The seminar begins with an examination of the fundamental vocabulary and concepts related to metrology. Topics include: accuracy, precision, calibration, and "uncertainty ratios".
The seminar ends with an explanation of how to combine all relevant uncertainty information into an "Uncertainty Budget" that helps determine the appropriate width of QC specification intervals (i.e., "guard-banded specifications").
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Webinar On Statistical analysis of gages
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Webinar Description:
Webinar On Statistical Analysis of Gages
Product Id FDB1272
Category Food, Drugs & Biologics
Scheduled On Thursday, September 25, 2014 at 13:00 Hrs
Duration 60 Minutes
Speaker John N. Zorich
he seminar begins with an examination of the fundamental vocabulary and concepts related to
metrology. Topics include: accuracy, precision, calibration, and "uncertainty ratios". Several of
the standard methods for analyzing measurement variation are then described and explained,
as derived from AIAG's Measurement System Analysis reference book. The methods include:
Gage R&R (ANOVA method, for 3 gages, 3 persons, 3 replicates, and 10 parts), Gage Correlation
(for 3 gages), Gage Linearity, and Gage Bias.
he seminar ends with an explanation of how to combine all relevant uncertainty information
into an "Uncertainty Budget" that helps determine the appropriate width of QC specification
intervals (i.e., "guard-banded specifications"). Spreadsheets are used to demonstrate how to
perform the methods described during the seminar.
All manufacturing and development companies perform testing and/or inspection that involves
measurements of products, components, and/or raw materials. The output of those
measurements is compared to design or QC specifications, to determine whether or not the
measurements "pass" those specifications.
However, all measurement processes have some inherent variability; that is, a given
measurement will likely not be exactly equal to the true value, because of variation from a
number of different sources. Some of those sources are: person to person, equipment to
equipment, time to time, and calibration to calibration.
2. How much trust to place in a given measurement can be quantified by determining
the magnitude of each of those sources; in effect, the larger the uncertainty of the
measurement (i.e., the greater the measurement variation, in comparison to the size
of the design or QC specification interval), the lower the trust that should be placed in
a given measurement.
If the measurement uncertainty can be quantified, it can be applied to reduce the
width of the design/QC specifications, so that the resulting "guard banded"
specifications can be used without concern for measurement variation.
Areas Covered in the Session :
Fundamental Vocabulary & Concepts
Gage R&R (ANOVA method)
Gage Correlation
Gage Linearity
Gage Bias
Uncertainty Budgets and Guard-banded Specifications
Who will benefit:
QA/QC Supervisor
Process Engineer
Manufacturing Engineer
QC/QC Technician
Manufacturing Technician
R&D Engineer
Speaker Profile:
3. John Zorich has spent 35 years in the medical device manufacturing industry; the
first 20 years were as a "regular" employee in the areas of R&D, Manufacturing,
QA/QC, and Regulatory; the last 15 years were as consultant in the areas of QA/QC
and Statistics. His consulting clients in the area of statistics have included numerous
start-ups as well as large corporations such as Boston Scientific, Novellus, and
Siemens Medical.
His experience as an instructor in statistics includes having given 3-day
workshop/seminars for the past several years at Ohlone College (San Jose CA), 1-day
training workshops in SPC for Silicon Valley Polytechnic Institute (San Jose CA) for
several years, several 3-day courses for ASQ Biomedical, numerous seminars at ASQ
meetings and conferences, and half-day seminars for numerous private clients.
He creates and sells formally-validated statistical application spreadsheets that have
been purchased by more than 75 companies, world-wide.
To register visit https://compliancetrainings.com/SiteEngine/ProductDetailView.aspx?id=FDB1272