Measurement System(MSA)
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Measurement System Analysis (MSA)



Measurement system analysis (MSA) uses scientific tools to determine the amount of total variation is from the measurement system. An objective method to assess the validity of a measurement system and minimize these factors that could excessively contribute to the variation in the data.


Confirm that the measurement used to collect the data is valid. Goal is to quantify the equipment/process variation and appraiser variation and the total measurement system variation.

The following areas components of measurement error needs to be studied and quantified before establishing capability of a process making decisions from the data.


    This is often a very time consuming component of the project and can slow the team’s quick progression through the process.

    Continue to focus on low hanging fruit that may be momentum sustainers and work vigorously through the MSA process. Most of this can be done by the GB/BB outside of the team meetings and results shared with them when complete.

    Accuracy / Bias

    The difference from the true value and the value from the measurement system. Accuracy represents the closeness to a defined target. Precision is different than accuracy and is covered in Gage R&R under Repeatability.

    For best accuracy of the data:

    1) Accept all data as it is collected. Assigning special cause and scrutinizing the data can come later.

    2) Record the data at the time it occurs.

    3) Avoid rounding off the data, record it as it is.

    4) On the data collection plan, record as many details around the data such as the exact source, machine, operator, conditions, collector’s name, material, gage, and time. Record legibly and carefully.

    The data should be screened for misplaced decimal points, duplicate data entries by mistake or improper recording procedure, missing date points if frequency is important, and other obvious non-representative data.

    5) Verify the gage is accurate. If using a weigh scale, verify it with a known and calibrated weight. Use gage blocks for calipers or micrometers. Use hardness blocks to verify hardness testers.


    Resolution / Discrimination

    The goal is to have at least 5 distinct values or categories of readings.

    Adhere to the 10-bucket rule. If your measurement system requires measurements to the hundredths (x.xx), then divide that by 10. Collect and record the data to the nearest thousandths ( The measurement system shall be sensitive to change and capable of detecting change.

    The lack of resolution will not allow a measurement system detect change. If you are measuring the downtime and using measurement to the nearest hour and most downtime is less than an hour then most of the reading will either be a 0 (for 0 hours) or a 1 (for 1 hour).

    However, using a stop watch and recording data to the nearest minute will provide 60x more resolution and allow better distribution of data points, more variety of data, with fewer repeat measurements. You could have 60 different readings. Actually recording the nearest 6 minutes would satisfy the 10-bucket rule, but it is a guide to help ensure resolution in the measurement system.

    This part of the MSA is usually the easiest to fix such as finding a micrometer, caliper, hardness tester that can capably read to the next nearest decimal.


    Try acquiring a larger samples size, with the idea that some of these may create new observations or measurements.

    Measure to as much resolution as possible and practical.


    When gathering data only collect with the acceptable limits where there is proven linearity. This is a test to examine the performance of the measurement system throughout the range of measurements. For example, does the bathroom scale perform the same when weighing a pet of 10 lbs to a man of 250 lbs?


    Stability of a measurement system is analyzed using control charts. Ensuring the measurements taken by appraiser(s) for the process is stable and consistent over time.

    SPC Charts use a variety of tests to determine stability. Many software programs will have these as options to include when analyzing data and will even indicate the point(s) and test that each failed.

    Some of the corrective measures once again include Standard Operating Procedures. Each appraiser should measure the same way every time over a long period of time and each appraiser should measure the same way as all the others. Recall that special causes can also occur with the process control limits and these must be given corrective action before proceeding to validate the measurement system.

    Gage R&R

    Variable Gage R&R

    In a variable Gage R&R there are generally two to three operators appraisers with 5-10 process outputs measured by each appraiser. Each process output is measured 2-3 times by each operator.Depending on the cost and time involved you can add more appraisers and measurements and replications.

    When performing the replicated appraisals it is critical that the measurement are randomized so that no patterns or predictability can be entered in by the appraiser. This bias will mislead the team and create a useless Gage R&R.

    For example, an appraiser may remember the 7th part that was measured was borderline and made a decision to give it one measurement. He/she may have spend a lot of time of that part and if the 2nd round of measurements are not randomized, that person will remember the measurement (appraisal) they gave it on the first round.

    So, move the parts around each repeat set of measurements. However, the parts must be indentified so the person entering the data into the statistical software enters the reading under the correct part.

    Four Criteria in Variable Gage R&R

    The following four areas will be asssessed. A statisical software program will produce these values once the data is properly entered. The GB/BB will be responsible for finding these values and determining whether each passes and if the entire measurement system is adequate to determine process capability. Process capability can not be determined with reliablity if the measurements (the data) is suspect.

    1) % Study Variation is based on standard deviation
    2) % Tolerance is based on USL and LSL
    3) % Contribution is based on variance
    4) The number of distinct categories based on process variation

    Ideally, all four categories should be in the GREEN zone. Examining the visual aids below shows commonly used judgement criteria for each category.

    Variable Gage R&R Criteria

    2) % Tolerance

    Shown below is an example of a % TOLERANCE calculation. In this case we are using 3 appraisers measuring 6 different parts.

    This study shows the measurement error as a percent of tolerance in short period of time. It oncludes both repeatability and reproducibility, can not be separated.

    5.15 Study Variation = 99% (constant)

    The TOP TABLE at the top is a part of the d2 distribution. This value is a constant that is found by looking at the column with 3 appraisers and going across with the row with 6 parts. In this example the d2 value is 1.73.

    The LOWER TABLE shows that actual measurements that each of the appraisers cam up with using their variable gage. The range of the three measurements for each part is shown on the right. Then the average range is shown (=0.69) and this is carried on to the Gage Error formula.

    Calculating % Tolerance in Variable Gage R&R study

    To convert this gage error of 2.05 to a percentage of tolerance multiply by 100 and divide by the process tolerance for the analysis.

    The process tolerance is the difference in the specification limits. For example, if the USL is 27 and the LSL is 2, then the tolerance is 25.

    With the tolerance being 25, then:

    Referring back to the RED/YELLOW/GREEN criteria display for % TOLERANCE, it shown that 8.2% is a passing value and this part of the Variable Gage R&R is successful.

    Ability of one appraiser to get the same result and another appraiser or the ability of all appraisers to get the same results AMONG each other.

    To optimize reproducibility in ATTRIBUTE Gage R&R:

    1) Create visual aids, templates, definitions, or other specific criteria for each to meet a certain rating, value, or appraisal. Pictures of good, bad, in the middle, and colors, will help each appraiser standardize their response, improving the reproducibility.

    Note: If these corrective actions are needed to pass the Gage R&R, it should be instituted as a formal work instruction and everyone involved throughout the company or plant should adhere to same instructions.

    To optimize reproducibility in VARIABLE Gage R&R:

    1) Create a Standard Operating Procedure with visual aids and definitions. When using humanly subjective "touch" devices such as micrometers and calipers it is important that all appraisers "squeeze" the same amount. Too little or much pressure at higher levels of resolution can be enough to alter the Gage R&R.

    2) Visual aids also help. Even when using an optical comparator to get a higher resolute data point there is subjectivity where to place the template or the starting and end point(s) on the shadow. Pictures of acceptable and non-acceptable will help reduce this variation.


    This describes the ability for an appraiser to repeat his/her measurements each time when analyzing the same part, unit, etc. In destructive testing (such as tensile testing) these reading will not be possible and some statistical software programs have options to select for destructive testing.

    The goal is to have an appraiser repeat unit readings at least three times. The person administering the test should randomize the sequence each time to prevent and patterns and bias (the appraiser may remember or try to remember what a measurement was and tend to alter real measurements to get the Gage R&R to pass). It is important for the administrator to record carefully to ensure readings correlate the correct part/unit each time.

    Avoid writing down measurements and then typing them into a statistical program. The fewer times measurements are recorded and copied the lower the risk for human error to add even more variation and possibly fail (or pass) the Gage R&R when it shouldn't have.

    Precision is the ability to have the same repetitive result (or appraisal in this case). Visually, it means that all your shots of an arrow are very close to one another. It does not mean that they are near the bulls eye. In other words, it does not mean that your shots are accurate.

    If your shots are accurate and precise, then they are tight circle centered around the target. It is also possible to be somewhat accurate without being precise. You may have several shots all around the bulls eys (target) but they may be scattered around it. If you take a look at the group the center (mean) may be the bulls eye but the shots are not in control or precise. In others words, there is a lot of unpredictability or variation.



    Measurement System Analysis Components


    A measurement system has five components:

    BIAS - also referred to as Accuracy, is a measure of the distance between the average value of the measurements and the "True" or "Actual" value of the sample or part.

    Linearity - Linearity is the bias throughout complete operating range of the gage. All gages have bias and we want that bias to be linear. This allows us to know what the bias is at any point in the gages range.

    For example, if a car's speedometer is off by 0.5 MPH at 35 MPH and off by 1.0 MPH at 65 MPH the speedometer's bias is NOT linear.

    Stability - Stability is how long the gage can maintain its acceptable operating status under normal conditions of use. The stability factor gives us a yardstick for determining how often a gage needs to be checked and possibly calibrated.

    Repeatability - assesses whether the same appraiser can measure the same part/sample multiple times with the same measurement device and get the same value. Repeatability is the amount of variation the appraiser/gage operator contributes to the overall error.

    Reproducibility - assesses whether different appraisers can measure the same part/sample with the same measurement device and get the same value. Reproducibility is the amount of variation the gage contributes to the overall error.

    Reproducibility, by default, will also contain some error from repeatability because of the gage user taking the measurements. This repeatability can be removed statistically resulting a more accurate reproducibility factor.


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