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A Hierarchical Assessment Method using Bayesian Network for Material RiskDetection on Green Supply Chain

机译:一种使用贝叶斯网络对绿色供应链物资风险的分层评估方法

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Today's social awareness of environmental protection presents the electronic companies with an irreversible trend towards green manufacturing. It raises harsh requirement for the sourcing process and imposes unprecedented pressure to the QA system, majorly due to the risk of hazardous material. As QA procedures are becoming more complicated for coping with increasing material risk and meanwhile the time and resource available are tightly constrained, the development of an effective mechanism for material testing turns up to be a critical issue. In this study, a hierarchical material risk assessment approach is proposed based on FMEA framework. Taking into account the risk occurrence, the difficulty in detection and the severity the risk causes, it enables companies to estimate their material risks dynamically using Bayesian network. With its help, companies can assess and prioritize the material risk in a systematic and efficient manner which will drive QA towards a more high-performance process.
机译:今天,环境保护的社会意识介绍了绿色制造业的不可逆转趋势的电子公司。它提高了对采购过程的恶劣要求,并对QA系统施加前所未有的压力,主要是由于有害物质的风险。由于QA程序正变得更加复杂,因为应对材料风险的增加,同时有效地受到严格限制的时间和资源,有效的物料测试机制的发展成为一个关键问题。在本研究中,基于FMEA框架提出了一种分层材料风险评估方法。考虑到风险发生,检测难度和风险原因的严重性,它使公司能够使用贝叶斯网络动态地估计其材料风险。通过帮助,公司可以以系统和有效的方式评估和优先考虑物质风险,这将推动QA更高性能的过程。

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