Attribute Measurement System Analysis Vendor Invoices Cost Data Integrity Project Purpose
Need to make sure that our operating definitions are rock solid and no variation gets introduced based on how we are measuring things. For example, if two different people measure the same thing and they come up with two different answers, then we have some degree of variation introduced through bias and we want to measure only real variation. So it is important to evaluate or gage two things: 1. Repeatability - If the same person measures the same thing, do they still get the same answer? 2. Reproducibility - If someone else measures the same thing, do they get the same answer the first person got? Note: You may see this referred to as "Gage R & R". Here are a few more tips to keep in mind:
- If physical equipment or instruments are involved in measurement readings, make sure the equipment is properly calibrated to ensure accuracy. - People who do the measuring should be well versed in the process and follow a documented step by step procedure. - Methods, materials, and even the environment can impact the readings. You want a typical or usual environment that is representative of how the process really works. - Over time, you want to have a stable environment. Plotting natural variations using X & R Charts is recommended Step 1 - Select at least two observers or appraisers to participate in the Measurement System Analysis: Name of Observers / Appraisers 1.1 Sherry Minzer 1.2 Robert Bowers 1.3 Jamin Musului 1.4 1.5 1.6 In order to measure repeatability, each person should make at least two trial runs. Indicate the number of trail runs each person will take:
Step 2 - Establish an acceptable criteria regarding if the measurement passes of fails: 2.1 Percent that must be in Agreement > 95% 2.2 Confidence Level in Results > 95% 2.3 Indicate the number of measurements to be taken >
20
Step 3 - Select the units to be measured, have each observer measure the unit in random order, repeat the process according to the number of trial runs, and tabulate the results in the table below: Observ No. 1 2 3 4 5 6 7 8 Sherry Minzer Trial 2 Trial 3 2 3 2 4 4 2 0 2 Robert Bowers Trial 2 Trial 3 2 3 2 4 4 4 1 2
Trial 1 2 3 2 4 4 2 0 2
Trial 4
Trial 1 2 3 2 4 4 4 1 2
9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
3 5 4 3 2 2 3 6 4 5 3 2
3 5 3 3 2 2 3 5 4 5 3 2
3 5 3 3 2 2 3 6 4 4 3 2
3 5 3 3 2 2 3 6 4 4 3 2
Step 4 - Determine the Degree of Agreement in the Data Observations per Each Trial in Agreement by Observer Observ Observ Observ Observ No. 1.1 1.2 1.3 1 1 1 1 2 1 1 1 3 1 1 1 4 1 1 1 5 1 1 1 6 1 1 1 7 1 1 1 8 1 1 1 9 1 1 1 10 1 1 0 11 0 1 1 12 1 1 1 13 1 1 1 14 1 1 1 15 1 1 1 16 0 1 1 17 1 1 1 18 1 1 1 19 1 1 1 20 1 1 1 21 22 23 24
Observ 1.4
Observ 1.5
Observations in Agreement Betwee Observ No. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
25 26 27 28 29 30 Total Agreements
25 26 27 28 29 30 18 20 19
uced based on how we are ome up with two different answers, nly real variation. So it is
the same answer? same answer the first person got?
make sure the equipment
w a documented step by step
want a typical or usual environment
using X & R Charts is recommended.
nt System Analysis:
epeatability, each person should l runs. Indicate the number of 2
ndom order, repeat the process
Trial 4
Trial 1 2 3 2 4 4 4 1 2
Jamin Musului Trial 2 Trial 3 2 3 2 4 4 4 1 2
0 Trial 4 Trial 1 Trial 2 Trial 3 Trial 4
3 5 3 3 2 2 3 5 4 4 3 2
3 4 3 3 2 2 3 5 4 4 3 2
Observations in Agreement Between Observers Observ 1.1 vs: Observ 1.2 vs: 1.2 1.3 1.1 1.3 1 1 Col J 1 1 1 1 1 1 1 1 0 0 0 0 1 1 1 1 1 0 0 0 1 1 1 1 1 1 1 1 0 0 1 1 0 0 1 1 1 1
(May have to revise the tabulation below to fit the tabluation to the left) Observ 1.3 vs: 1.1 1.2 1 Col K Col M 1 1 1 1 1 1 1 1 0 1 1 1 1 1 0 1 1 1 1
15
14
0
18
0
0
0 Trial 1 Trial 2 Trial 3 Trial 4
it the tabluation to the left)
Attribute Measurement System Analysis Vendor Invoices Cost Data Integrity Project Repeatability Results
Were each of the observers able to repeat within our target of > Number in Observer / Appraiser No of Obs Agreement Sherry Minzer 20 18 Robert Bowers 20 20 Jamin Musului 20 19 0 20 0 20 95% Percent 90% 100% 95% 0% 0% Meets Target? No Yes Yes No No
Reproducibility Results
How well did each observer do in reproducing the same results as the other observers? Number in Meets Observer / Appraiser No of Obs Agreement Percent Target? Observ 1.1 vs: 1.2 20 15 75% No Observ 1.1 vs: 1.3 20 14 70% No Observ 1.2 vs: 1.3 20 18 90% No 20 0% No 20 0% No