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This paper aims to enhance the effectiveness of risk management in the entire vehicle development process. Based on a Sino-foreign cooperative entire vehicle research and development project, the study analyzes the characteristics of the low-voltage harness in vehicles, identifies and categorizes risk factors, and utilizes fault tree analysis to model the causal relationships of various risks. These relationships are then mapped into a Bayesian Network (BN). By employing the fuzzy set theory, collected expert opinions are transformed into prior and conditional probabilities of node events, establishing a risk assessment model for vehicle low-voltage harness development based on fault tree-Bayesian network. This model quantifies the probability and impact of risk factors. For key and sensitive risk factors, corresponding risk response strategies are proposed, providing effective risk management for harness development.

, authors=Wanting Zhang^{1, 2}, authorsList=Wanting Zhang, authorCompany=null, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1309639597957677559, articleId=1309639597374669300, tenantId=1146029695717560320, journalId=1189645257101713411, language=CN, title=基于故障树与贝叶斯网络的汽车线束开发风险管理, columnId=1309639589879444032, journalTitle=汽车文摘, columnName=自动驾驶技术专题, runingTitle=null, highlight=null, articleAbstract=

为提升整车开发过程中风险管理效能，以中外合作整车研发项目为背景，分析汽车低压线束的特点，并进行风险因素的识别及分类。利用故障树分析法，对风险的因果关系进行建模，将其映射成贝叶斯网络（BN），借助模糊集理论，将采集的专家意见转化为节点事件的先验概率和条件概率，构建起基于故障树-贝叶斯网络的整车低压线束开发风险评估模型，对风险因素发生概率和影响程度进行量化分析，针对关键风险因素和敏感风险因素，提出相应的风险应对策略，为线束开发提供有效的风险管理。

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