Webinar On Process Capability Analysis using Confidence/Reliability Calculations

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Webinar On Webinar On Process Capability Analysis
using Confidence/Reliability Calculations


Presented By John N. Zorich
Thursday, April 9, 2015 at 1300 Hrs
Hosting By Compliance Trainings
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Process Capability Analysis using
Confidence/Reliability Calculations
Product Id
MD1277
Category
Medical Devices
Scheduled On
Thursday, April 9, 2015 at 1300 Hrs
Duration
90 Minutes
Speaker
John N. Zorich
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Webinar Description
All manufacturing and development companies
perform testing and/or inspections that involve
concluding whether or not a product or lot is
acceptable vs. design or QC specifications. Such
test/inspections may occur during design
verification/validation or during incoming or
final QC. The most informative method for
analyzing the data that results from such
activities is the calculation of the product's or
lot's "reliability" at a chosen "confidence"
level (where "reliability" means
"in-specification"). Such a method produces
information that is more valuable than simply
that the given product or lot "passed" (as is the
case when "AQL Attribute Sampling Plans" are
used) or a in-specification statement without
any corresponding confidence statement (as is the
case with AQL Variables Sampling Plans and with
Process Capability calculations). The output of
a "Confidence/Reliability" calculation is a
definitive statement that the given product or
lot has a specific in-specification, which
conclusion we can state with a specific level of
confidence (e.g., 95 confidence of 99
reliability, or 90 confident of 93
reliability").
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Areas Covered in the Session

• The seminar begins with a discussion of relevant
  regulatory requirements, as motivation for
  calculating "confidence/reliability". Then, some
  vocabulary and basic concepts are discussed.
• Next, detailed descriptions are given for how to
  calculate confidence/reliability for data that is
  either pass/fail (i.e., "attribute" data),
  normally-distributed measurement data,
  non-normally distributed measurement data that
  can be transformed into normality, or
  non-normally distributed measurement data that
  cannot be transformed into normality.
   Spreadsheets are shown as examples of how to
  implement the methods described in the seminar. A
  final discussion is provided on how to introduce
  the methods into a company.
• All the above is captured in these bullet points
• Regulatory Requirements
• Vocabulary and Concepts
• Attribute Data
• Normal Data
• Normal Probability Plotting 
• Non-Normal Data that can be normalized
• Reliability Plotting (for data that cannot be
  normalized) 
• Implementation Recommendations

Who will Benefit

• A must attend webinar for all
• QA / QC Supervisors
• Process Engineers
• Manufacturing Enginee
• QA / QC Technicians
• Manufacturing Technicians
• RD Engineers

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Speaker Profile
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 RD,
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.
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