title: [Reliability theory based on quality risk network analysis for Chinese medicine injection].
abstract: A new risk analysis method based upon reliability theory was introduced in this paper for the quality risk management of Chinese medicine injection manufacturing plants. The risk events including both cause and effect ones were derived in the framework as nodes with a Bayesian network analysis approach. It thus transforms the risk analysis results from failure mode and effect analysis (FMEA) into a Bayesian network platform. With its structure and parameters determined, the network can be used to evaluate the system reliability quantitatively with probabilistic analytical appraoches. Using network analysis tools such as GeNie and AgenaRisk, we are able to find the nodes that are most critical to influence the system reliability. The importance of each node to the system can be quantitatively evaluated by calculating the effect of the node on the overall risk, and minimization plan can be determined accordingly to reduce their influences and improve the system reliability. Using the Shengmai injection manufacturing plant of SZYY Ltd as a user case, we analyzed the quality risk with both static FMEA analysis and dynamic Bayesian Network analysis. The potential risk factors for the quality of Shengmai injection manufacturing were identified with the network analysis platform. Quality assurance actions were further defined to reduce the risk and improve the product quality.
authors.forename: Zheng
authors.initials: Z
authors.lastname: Li
authors.forename: Li-Yuan
authors.initials: LY
authors.lastname: Kang
authors.forename: Xiao-Hui
authors.initials: XH
authors.lastname: Fan
mesh_terms: D004365:Drugs, Chinese Herbal / Q000008:administration & dosage / Q000737:chemistry* / Q000592:standards*; D008516:Medicine, Chinese Traditional / Q000592:standards*; D011786:Quality Control; D015203:Reproducibility of Results; D018570:Risk Assessment
chemical_list: D004365:Drugs, Chinese Herbal