Tahirawan77
Involved In Discussions
Hi,
I would like to perform a Gage R&R study where the data type is 'Ordinal' in nature. The defect can be categorized as No defect, Low, Medium and High
The process in question is drilling of holes in composite material. After the drilling process there is risk of making a 'splinter' at the edge of hole. The size of the splinter can vary from 'No splinter' to Low, Medium and High splinter. I cannot / do not want to measure the splinter size as this is not measured in the production due to time constraints. Instead each hole is inspected visually by QC inspector and rated as one of the above category. Low Splinter will not be reworked, any Medium splinter will be reworked where as High will be rejected.
I would like to plan the study as Attribute Gauge R&R study with 30 holes where holes with 'No Splinter' is marked as 'Good' and all other form of splintering can be categorized as 'Fail'. But by doing so I will miss the ability of the operators to identify different defect types (medium defect identified as High and vice versa).
I would like to know if there is any other way how I can perform the study where the data type is 'Ordinal' or any other suggestions to improve the Gage R&R study
Thanks
I would like to perform a Gage R&R study where the data type is 'Ordinal' in nature. The defect can be categorized as No defect, Low, Medium and High
The process in question is drilling of holes in composite material. After the drilling process there is risk of making a 'splinter' at the edge of hole. The size of the splinter can vary from 'No splinter' to Low, Medium and High splinter. I cannot / do not want to measure the splinter size as this is not measured in the production due to time constraints. Instead each hole is inspected visually by QC inspector and rated as one of the above category. Low Splinter will not be reworked, any Medium splinter will be reworked where as High will be rejected.
I would like to plan the study as Attribute Gauge R&R study with 30 holes where holes with 'No Splinter' is marked as 'Good' and all other form of splintering can be categorized as 'Fail'. But by doing so I will miss the ability of the operators to identify different defect types (medium defect identified as High and vice versa).
I would like to know if there is any other way how I can perform the study where the data type is 'Ordinal' or any other suggestions to improve the Gage R&R study
Thanks