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Setting appropriate fill weight targets -A statistical engineering case study

机译：设定适当的填充重量目标-统计工程案例研究

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摘要

Purpose: To present a case study of the development of a solution of a high-level need for setting required targets for a product filling processes. Summary: Companies producing products are legally obligated to provide a net content declaration on packaging to provide fair weights and measures. Governments around the world are interested in both the mean and the variance of the fill weight distribution to ensure that the company provides at least the declared content weight. For the sake of simplicity, the case study uses the US regulations, though Procter & Gamble (P&G) follows such regulations in the countries they serve. One method to ensure correct content is to weigh every packet and make up for any shortfalls. This is not practical in an industrial operations scenario. Another method is to consider the weight from the filling process as following a probability distribution. However, it is practically seen that lot-to-lot variation also plays an important role in deciding the weight of the content. Hence, P&G was exploring the possibility of a new model to assess the capability of their filling processes against the regulatory and corporate requirements. This article presents how statistical engineering was used to develop a new model to overcome this complex problem for which no known solution was available.
机译：目的：提供一个案例研究，该案例开发了为产品灌装过程设定所需目标的高层次解决方案。简介：生产产品的公司有法律义务在包装上提供净含量声明，以提供合理的重量和度量。全世界的政府都对填充重量分布的均值和方差感兴趣，以确保公司至少提供声明的内容重量。为了简单起见，该案例研究使用美国法规，尽管宝洁（P＆G）在其服务的国家/地区遵循此类法规。确保内容正确的一种方法是称量每个数据包并弥补任何不足。在工业操作方案中，这是不切实际的。另一种方法是按照概率分布来考虑来自填充过程的权重。但是，实际上可以看出，批次间的差异在确定内容物的重量方面也起着重要作用。因此，宝洁正在探索一种新模型的可能性，以根据法规和公司要求评估其灌装过程的能力。本文介绍了如何使用统计工程来开发新模型来克服这一复杂问题，而目前尚无已知的解决方案。

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