# Metrology: Statistical Analysis of Measurement Uncertainty

## The webinar gives an explanation of Statistical Analysis of Measurement Uncertainty in metrology. It will explain accuracy, precision, calibration, and "uncertainty ratios". It will describe the Gage R&R, Gage Correlation, Gage Linearity, and the Gage Bias methods.

Instructor:
John N. Zorich
Duration:
90 Minutes
Product Id:
502879
Access:
6 months

Price Details
\$190 Recorded
\$390 Corporate Recorded
Price Detail Options
Overview:

The webinar 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. The webinar 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 webinar.

Why should you Attend: 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. 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
John N. Zorich has spent almost 40 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 next 15 years were as a consultant in the areas of QA/QC and Statistics. These last few years were as a trainer and consultant in the area of Applied Statistics only. 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 applied statistics includes having given annual 3-day seminars for many years at Ohlone College (San Jose CA), and previously having given that same course for several years for Silicon Valley ASQ Biomedical. He's given numerous statistical seminars at ASQ meetings and conferences. And he creates and sells validated statistical software programs that have been purchased by more than 110 companies, world-wide.