Measurement System Analysis (GR used as an estimate of short-term measurement variation.Master ValueGood RepeatabilityPoor Repeatabilitysss s2 2 2 2totalproductrepeatabilityreproducibility=+ +Precision: ReproducibilityReproducibility: The variation that results when different conditions areused to make the same measurements Different operators Different set-ups Different test units Different environmental conditions Long-term measurement variation Estimated by the standard deviation of the averages of measurements from different measurement conditionsInspector AMaster ValueInspector BInspector CMachine AMachine BMachine CPrecision: ReproducibilityReproducibility: The standard deviation of the averages of the measurements made by different persons, machines, tools, etc. when measuring the identical characteristic on the same partExample: Accuracy vs PrecisionSuppose we have a reference material with a true hardness of 5.0. Method 1 gives the following readings: 3.8, 4.4, 4.2, 4.0 Method 2 gives the following readings: 6.5, 4.0, 3.2, 6.3Which method is more accurate?Which method is more precise?Which method do you prefer? Why?The number of decimal places that can be measured by the system. Increments of measure should be at least one-tenth of the width of the product specification or process variation.Discrimination (Resolution)12Which ruler should be used to measure parts for the process represented by the distribution above ?Measurement System Variance: s2meas = s2repeat + s2reprod Primary output of analytical Gage R&RTo determine whether the measurement system is “good” or “bad” for a certain application, you need to compare the measurement variation to the product spec or the process variation Comparing s2meas with Tolerance: Precision-to-Tolerance Ratio (P/T) Comparing s2meas with Process Variation (P/TV): % Repeatability and Reproducibility (%R&R) Discrimination IndexMeasurement System Metrics Precision to Tolerance Ratio Addresses what percent of the Tolerance is taken up by measurement error. 5.15 smeas represents 99% of all measurements Best case: Make Patterned Data Simple Set of Numbers (for each input)Step 4: Ask the first operator to measure all the samples once in random order. Blind sampling, in which the operator does not know the identity of each part should be used to reduce human bias.The Method - Calculating Gage CapabilityStep 5: Have the second operator measure all the samples once in random order and continue until all operators have measured the samples once (this is trial 1)Step 6: Repeat steps 4 & 5 for the required number of trials. It is best if these measurements can be done over several days.Step 7: Enter the data and tolerance information into Minitab Stat Quality Tools Gage R&R StudyStat Quality Tools Gage Run ChartStep 8: Analyze the results by assessing the quality of the measurement system based on the guidelines on the following page. Determine follow-up actions.MSA Sample Guidelines Usually 10 samples, 2-4 operators (if several operators use the gauge), 2-3 trials Depending on the purpose of the study 1 or more gages will be included In general select enough samples so that number of samples x number of operators/gages 15SAMPLE SELECTION Option 1: if process variability is unknown, the samples selected should be representative of the normal process/product variation (to get TV) Option 2: if process variability is known, the samples selected should uniformly span beyond the width of the specs*Example: MinitabStep 1: Randomly select 10 samples. In addition, identify the operators who use this instrument daily. (Parts 1 through 10 were collected and three operators were identified). Step 2: Calibrate the gage or verify the last calibration date is valid.Use Calc Make Patterned Data Simple Set of NumberslStep 3: Setup the Minitab data collection sheet for the R&R study. Create the R&R data collection sheet for 10 parts each measured 2 times by 3 operators Column headings: Column 1: Part ID (1-10) Column 2: Operator (1-3) Column 3: Trial (1-2) Column 4: Measurement(s)Step 4: Ask the first operator to measure all the samples once in random order. Blind sampling, in which the operator does not know the identity of each part should be used to reduce human bias.Step 5: Have the second operator measure all the samples once in random order and continue until all operators have measured the samples once (this is trial 1).Step 6: Repeat steps 4 & 5 for the required number of trials.(We assume the above steps were executed. See filename GageR&R.mtw.) Example - Gage R&R using MinitabANOVA method is preferred.Step 7: Enter the data and tolerance information into Minitab. Stat Quality Tools Gage R&R StudyFN: GageR&R.mtwExample - Gage R&R using MinitabEnter Gage Info and Options (see next page)totalmeastotalmeasTVPssss= 22 /Step 7: Enter