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[Reliability theory based on quality risk network analysis for Chinese medicine injection]
Summary
This study introduces a novel Bayesian network approach for quality risk management in Chinese medicine injection manufacturing. This method quantitatively identifies critical risk factors, enabling targeted actions to enhance product quality and system reliability.
Area of Science:
- Reliability theory and Bayesian networks applied to pharmaceutical manufacturing.
- Quality risk management in the context of traditional Chinese medicine production.
Context:
- Chinese medicine injection manufacturing plants face complex quality risks.
- Existing methods like Failure Mode and Effect Analysis (FMEA) have limitations in dynamic risk assessment.
Purpose:
- To introduce a new risk analysis method based on reliability theory for quality risk management.
- To transform FMEA results into a dynamic Bayesian network for quantitative risk evaluation.
- To identify critical risk factors and inform quality assurance actions.
Summary:
- A novel risk analysis method integrates reliability theory and Bayesian networks for Chinese medicine injection manufacturing.
- Risk events are modeled as nodes in a Bayesian network, allowing quantitative assessment of system reliability.
- The method was applied to a Shengmai injection manufacturing case, identifying key risk factors and guiding quality improvement strategies.
Impact:
- Enables quantitative evaluation of system reliability and identification of critical risk nodes.
- Facilitates the development of targeted minimization plans to reduce risks.
- Aims to improve overall product quality and manufacturing process reliability in the pharmaceutical industry.
