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Instructor : Steven Wachs 
Product Id : 50007

Overview: Design Validation should ensure that product performance, quality, and reliability requirements are met. Design Validation should ensure that product performance, quality, and reliability requirements are met.

In order to have high confidence that products will perform as intended, enough data must be collected and analyzed using various statistical methods.

Selecting appropriate sample sizes often vexes many practitioners. Testing only a few units does not provide a high level of confidence that performance requirements will be consistently met. Testing too many units may be unnecessarily expensive and can lead to misleading conclusions.

Statistical Methods are typically used to ensure that product performance, quality, and reliability requirements are met during the Design Validation phase of product development.

This webinar discusses common elements of sample size determination and several specific sample size applications for various design validation activities including Reliability Demonstration/Estimation, Acceptance Sampling, and Hypothesis Testing. Numerous examples are provided to illustrate the key concepts and applications.
Steven Wachs has 25 years of wide-ranging industry experience in both technical and management positions. He has worked as a statistician at Ford Motor Company where he has extensive experience in the development of statistical models, reliability analysis, designed experimentation, and statistical process control.

Mr. Wachs is currently a Principal Statistician at Integral Concepts, Inc. where he assists manufacturers in the application of statistical methods to reduce variation and improve quality and productivity. He also possesses expertise in the application of reliability methods to achieve robust and reliable products as well as estimate and reduce warranty. Mr. Wachs regularly speaks at industry conferences and provides workshops in industrial statistical methods worldwide.

He has an M.A. in Applied Statistics from the University of Michigan, an M.B.A, Katz Graduate School of Business from the University of Pittsburgh, 1992, and a B.S., Mechanical Engineering from the University of Michigan.
Instructor : John N. Zorich
Product Id : 50007

Overview: This webinar explains the logic behind sample-size choice for several statistical methods that are commonly used in verification or validation efforts, and how to express a valid statistical justification for a chosen sample size.

This webinar explains the logic behind sample-size choice for several statistical methods that are commonly used in verification or validation efforts, and how to express a valid statistical justification for a chosen sample size.

The statistical methods discussed during the webinar include the following:

  • Confidence intervals
  • Process Control Charts
  • Process Capability Indices
  • Confidence / Reliability Calculations
  • MTBF Studies ("Mean Time Between Failures" of electronic equipment)
  • QC Sampling Plans
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.
Instructor : John N. Zorich
Product Id : 50007

Overview: This webinar explains how to choose and justify a sample-size for Lots that are included in Process Validation studies.

This webinar explains how to choose and justify a sample-size for Lots that are included in Process Validation studies.

The statistical methods discussed during the webinar include the following:

  • Confidence intervals
  • Confidence / Reliability Calculations (for variables & attributes)

It then explains how to analyze those samples in such a way that they provide statistically valid final %Reliability for the production Process itself. One example is worked through completely.

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.