Application of FMEA and Bayesian Network in Risk Assessment of Fluidized Bed Granulation of Traditional Chinese Medicine

Hai-ning ZHAO; Ya-jing WANG; Li-na SHANG; Meng-nan ZHOU; Yi ZHANG; Hui-shu SHI; Ya-nan WANG; Jin-ling LI

doi:10.13422/j.cnki.syfjx.20191049

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Application of FMEA and Bayesian Network in Risk Assessment of Fluidized Bed Granulation of Traditional Chinese Medicine

Pharmacy and Processing | 更新时间：2021-02-09

- Application of FMEA and Bayesian Network in Risk Assessment of Fluidized Bed Granulation of Traditional Chinese Medicine
- Chinese Journal of Experimental Traditional Medical Formulae Vol. 25, Issue 20, Pages: 100-108(2019)
- 作者机构：
  
  天津中医药大学　现代中药发现与制剂技术教育部工程研究中心，天津　 301617
- 作者简介：
- 基金信息：
- DOI：10.13422/j.cnki.syfjx.20191049
  CLC： R22; R28; R94; C37
- Received：16 November 2018，
  
  Published Online：29 January 2019，
  
  Published：20 October 2019
- 稿件说明：
移动端阅览
Hai-ning ZHAO, Ya-jing WANG, Li-na SHANG, et al. Application of FMEA and Bayesian Network in Risk Assessment of Fluidized Bed Granulation of Traditional Chinese Medicine[J]. Chinese journal of experimental traditional medical formulae, 2019, 25(20): 100-108.
DOI：

Hai-ning ZHAO, Ya-jing WANG, Li-na SHANG, et al. Application of FMEA and Bayesian Network in Risk Assessment of Fluidized Bed Granulation of Traditional Chinese Medicine[J]. Chinese journal of experimental traditional medical formulae, 2019, 25(20): 100-108. DOI： 10.13422/j.cnki.syfjx.20191049.

摘要

目的：

运用失效模式与影响分析(FMEA)及贝叶斯网络(BN)对影响中药流化床制粒过程中的因素进行风险评估，以有效控制风险因素，提升产品质量。

方法：

通过FMEA对流化床制粒过程进行风险分析，然后将筛选出的中风险和高风险因素作为主要控制点并建立相应的BN，运用敏感性分析筛选出影响颗粒流动性、粒度均匀性、溶化性及产品洁净度的主要风险因素，并以颗粒质量不合格为证据确定各风险因素的发生概率，最后以三叶片流化床制粒过程为例，将FMEA与BN结合应用到其风险评估过程中，验证该方法的有效性和可靠性。

结果：

在通过FMEA筛选出流化床工艺、原料粒径、原料含水量和吸湿性、投药量、黏合剂浓度和加入量、捕集袋清洗程度和完整性、喷嘴位置等风险点的基础上构建了具有因果关系的流化床制粒风险网络，其中原料吸湿性、黏合剂浓度及加入量、进口温度和雾化压力为大概率风险因素，发生概率分别为55%，63%，59%和58%；根据贝叶斯风险关系网络控制三叶片流化床制粒分析结果显示，在影响因素与颗粒粒度均匀性的回归模型中，进口温度、雾化压力及黏合剂浓度的

分别为0.003 4，0.032 6，0.041 8，表明三者与颗粒质量间均具有较大的相关性，与FMEA-BN方法得出的结论基本一致。

结论：

FMEA和BN相结合对流化床制粒进行可视化风险评估有助于对制粒过程中的风险因素进行有效控制，降低产品质量风险，为中药制粒工艺的改进和完善提供有力支持。

Abstract

Objective:

To carry out the risk assessment on the factors in the process of granulation fluidized bed of traditional Chinese medicine(TCM) by using failure model and effect analysis(FMEA) and Bayesian network(BN)

in order to effectively control risk factors and improve product quality.

Method:

The risk analysis of the fluidized bed granulation process was carried out by FMEA and the selected medium risk and high risk factors were taken as the main control points

the corresponding BN was established. The sensitivity analysis was used to screen out the main risk factors affecting particle fluidity

particle size uniformity

solubility and product cleanliness

the occurrence probability of each risk factor was determined by the evidence of unqualified particle quality

finally

taking fluidized bed granulation process of Sanye tablets as an example

the FMEA and BN were combined into the risk assessment process to verify the effectiveness and reliability of the method.

Result:

Based on the middle and high risk points of fluidized bed process

particle size of raw materials

moisture content and hygroscopicity of raw materials

dosage

concentration and addition amount of binder

cleaning degree and integrity of collection bag

and nozzle position

which were selected by FMEA

a fluidized bed granulation risk network with causality was constructed. Among them

hygroscopicity of raw materials

concentration and addition amount of binder

inlet temperature and atomization pressure were high probability risk factors

and the probability of occurrence were 55%

63%

59%and 58%

respectively. According to the Bayesian risk relationship network which controlled Sanye tablets fluidized bed granulation analysis results showed that the

values of inlet temperature

atomization pressure and concentration of binder were 0.003 4

0.032 6 and 0.041 8

respectively in the regression model of influencing factors and particle size uniformity

indicating that there was a significant correlation between the three factors and the particle quality

which was basically consistent with the conclusion obtained by FMEA-BN method.

Conclusion:

The combination of FMEA and BN for visualized risk assessment of fluidized bed granulation helps to effectively control the risk factors in the granulation process

reduce product quality risks and provide strong support for the improvement of granulation process of TCM.

关键词

Keywords

references

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