Inference of product quality by using RFID-enabled traceability information a study on the US pharmaceutical supply chain

T. Inaba
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引用次数: 9

Abstract

We present a stochastic model to infer a product quality index by using product traceability information. We propose a model by using Bayesian Network and apply it to the US pharmaceutical supply chain where regulations to mandate exchanging of traceability information for individual prescription drugs are being studied. In supply chains where traceability information of only a few products is available, consumers simply take the quality of products with traceability information is higher than those without traceability information. But when traceability information of many products becomes available, consumers need to understand the difference and choose the products that have a suitable quality for them. Our model can be used in this situation. We show that our model successfully differentiate product quality indices by using a numerical study with a hypothetical scenario.
通过使用rfid可追溯性信息推断产品质量——对美国制药供应链的研究
我们提出了一个利用产品可追溯性信息来推断产品质量指标的随机模型。我们通过使用贝叶斯网络提出了一个模型,并将其应用于美国制药供应链,其中正在研究强制交换个人处方药可追溯性信息的法规。在只有少数产品可追溯信息的供应链中,消费者简单地认为有可追溯信息的产品质量高于没有可追溯信息的产品。但是,当许多产品的可追溯性信息可用时,消费者需要了解其中的差异,并选择适合自己质量的产品。我们的模型可以用于这种情况。我们表明,我们的模型成功区分产品质量指标通过使用一个数值研究与一个假设的场景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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