权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

MUKOM - Cost-efficient determination of the measurement uncertainty of complex measurement processes

MUKOM - 经济高效地确定复杂测量过程的测量不确定度

基本信息

批准号：
388678238
负责人：
Professor Dr.-Ing. Robert Schmitt
金额：
--
依托单位：
Forschungsbereich Fertigungsmeßtechnik und Qualitätsmanagement
依托单位国家：
德国
项目类别：
Research Grants
财政年份：
2017
资助国家：
德国
起止时间：
2016-12-31 至 2019-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/388678238?language=en
关键词：
MUKOM Cost efficient determination measurement

项目摘要

The result of every measurement is impaired with an uncertainty. Because of this measurement uncertainty, the inspection of conformity can result in a faulty test decision with two consequences. Either good parts are scrapped or malfunctioning parts are delivered to the customers. In order to make sure that the test decision is correct, it is necessary to know the uncertainty of the measurement process. Right now and with the currently available procedures, it is already possible to determine the measurement uncertainty for a large amount of measurement processes. However, this remains a challenge for measurement processes, for which there are no standardized metrological models applicable. These can be summarized under the term complex measurement processes. Examples are hardness testing, inspections with large amounts of influencing quantities or inspections with inhomogeneities in the material. Nevertheless, there is a verifiable need in research and the industry for such a procedure. The goal of this research project is therefor to develop a procedure for the estimation of the measurement uncertainty for complex inspection processes. The procedure qualifies the user to identify relevant influence quantities, model complex inspection processes, include knowledge from experts into the modeling. Compared to the conventional procedures, the newly developed procedure will use an innovative approach, which combines the analytical modeling in accordance to the scientifically accepted GUM (Guide to the Expression of Uncertainty in Measurement) and the deduction of meta models from experimental data. Due to this, one can benefit from the advantages of the exact system modeling based on previous knowledge and the experimental modeling using systematic tests.

每项计量之结果均因不确定性而减值。由于这种测量不确定性，合格性检查可能导致错误的测试决策，并产生两种后果。好的部件被报废，或者故障部件被交付给客户。为了确保测试决策的正确性，有必要了解测量过程的不确定度。现在，利用现有的程序，已经可以确定大量测量过程的测量不确定度。然而，这仍然是一个挑战的测量过程中，有没有标准化的可应用的模型。这些可以概括为复杂的测量过程。例如硬度测试、具有大量影响量的检查或材料不均匀性的检查。然而，在研究和工业中确实需要这样一种程序。因此，本研究项目的目标是开发一个程序，用于复杂的检测过程中的测量不确定度的估计。该程序使用户能够识别相关影响量，对复杂的检测过程进行建模，并将专家的知识纳入建模。与传统的方法相比，新开发的方法将使用一种创新的方法，该方法将根据科学公认的GUM（测量不确定度表达指南）的分析建模与从实验数据中推导元模型相结合。由于这一点，人们可以受益于基于先前知识的精确系统建模和使用系统测试的实验建模的优点。