posted 06 November 2000 03:58 AM               

An out-of-control Range chart indicates unstable repeatability (too much variation) and an out-of-control X-bar chart may mean that the instrument is due for calibration (bias).

A measurement process must be statistically under control (no special cause variations) for it to be used effectively to control the manufacturing process it measures. If there are no out-of-control signals, Standard Deviation can be estimated and compared with process standard deviation to determine suitability of the measurement process for the application.

Once the statistical stability is established, R&R study is then conducted to 'quantify various errors' in the measurement system. Based on these (r&r percentages), one can determine the suitability of the measurement system for a particular measurement application.

Quoting from MSA manual "...Without data-based knowledge of the state of control of a measurement process, figures of 'repeatability' , 'reproducibility', etc. are only descriptions of data obtained during the (r&r) study. They may have no meaning for future performance. Assessing the repeatability, reproducibility etc. of a measurement system for which the state of stability is unknown may cause more harm than good..."

posted 06 November 2000 07:58 PM               

STABILITY:

When considering the subject of stability in connection with measurement system, it becomes extremely important to differentiate between what is generally referred to as measurement system stability ----

a ) The amount of total variation in the systemâs bias over time on a given part or master part : Known as "Stability over Time"

and

statistical stability, the more general term which is applied to not only stability ,but to repeatability, bias, process in general., etc.

to understand the difference between the two stability, let us consider that there can be 2-measurement systems, measuring exactly the same master part, both of which demonstrate statistical stability, yet one system may have significantly higher variation in its bias over time than the other. From a statistical standpoint, they are equally stable. From a traditional gage stability stand point, the system with greater bias variations over time is considered less ã STABLE ã than the one with lower bias variation. ----------------- (page-21,chapter-2-section-2 )

Statistical properties of measurement systems :

The measurement system must be in statistical control. This means that variation in the measurement system is due to common causes only and not due to special causes. This can be referred to as statistical stability. ---------- (page-5, chapter ö1 , section-2 )

Quality of measurement data
The statistical properties most commonly used to characterize the quality of data are

Bias and Variance.
The property called bias refers to the location of the data relative to the master value and the property called variance refers to the spread of the data.
---------- ( page-3 , chapter-1,section-1)

specifically, the procedures assess the following statistical properties;

Repeatability, reproducibility, bias, stability, and linearity.

Collectively, the procedures are sometimes referred to as ãgage R&Rä procedures. ------------ (page-15,chapter-15,-section-1)
DOES THE GAGE R&R ASSESS THE SAID STATISTICAL PROPERTIES OTHER THAN REPEATABILITY & REPRODUCIBILITY. YES/NO.

If yes -------------- how

Analysis of results ---graphical analysis

Stability
From range chart stability is determined by: a point or points beyond the control limit ; within operator or within part patterns, ------- ( page-46 , chapter 2- section 4 )
linearity

the averages of the multiple readings by each appraiser on each part are plotted with the reference value or overall part average as the index. This plot can assist in determining :

linearity (if the reference value is used ) ------- (page-52, chapter 2-section4 )

CONCLUSION

GAGE R&R study is an apt exercise for statistical stability and if used, as said above all statistical properties are revealed. Like stability, linearity, repeatability & reproducibility. GRR should be done first and GRR values should be brought below 10% . This can be achieved by understanding the graphical representation and taking appropriate steps. By doing so we are achieving the "Statistical stability".

Without data öbased knowledge of the state of control of a measuring process, R&R figures are only descriptions of the data obtained during study. They have no meaning for future performance. Assessing the repeatability ,reproducibility, etc, of a measurement system for which the state of stability is unknown may cause more harm than good. When talking of measurement system statistical stability, the length of time a system is stable is often a major point of discussion. However by means of TIME STABILITY, the length of time a system is stable can be found by using x-bar r-bar control chart. This time stability is to be done after statistical stability in other words called gage R&R. Incase if time stability is performed prior to gage R&R the bias readings will not be exact as readings are contaminated with repeatability and, reproducibility errors.

Above all, any manufacturing process is supposed to be statistically stable if CP & CPK are controlled as they are representing spread & bias (centrality. ).The normal practice to control SPREAD first then to CPK the bias or centering OPN.

Similarly, we have to look at measurement system.

First control repeatability and reproducibility errors of SPREAD by doing gage R&R STUDY and then go to TIME STABILITY to know the extent of DRIFT OR BIAS the CPK.

the book reference r indicated in the brackets.

invite views on this

posted 07 November 2000 06:31 PM               

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