Measurement uncertainty and optimized conformance assessment
Measurement uncertainty and optimized conformance assessment
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DOI：
10.1016/j.measurement.2006.04.007
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发表时间：
2006-11-01
期刊：
影响因子：
5.6
通讯作者：
Forbes, Alistair B.
中科院分区：
文献类型：
--
作者：
Forbes, Alistair B.
本文讨论了通过测量来评估产品是否符合其规格。给定测量数据和产品规格，必须做出有限数量的选择，例如，接受产品，用更精确的测量系统重新测量产品，重新设计产品，拒绝产品等。承认测量信息只提供了关于真实产品特性的部分信息，我们需要决策规则，以最大限度地利用测量数据，并最大限度地减少与做出错误决策相关的负面后果。在本文中，我们应用贝叶斯决策方法进行符合性评估，使用损失函数来量化错误决策的成本，并推导出最佳的决策规则，使预期损失最小化。一个重要的方面是，与测量系统相关的未知系统效应的存在对预期损失的行为有重大影响。皇冠版权所有（c）2006年出版的爱思唯尔有限公司保留所有权利。
This paper is concerned with the assessment from measurements of whether or not a product meets its specification. Given measurement data and a product specification, a finite number of choices have to be made, e.g., accept the product, re-measure the product with a more accurate measuring system, re-engineer the product, reject the product, etc. Acknowledging that the measurement information provides only partial information about the true product characteristics, we require decision rules that make best use of the measurement data and minimise the negative consequences associated with making a wrong decision. In this paper we apply Bayesian decision-making approaches to conformity assessment, using a loss function to quantify the cost of wrong decisions and deriving optimal decision rules that minimise the expected loss. One important aspect is that the presence of unknown systematic effects associated with the measurement system has a significant influence on the behaviour of the expected loss. Crown Copyright (c) 2006 Published by Elsevier Ltd. All rights reserved.