MSA Reference Manual, Fourth Edition Now Available - June 2010

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D

debyang

#32
Jim, thanks.

After reviewing that document, the bias calculation change seems to be the major one. Does anyone know why AIAG get rid of the d2* and go back to the basic statistic? Why d2* is no good for bias estimation any more? (Actually, I like this change, because I never figure out why d2* is used in the first place.)
 
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Tim Alcock

#34
Hi.. I've updated the comparison of the changes between V3 and V4 on the excel-world website (under technical info tab) if you would like to download it.
 
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allenlee

#35
Hi, it was disappointing to get V4 and find that it made no mention of what has changed from V3 to V4. There is a comparison of the two documents on Excel world uk website. I can send copies if required. No attempt is made to interpret the consequences of the changes, only the major differences. I hope that this will save others time in performing the same task and prompt some discussion. Regards, Tim
Thanks! So disppointed -- Doc control require to identify the change history, however, the international standards don't follow ...;)
 

MasterBB

Involved In Discussions
#38
New MSA Reference Manual: More Clarity, Better Organization

Here's a quick review of improvements made to the newly released Fourth Edition of the MSA Reference Manual.
– By Michael Down


Data and measurement impact all aspects of every industry. Manufacturing, assembly, retail, services, construction, labs, etc., all require review and analysis of data, followed by action that is taken on the basis of that information.

Although it is normally assumed that a measurement device is accurate, reliable, and giving high quality data, in many cases this is not only untrue, but many of the perceived problems may be due to the measurement system itself.

Changes to the MSA reference manual
Several editions of the Measurement System Analysis (MSA) Reference Manual have been released. In general, all issues that were identified by customers over the last few years are addressed in this Fourth Edition. The major areas of change are:

Additional examples to aid in the understanding of basic measurement system fundamentals;
Improvements to the organization of the manual and the table of contents;
Clarification of the relationship between calibration and MSA;
Clearer definition of the measurement decision (5-10-30);
Improved the bias and linearity sections;
Clarified and improved the attribute and the non-replicable (i.e., destructive) testing section.


These changes have helped to make the manual an asset in the understanding of measurement systems and the use of those systems to improve quality and services. The new version of the manual is now available at AIAG.

Purpose of MSA
The Measurement System Analysis (MSA) manual, one of the GM, Ford, and Chrysler reference manuals offered through the AIAG, is a reference manual wherein methodologies and principles are recommended, but not mandated. OEM's expect organizations will meet the intent of MSA in relation to measurement systems that are used in the manufacturing and assembly of supplier parts and subsystems.

Organizational improvements
One of the most important roles of a reference document is to provide a clear understanding of the subject. Improvements have been made in the usability of the MSA manual. For example, the table of contents is reformatted and structured to improve the reader's ability to find a specific subject. Some of chapters have been moved and combined to aid in the flow of material.



Relationship between Calibration and MSA
Another key improvement is the addition of information showing the relationship between the measurement system on the floor and how it tracks back to the National Measurement Institute Standards. This standardization helps to connect all who measure to a single source and reduces variation which could cause measurement errors. Measure Assurance Programs or MAPs, which keep measurement devices calibrated to the standards, are also discussed.

In general, several elements are present that can impact measurement results. For example, when taking blood pressure, the result is affected by the operator taking the measurement, the device itself, the patient, the environment, etc. The calibration method is used to verify that a measurement device can measure the characteristic within the specified design range. Normally, a "check" standard or "reference" value is used to validate the measurement device on a regular or annual basis.

5-10-30 Rule
The section of the manual discussing how to determine the minimum acceptable GRR (Gage Repeatability and Reproducibility, a statistical measure of the precision of a measurement system), has been expanded and includes clear guidelines for the decision making process. The four areas covered are:

Assembly error
Fixture error (should always be checked prior to any changes or improvements to the measurement system)
Location error
Width error (which includes the following table)
GRR Decision Comments
Under 10 percent Generally considered to be an acceptable measurement system. Recommended; especially useful when trying to sort or classify parts or when tightened process control is required.
10 percent to 30 percent May be acceptable for some applications Decision should be based upon, for example, importance of application measurement, cost of measurement device, cost of rework or repair.
Should be approved by the customer.
Over 30 percent Considered to be unacceptable Every effort should be made to improve the measurement system. This condition may be addressed by the use of an appropriate measurement strategy, for example, using the average result of several readings of the same part characteristic in order to reduce final measurement variation.



It is also pointed out that this information should not be used to establish threshold values for GRR. Each measurement situation requires review based on its own applications and merits.

Improvement to Bias and Linearity Sections
Some basic improvements have been made to the Bias and Linearity section of the manual. Calculations have been updated to use standard deviation instead of range, which was used in the past because the calculations were done manually. Since computers are used most of the time, standard deviation is a more robust value.
As a reminder:

Bias: the difference between the true value (reference value) and the observed average of measurements on the same characteristic on the same part.


Linearity: The difference of bias throughout the expected operating (measurement) range of the equipment is called linearity. Linearity can be thought of as a change of bias with respect to size. This is critical to understand in relation to linearity. Linearity can be thought of as a change of bias with respect to size.
Bias and linearity both include an evaluation or repeatability. The bias and linearity are useless if the repeatability is not acceptable.

GRR and the Target Pp
The explanation of how the target Pp (process performance index) is used has been clarified in this new release of the MSA manual. There are four different approaches to determine the process variation for measure acceptability:

Process Variation (Preferred Method) – Process variation takes on the parts in the GRR Study itself. Use when the selected sample represents the expected process variation. This would be a planned sample, instead of a random sample, to make sure the process variation is represented in the sample.
Surrogate Process Variation – When sufficient samples from the targeted process are not available, but samples can be taken from an existing process with similar variation.
Specification Tolerance – This method can be used when the measurement system is to be used to sort the process and the process has a Pp less then 1.0.
Pp (or Ppk) Target Value – When a sufficient sample to represent, the process variation is not available and an existing process variation is not available, or the new process is expected to have less variation then an existing process.
Improvements to the Attribute Section
Improvements have been made to the attribute section to help in its application, including clarification and additional examples on the use of this methodology:

Definition of cross tabs is improved, with examples of their use in the hypothesis test method.
Sample size for attribute gauging analysis has been clarified.
In the signal detection approach, the table creation was clarified, its origin identified, and step-by-step instructions with enhanced tables and graphics provided.
Improvements to the Non-Replicable section
Time was spent improving the information and locating the analysis for non-replicable measurement, or the case when multiple measurements cannot be taken on the same part or it is impossible to measure the same part or system multiple times. In addition, the index in the front has been improved and multiple gauging examples are identified.

Conclusion
The committees hope the improvements to the manual will aid in its use and application in the field.
 

bobdoering

Stop X-bar/R Madness!!
Trusted Information Resource
#39
I attended the AIAG 4th Ed. MSA rollout session, and have some additions to Michael Down's statement above.

First, it's good to go and hear right from the "horse's mouth" what their thinking is - you will never get that from a MSA trainer. To me, it was worth it.

Here are some notes - most from comments from the speakers:

-MSA book is specified as a “guidance document”, not a requirement like the PPAP book
-If you write into your procedures that the MSA is your procedure, then it becomes auditable.
-If your customers identify it as a “requirement” it becomes one

-Bias is a big deal - it will create disagreement between customer and supplier

-Linearity and Bias need to be checked over the entire range of use.

-(My note: ) Their Conformity Assessment Risk diagram shows clearly why the shop floor should never run to 100% of the tolerance - just based on gaging issues.

-If you have a part at specification, you will reject the part 50% of the time in the gage error "gray area"

-Concerning ndc - the basis for the minimum of 5 was based on a histogram should have at least 5 bars to be useful (My note: after cringing at that comment, and at the note in their chart that a ndc of 5 was useful for variable charting, I asked the speaker Greg Gruska of Omnex during the break that if you have an ndc of 5 in a control chart, that you only have 2 1/2 statistically meaningful divisions between the mean and the control limits. He agreed. I asked, doesn't that make the data too "chunky" to be really useful? He agreed. I told him I recommend ndc 10 minimum for charting - 5 on either side of the mean - to be meaningful, and he had not argument with that logic.)

-Engineering needs to understand measurement systems to design for measurement (my note: it is a subset of design for manufacturability - people just don't recognize that typically)

-Save samples from previous prototype runs to try to collect product characteristic variation to test on the gage

-They stated that if a process is stable and capable (and there has been no customer complaints) that there may be no need to do a gage study. Process variation includes the measurement variation. (my note: Of course this is a simplistic an absurd statement. Without a gage R&R, you have no evidence to trust the previous data used to make the conclusion that the process was stable and capable. There may have been terrible resolution that makes it look capable when it is not. Do not take this advice. We have discussed this in other threads.)

-When looking at the Gage R&R result charts:
R Chart – should be in control by appraiser
X-bar chart – should be 50% out of control
Variation by appraiser should be flat
Is 40% GR&R bad? It depends!

-They had a very interesting analysis of gaging of true position, using the bivariate form and MANOVA.

-For Gage R (Appendix D), the question was asked concerning the statement in bold "This method CANNOT be used for final gage acceptance without other more complete and detailed MSA methods". What were these "other methods"? Patrice White-Johnson (Ford) answered that for her suppliers she expects linearity and bias studies need to be completed. (my note: That issue is obliquely mentioned in Appendix D in terms of "Linearity and bias are not issues".)

-The goal of the Attribute Gage R&R is to study the "gray area" around the measurement decision - not to prove it can detect the obvious pass and fail parts. Anybody can pass that...
 
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