Hi,
I want to perform a study to calculate the 'probability of correctly detecting a defect size'. The defect is 'wrinkle size' and it varies from 0 to 0.2. The defects are classified into three different categories, Low wrinkle (less than 0.10), Medium wrinkle (between 0.1  0.15) and High wrinkle (0.15  2.0). The defects are classified visually by operator by looking at a the 'scan result picture'. The object of the study is to estimate 'The probabiliy of detecting a Low wrinkle is xx with a confidence interval of yy and the probability of detecting a medium wrinkle is yy with a confidance interval of zz and so forth. (see attached picture)
For this purpose i plan to take 10 samples of each defect category Low, medium and High. They will be classified by a better measurement system and then a operator will be asked to classify each sample into different defect size. I want to know how to calculate the probability from this data, Is this the right appraoch or should i perform a GR&R instead?
I want to perform a study to calculate the 'probability of correctly detecting a defect size'. The defect is 'wrinkle size' and it varies from 0 to 0.2. The defects are classified into three different categories, Low wrinkle (less than 0.10), Medium wrinkle (between 0.1  0.15) and High wrinkle (0.15  2.0). The defects are classified visually by operator by looking at a the 'scan result picture'. The object of the study is to estimate 'The probabiliy of detecting a Low wrinkle is xx with a confidence interval of yy and the probability of detecting a medium wrinkle is yy with a confidance interval of zz and so forth. (see attached picture)
For this purpose i plan to take 10 samples of each defect category Low, medium and High. They will be classified by a better measurement system and then a operator will be asked to classify each sample into different defect size. I want to know how to calculate the probability from this data, Is this the right appraoch or should i perform a GR&R instead?
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