duy ngoc

Thank you very much for your information. I really appreciate that you spend your time for my problem. I'd like to explain my real case for example: We use measurement system 1 to evaluate our product. After some years, we upgrade our measurement system with new software (reduce cycle time - measurement system 2) and we want to compare the different between measurement system 1 and 2. Hear is the method: 1. we measure golden sample by measurement system 1 to find reference value , the reference value is 98 2. We measure golden sample by measurement system 2 to find bias (MSA method from AIAG), the reference value is 98.7, standard deviation is 0.65. After using hypothesis test, we see that hypothesis was rejected, that mean two measurement system has bias and need to calibrate. But the specification of product is from 93 to 103, so we see that is, with respect to the specification limits, the potential to make the wrong decision about the part exists only when the measurement system error intersects the specification limits, and this is not in this case (we measure 100 sample to see distribution and calculate Cpk >1.3--> the distribution capability is far away from specification limit). So we continue using new measurement system although fail hypothesis test. Is it correct ? If not, can you give me better solution in this case ?

Hello Team, [Measurement system analysis-AIAG] In Bias, we just compare measured value with reference value to see significant different by hypothesis test, but I think bias must be compared to product specification for better evaluation (like GRR value). In some case, the bias is large (hypothesis fail) but the specification is too high (Ex: bias/specification < 10%) so can we accept bias in this case ? Regards, Duy