LENGTH: One Hour
Most quality professionals know the need for gage calibration, which ensures that the gage will return (on average) the dimensions of the standard that is used to calibrate it. Gage capability is meanwhile similar to process capability because it reflects the gage's ability to return the same measurement consistently for a given part. Gages must be capable as well as calibrated to do their jobs.
The two primary components of gage capability are repeatability, or the gage's ability to return consistent measurements by a single inspector, and reproducibility, or the ability of different inspectors to get the same results from a given part. Each element is measurable in terms of a variance or standard deviation, the less of which is better.
The gage itself can therefore be a variation source that affects (1) the quality of outgoing work, (2) statistical process control, and (3) estimates of process capability. If the gage variation is high, then measurements close to the specification limits become questionable; it is quite possible to accept parts that should be rejected and reject parts that should be accepted.
The effective standard deviation for control chart work meanwhile includes both the process and gage variation, which leads to wider control limits and reduced power (or longer average run lengths) to detect process shifts. If the gage variance is known, however, it can be separated analytically from the process variation to allow a relatively accurate computation of the process capability.
Two standard methods are available for gage R&R studies: the "long form" method that uses sample averages and ranges to estimate the reproducibility and repeatability components, and Analysis of Variance. Both can be performed in Microsoft Excel, and StatGraphics and Minitab also offer gage study functions.
What You Will Learn
Participants in this in-depth one-hour webinar will:
- Understand the difference between a calibrated (accurate) gage and a capable (precise) gage.
- Know the components of gage capability including repeatability and reproducibility.
- Understand other measurement system aspects such as linearity and bias.
- Recognize the effect of measurement system variability on outgoing quality, statistical process control, and process capability analysis.
- Know the procedure for performing a reproducibility and repeatability (R&R) analysis, and also software resources for this purpose.
- Know potential remedies for non-capable gages, such as measurement replication to deal with poor repeatability.
Viewers of the On-Demand webinar get:
- Unlimited viewing of the webinar for one full year, including any updated versions
William A. Levinson, P.E., is an ASQ Fellow, Certified Quality Engineer, Quality Auditor, Quality Manager, Reliability Engineer, and Six Sigma Black Belt. Levinson is also the author of several books on quality, productivity, and management. Henry Ford's Lean Vision is a comprehensive overview of the lean manufacturing and organizational management methods that Ford employed to achieve unprecedented bottom line results, and Beyond the Theory of Constraints describes how Ford's elimination of variation from material transfer and processing times allowed him to come close to running a balanced factory at full capacity. Statistical Process Control for Real-World Applications shows what to do when the process doesn't conform to the traditional bell curve assumption.
HOW DOES THIS ALL WORK?
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