics evaluation method, in order to conduct a quality evaluation of granules produced by pulsed-spray fluid-bed granulation (PSFBG). Physical fingerprint were constructed with twelve indexes, such as angle of repose, porosity and particle size, to evaluate the quality consistence of PSFBG products. The parameter index, the parameter profile index and the good compressibility index were established to study the compressibility of particles. Multivariate data analysis was used to evaluate the quality attributes of different batches of granules. Results show that the physical fingerprint can not only reflect the similarities and differences of the properties of granules obtained by different granulation methods, but also assist in judging the compression characteristics of particles. Combined with the method of multivariate statistical analysis, the physical fingerprint can be used to analyze the regularity between multiple indicators when they are related to each other. Physical fingerprint spectroscopy is an effective tool for evaluating the properties of granules, which provides new insights into the quality consistence evaluation of PSFBG products.

Key words： fluid bed      pulsed spray      physical properties      physical fingerprint      compressibility      multivariate data analysis     
Received: 30 December 2018      Published: 10 March 2020
CLC:  TP 273  
  TQ 460  
Corresponding Authors: Hai-bin QU     E-mail: zhaojie_1021@zju.edu.cn;quhb@zju.edu.cn
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Jie ZHAO
Hai-bin QU
Geng TIAN
Yan-ding WEI
Cite this article:

Jie ZHAO,Hai-bin QU,Geng TIAN,Yan-ding WEI. Quality consistency evaluation method for granules in fluidized bed granulation based on powder properties. Journal of ZheJiang University (Engineering Science), 2020, 54(2): 374-380.

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http://www.zjujournals.com/eng/10.3785/j.issn.1008-973X.2020.02.019     OR     http://www.zjujournals.com/eng/Y2020/V54/I2/374


基于粉体学性质的流化床制粒质量一致性评价方法

为了评价流化床脉冲喷雾制粒（PSFBG）产品的质量，采用粉体学评价方法表征颗粒的堆积特性、可压性、流动性等物理属性. 构建由休止角、空隙率、粒径等12个指标构成的物理指纹谱. 基于物理指纹谱对PSFBG产品进行质量一致性评价，并通过构建参数指数、参数轮廓指数和良好可压性指数分析颗粒的压缩特性；运用多变量数据分析对不同批次颗粒的质量属性进行评价. 结果表明，所建立的物理指纹谱不仅可以反映不同制备工艺所获得颗粒的粉体学性质的异同，还能辅助判断颗粒压缩特性，结合多元统计分析方法在多个指标互相关联的情况下分析它们之间的规律. 物理指纹谱是评价产品粉体学性质的有效工具，为PSFBG产品质量一致性的综合评价提供思路.


关键词： 流化床,  脉冲喷雾,  物理属性,  物理指纹谱,  压缩特性,  多变量数据分析 
Fig.1 Schematic diagram of pulsed-spray fluid-bed granulation experimental setup
批次 工艺参数
θ/°C Hw/% V/（r?min?1） A/MPa T/min c/%
1 60 70 30 0.16 3 70
2 60 50 20 0.12 1 30
3 65 60 20 0.16 3 30
4 55 60 30 0.12 1 70
5 65 50 25 0.12 3 70
6 55 70 25 0.16 1 30
7 55 50 30 0.14 3 30
8 65 50 30 0.16 1 50
9 55 70 20 0.12 3 50
10 60 60 25 0.14 2 50
11 60 60 25 0.14 2 50
12 60 60 25 0.14 2 50
Tab.1 Process parameters of pulsed-spray fluid-bed granulation in different batches
一级指标 二级指标 符号 单位
堆积特性 松密密度 ρb g/mL
振实密度 ρt g/mL
可压性 空隙率 ε %
卡尔指数 I ?
流动性 豪斯纳比率 H ?
休止角 α °
稳定性 水的质量分数 w %
均一性 颗粒累积分布为10%的粒径 d10 μm
颗粒累积分布为50%的粒径 d50 μm
颗粒累积分布为90%的粒径 d90 μm
粒径分布宽度 S ?
粒径范围 W μm
Tab.2 Parameters used in physical fingerprint
Fig.2 Physical fingerprint of granules obtained from different PSFBG batches
一级指标 二级指标 单位 实验值 转化值 属性均值
堆积特性 ρb g/mL 0.30 10.00 10.00
ρt g/mL 0.42 10.00 10.00
可压性 ε % 29.44 6.97 6.97
I ? 0.29 6.97 6.97
流动性 H ? 1.42 6.72 5.00
α ° 47.02 3.28 5.00
稳定性 w % 5.46 3.47 3.47
均一性 d10 μm 84.62 0.00 2.00
d50 μm 121.66 0.00 2.00
d90 μm 219.27 0.00 2.00
S ? 1.11 10.00 2.00
W μm 134.65 0.00 2.00
Tab.3 Related physical parameters of granules obtained from PSFBG batch 3
Fig.3 Physical fingerprint mapping of granules obtained from different PSFBG batches
批次 批次
1 2 3 4 5 6 7 8 9 10 11 12
1 1 ? ? ? ? ? ? ? ? ? ? ?
2 0.759 9 1 ? ? ? ? ? ? ? ? ? ?
3 0.391 0 0.550 1 1 ? ? ? ? ? ? ? ? ?
4 0.813 6 0.926 7 0.578 0 1 ? ? ? ? ? ? ? ?
5 0.858 7 0.624 2 0.491 0 0.805 5 1 ? ? ? ? ? ? ?
6 0.395 4 0.657 4 0.967 1 0.632 6 0.443 5 1 ? ? ? ? ? ?
7 0.745 6 0.639 7 0.589 6 0.828 6 0.964 9 0.564 4 1 ? ? ? ? ?
8 0.396 9 0.666 1 0.809 3 0.566 6 0.348 6 0.921 2 0.462 8 1 ? ? ? ?
9 0.736 6 0.885 9 0.793 8 0.946 0 0.787 1 0.833 6 0.851 0 0.750 2 1 ? ? ?
10 0.824 9 0.599 0 0.498 3 0.816 3 0.988 3 0.440 7 0.964 1 0.315 4 0.793 9 1 ? ?
11 0.860 3 0.645 3 0.448 4 0.833 3 0.980 3 0.434 0 0.959 1 0.384 6 0.801 1 0.979 4 1 ?
12 0.827 0 0.654 4 0.358 8 0.828 3 0.939 2 0.382 6 0.934 4 0.386 7 0.772 8 0.933 4 0.983 2 1
Tab.4 Cosine ratio of granules obtained from different PSFBG batches
批次 IP/% IPP IGC
　1）注：*表示数值在可接受范围内
1 33.33 4.78 4.56
2 50.00 4.85 4.63
3 50.00 4.78 4.57
4 50.00 4.84 4.62
5 66.67*1） 6.17* 5.89*
6 25.00 3.90 3.72
7 75.00* 6.19* 5.91*
8 25.00 2.64 2.52
9 50.00 5.03 4.81
10 75.00* 7.22* 6.90*
11 75.00* 6.47* 6.18*
12 50.00* 5.94* 5.67*
Tab.5 Compression characteristic parameters of granules obtained from different PSFBG batches
Fig.4 Score scatter plot of granules obtained from twelve PSFBG batches
Fig.5 Loading scatter plot of granules obtained from twelve PSFBG batches
Fig.6 Contribution rate of different physical properties of granules to P1 and P2
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