MSA R&R for training in manufacturing industry

MSA used in manufacturing industry

1. WELCOME TO MSA (R&R) TRAINING PROGRAM

2. Content History What is measurement system What is MSA Accuracy & Precision Bias Linearity Stability Repeatability Reproducibility NDC

3. History Developed by Big 3 (Ford, Chryslar & GM)- AIAG ( Automotive Industry Action Group) 1 st Edition issued in 1990 2 nd Edition issued in 1995 3 rd Edition issued in 2002 4 th Edition issued in 2010

4. Measurement System Measurement system is the collection of instruments or gauges, standards, operations, methods, fixtures, software, personnel, environment. Gage is any device used to obtain measurements,: frequently used to refer specifically to the devices used on the shop floor, includes go/ no go devices.

5. Properties of “GOOD” Measurement System Adequate discrimination & Sensitivity Variability of System is always under statistical control, i.e. variation must be only due to common causes Variability of measurement system is small compared to Manufacturing process variation and Tolerance

6. Types of VARIATION Variation – Normal / Chance Cause - Common / Natural Process - In control Un u s ua l / Abnor m a l Spe cial / A ssi g nab le Out of control

7. Common cause variation in a process The total variation in the observed variation is composed of two parts - Normal or chance and Abnormal or unusual. Normal variations are inherent to the process which are natural and it is generally uneconomical to find out the causes for it. Economically nothing can be done about it unless the whole process itself is changed which constitutes a fundamental change. Common causes refers to many sources of variation within a process that has a stable and repeatable distribution over time. If only common causes of variation are present and do not change, the output of a process is predictable.

8. Common cause variation Examples Unclear scope definition Inadequate design Poor management Insufficient procedures Weather conditions Temperature Humidity Computer response time Inadequate working conditions

9. Assignable cause variation in a process On the other hand unusual variations are external which can be always be traced and corrected, these causes can always be traced to the operating conditions of the processes and eliminated. These special causes ( Assignable ) refer to any factors causing variation that are not always acting on the process. Whenever they occur, they make the process distribution change. Unless all the assignable causes are identified and acted upon, they will continue to affect the process output in unpredictable ways.

10. Assignable cause variation Examples  Machine fault. • Power surges • Operator absent/ falls asleep • Computer fault.

11. What is Measurement System Analysis (MSA)? A measurement system analysis (MSA) is a specifically designed experiment that seeks to identify the components of variation in measurement The purpose of MSA is To asses the quality of a measurement system. To validate the consistency of inspectors. Provide methods for validation of measurement system

12. Why MSA? Objective of MSA is to To obtain information related to amount and type of variation associated with measurement system when the system is put into use. Used to know the percentage of measurement error incurred by an operator with relevant gauge for measuring part. Defect Prevention Statistics Data MSA IS MANDATORY PRIOR TO SPC

13. Measurement system errors Bias Linearity Stability Repeatability Reproducibility

14. Accuracy and Precision ACCURACY Closeness to reference or master value Required where two or more MS measuring a same characteristic Same parameters are checked at Suppliers end or at Customer end PRECISION Ability of MS to repeat the same reading Required where MS is repeatedly used to assess and adjust the process In process inspection

15. Accuracy and Precision Low Precision, High Precision, High Precision, Low Accuracy Low Accuracy High Accuracy .. . .. ... … . ... … . .. …. .. . .. … .. Accuracy is captured by: Bias, Linearity, Stability Precision is captured by: Repeatability, Reproducibility

16. Bias BIAS is the difference between the observed average of measurements and the reference value. Ref.Value BIAS Observed average

17. Bias A Part of reference value 6.00 is checked 15 times by one appraiser, who obtained following values: 5.80, 5.70, 5.90, 5.90, 6.00, 6.10, 6.00, 6.10, 6.40, 6.30, 6.00, 6.10, 6.20, 5.60, 6.00. Average = 6.0067. Hence Bias = 0.0067 .

18. Linearity Linearity is the difference in Bias values through the expected operating range of the Gauge. Linearity = Difference between Bias values over the operating range Lower Range Observed average Upper Range Ref.Value Non Linearity Gauge is measuring lower than true value at high end. Reference Value Measured Value

19. Stability Stability is the total variation in the measurements obtained with a measurement system on the same master or part and with same appraiser when measuring a single characteristic over an extended time period. Stability = Variation in measurement averages over a period of time. Time 1 Stability Observed average Time 2

20. Repeatability & Reproducibility Repeatability One Appraiser One Equipment Same part Several trials Reproducibility Same equipment Same Parts Several trials Different Appraiser This Variation is represented by Equipment This Variation is represented by Appraiser

21. Repeatability & Reproducibility (R&R) The Gauge R & R are often the major contributors of measurement variation. The evaluation of variations contributed by repeatability and reproducibility is called Gauge R and R Study.

22. Constitution of total variation Total variation Manufacturing process variation Part to part variation (PV) Within part variation (WIPV) Measurement system variation Appraiser variation (AV) Equipment variation (EV) Appraiser part interaction

23. Constitution of total variation Relation of R & R, PV and TV R&R EV AV R&R TV PV

24. How to conduct R&R Study Key factors for effective Gauge R & R study: Sample parts must be selected from process which represent its entire operating range. The appraisers chosen should be selected from those who normally operate the instrument. The measurements should be made in a random order. The instrument must have a discrimination that allows at least one tenth of the expected process variation to be measured.

25. Methods of GR&R Study Elements of Variation Range Method X bar & R Method ANOVA Method TV PV WIPV AV EV App & part interaction

26. Average and range method (X bar and R) No. of Samples 10 nos. Randomly selected representing actual process variation No. of Appraisers Min 2 preferably 3 from personnel actually performing on a day to day operation No. of trials Min 2 . Preferably 3

27. X bar and R method applicability To capture Precision, Mandatory before SPC study Measurement Systems which are used repeatedly on line to control the process based on the measurement data Where individual readings are affected by the precision of the instrument Applicable for all MS used in process where the MS can be repeated

28. Steps for conducting study: Identify the parts from 1 – 10 Mark the Place where to check to eliminate Within part variation Communicate the purpose of the study to all appraisers Conduct the study in a Random manner covering all parts for required no. of trials through all appraisers Monitor all appraisers are following the same method Record the observations in a manner which is not seen by the appraisers If any abnormal readings are observed ask the appraiser to repeat. Calculate EV,AV,PV & TV and it Percentage against TOL or TV and NDC

29. Calculations involved: Equipment Variation (EV) - Repeatability EV = R X K1 Appraiser Variation(AV) - Reproducibility   Trials K1 2 0.8862 3 0.5908 Appraisers K2 2 0.7071 3 0.5231 Parts K3 2 0.7071 3 0.5231 4 0.4467 5 0.403 6 0.3742 7 0.3534 8 0.3375 9 0.3249 10 0.3146 n = No. of part r = No. of trials X Diff = Min X – Max X X = Avg. of part readings R = Avg. of R R = Avg. of Ranges of part

30. Calculations involved: Repeatability & Reproducibility (R&R) R&R =   Total Variation (TV) TV =   Part Variation(PV) EV = X K3   = Range of part Average  

31. Calculations involved: Further calculation involves two methods, i.e. one against the Total Variation and other against the Tolerance . Against Total Variation Against Tolerance %EV = (EV/TV)100 %AV = (AV/TV)100 %GRR = (R&R/TV)100 %EV = (EV/TV)100 %AV = (AV/TV)100 %GRR = (R&R/TV)100 Here TV= Sigma. It can be calculated by  

32. Calculations involved: COMPARE AGAINST TOLERANCE WHEN TV IS MORE THAN TOLERANCE WHERE SPC IS NOT REQUIRED COMPARE AGAINST TOTAL VARIATION WHEN TV IS LESS THAN TOLERANCE WHERE SPC IS REQUIRED

33. X bar and R Acceptance criteria % R&R < 10 % OF TOL OR TV % R&R 10 – 30 % OF TOL OR TV ACCEPTABLE SUBJECT TO ANALYSIS AND JUSTIFICATION W.R.T COST OF REPAIR AND CRITICALITY No. of distinct data categories NDC > 5 where SPC is to be use NDC >2 where no SPC is not used

34. What is NDC ? NDC refers to No. of Distinct Data Categories NDC .represent the number of groups your measurement tool can distinguish from the data itself. When the number of categories is less than 2, the measurement system is of no value for controlling the process, since one part cannot be distinguished from another or we have not selected the part over entire range of process variation. When the number of categories is 2, the data can be divided into two groups, say high and low. When the number of categories is 3, the data can be divided into 3 groups, say low, middle and high

35. Importance of NDC ? NDC = 1 Acceptable for control only when process variation is small compared to specs. Unacceptable for analysis. NDC = 2 to 4 Suitable for controls with semi-variable techniques (say p-chart). Provide only coarse estimates. Hence not acceptable for estimating process indices and parameters.

36. Importance of NDC ? NDC = 5 and above Acceptable for control as well analysis. Can be used with variable control charts (Ex. X Bar-R Chart). Recommended.

37. Importance of NDC ? But why minimum 5 Data Categories ? 5.15 Standard Deviation covers 99 % of the process distribution. The Measurement System should be able to discriminate values at least between each Sigma value for SPC. Each segment (coloured in dark blue to light blue) represents one standard deviation away from the mean. For example, 2σ means two standard deviations from the mean

38. Actions on R&R Value If Repeatability is large compared to Reproducibility, look for following causes: 1. The Instrument needs maintenance 2. The gauge is probably not calibrated properly 3. The clamping or location for gauging need to be improved If Reproducibility is large compared to Repeatability, look for following causes: 1. The Appraiser(s) may require more training 2. Calibrations on the gauge / instrument dial not clear 3. A fixture of some sort may be required to help the appraisers to use the gauge more consistently.