论文标题
产品风险评估：贝叶斯网络方法
Product risk assessment: a Bayesian network approach
论文作者
论文摘要
产品风险评估是确定产品是否可以安全使用的产品（从类型的洗衣机到类型的泰迪熊）是否可以使用产品的总体过程。有几种用于产品风险评估的方法，包括Rapex，这是英国和欧盟监管机构使用的主要方法。但是，尽管它广泛使用，但我们确定了RAPEX的几个局限性，包括处理不确定性的有限方法以及无法纳入用于使用和解释测试数据的因果解释。相比之下，贝叶斯网络（BNS）是一种严格的，规范性的方法，用于建模不确定性和因果关系，这些方法已经用于医学和金融等领域的风险评估以及一般关键的系统。本文提出了BN模型，该模型为产品风险评估提供了改进的系统方法，该方法可以通过RAPEX解决确定的局限性。我们使用建议的方法来证明泰迪熊的风险评估以及没有测试数据的新的未经认证的水壶，并且产品实例的数量尚不清楚。我们表明，尽管我们可以复制Rapex方法的结果，但BN方法更强大，更灵活。
Product risk assessment is the overall process of determining whether a product, which could be anything from a type of washing machine to a type of teddy bear, is judged safe for consumers to use. There are several methods used for product risk assessment, including RAPEX, which is the primary method used by regulators in the UK and EU. However, despite its widespread use, we identify several limitations of RAPEX including a limited approach to handling uncertainty and the inability to incorporate causal explanations for using and interpreting test data. In contrast, Bayesian Networks (BNs) are a rigorous, normative method for modelling uncertainty and causality which are already used for risk assessment in domains such as medicine and finance, as well as critical systems generally. This article proposes a BN model that provides an improved systematic method for product risk assessment that resolves the identified limitations with RAPEX. We use our proposed method to demonstrate risk assessments for a teddy bear and a new uncertified kettle for which there is no testing data and the number of product instances is unknown. We show that, while we can replicate the results of the RAPEX method, the BN approach is more powerful and flexible.
