测量的定义是对某具体事物赋予数字(数值),以表示它们对于特定特殊性之间的关系。测量系统是一个过程(如: Fig-1),过程的输入包括所有和测量相关的因素:量具、人员、材料、测量方法、环境;过程的输出为产品的测量值。
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[url=https://insevent.instrument.com.cn/t/jp]<font color=)
上面的过程输入的各个因素都会导致一个测量系统的变异;MSA是评估一个测量系统好坏的常用手段,其中GRR是一个重要的指标,判断标准参考如下(Fig-2 & Fig-3)。
![](https://ng1.17img.cn/bbsfiles/images/2024/03/202403061458465502_1103_2942222_3.png)
![](https://ng1.17img.cn/bbsfiles/images/2023/08/202308011326332938_6117_2942222_3.jpg!w597x462.jpg)
![](https://ng1.17img.cn/bbsfiles/images/2024/03/202403061458467311_1776_2942222_3.png)
![](https://ng1.17img.cn/bbsfiles/images/2023/08/202308011326500906_435_2942222_3.jpg!w576x396.jpg)
测量系统包括非破坏性和破坏性测量系统,很多化学和颗粒方面的测量系统因为样品属于破坏性测量系统。破坏性测量系统因为样品不能重复使用,所以研究破坏性测量系统会比非破坏性测量系统麻烦点。
破坏性测量系统因为样品已经受到破坏,无法进行重复测量,无法评估样品的重复性和再现性。所以在进行破坏性测量系统研究时需进行如下假设(Fig-4):
![](https://ng1.17img.cn/bbsfiles/images/2024/03/202403061458476831_4135_2942222_3.png)
![](https://ng1.17img.cn/bbsfiles/images/2023/08/202308011327115159_9183_2942222_3.jpg!w616x341.jpg)
采样方案解决之后就制定样品的采样计划和测试计划,划出Gan图((Fig-5)),按计划执行。
![](https://ng1.17img.cn/bbsfiles/images/2023/08/202308011327537469_7208_2942222_3.jpg!w690x245.jpg)
![](https://ng1.17img.cn/bbsfiles/images/2024/03/202403061458481661_4746_2942222_3.png)
开始收集数据,并使用Minitab 去进行计算GRR指标的计算。因为Minitab对数据的要求不一样,使用Excel收集的数据需要处理到Minitab可以使用的模式(Fig-6)。
![](https://ng1.17img.cn/bbsfiles/images/2024/03/202403061458482218_4655_2942222_3.png)
![](https://ng1.17img.cn/bbsfiles/images/2023/08/202308011328092026_1599_2942222_3.jpg!w548x335.jpg)
使用Minitab计算的操作步骤参考如下(Fig-7),按步骤操作之后就可以得出GRR的各个指标。
![](https://ng1.17img.cn/bbsfiles/images/2024/03/202403061458485718_9540_2942222_3.png)
![](https://ng1.17img.cn/bbsfiles/images/2023/08/202308011328222694_1400_2942222_3.jpg!w690x394.jpg)
通过Minitab的操作,可以直接得出各个指标如下(Fig-8)。参考各个指标的判断标准,可以得出该测试系统是可以接受的。
![](https://ng1.17img.cn/bbsfiles/images/2024/03/202403061458490937_2387_2942222_3.png)
![](https://ng1.17img.cn/bbsfiles/images/2023/08/202308011328511276_3409_2942222_3.jpg!w690x352.jpg)