The 2-day seminar explains how to apply statistics to manage risks and verify/validate processes in R&\;D\, QA/QC\, and Manufacturi ng\, with examples derived mainly from the medical device design/manufactu ring industry. The flow of topics over the 2 days is as follows:

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Almost all design and/or m anufacturing companies evaluate product and processes either to manage ris ks\, to validate processes\, to establish product/process specifications\, to QC to such specifications\, and/or to monitor compliance to such speci fications.

\n\nThe various statistical methods used to support such activities can be intimidating. If used incorrectly or inappropriately\, s tatistical methods can result in new products being launched that should h ave been kept in R&\;D\; or\, conversely\, new products not being launc hed that\, if analyzed correctly\, would have met all requirements. In QC\ , mistakenly chosen sample sizes and inappropriate statistical methods may result in purchased product being rejected that should have passed\, and vice-versa.

\n\nThis seminar provides a practical approach to unders tanding how to interpret and use more than just a standard tool-box of sta tistical methods\; topics include: Confidence intervals\, t-tests\, Normal K-tables\, Normality tests\, Confidence/reliability calculations\, Reliab ility plotting (for extremely non-normal data)\, AQL sampling plans\, Metr ology (i.e.\, statistical analysis of measurement uncertainty )\, and Stat istical Process Control. Without a clear understanding and correct impleme ntation of such methods\, a company risks not only significantly increasin g its complaint rates\, scrap rates\, and time-to-market\, but also risks significantly reducing its product and service quality\, its customer sati sfaction levels\, and its profit margins.

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- FDA\, ISO 9001/13485\, and MDD require ments related to statistical methods \n
- How to apply statistical m ethods to manage product-related risks to patient\, doctor\, and the desig ning/manufacturing company \n
- Design Control processes (verificati on\, validation\, risk management\, design input) \n
- QA/QC process es (sampling plans\, monitoring of validated processes\, setting of QC spe cifications\, evaluation of measurement equipment) \n
- Manufacturin g processes (process validation\, equipment qualification) \n

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- QA/QC Supervisor \n < li>Process Engineer\n
- Manufacturing Engineer \n
- QC/QC Tec hnician \n
- Manufacturing Technician \n
- R&\;D Engineer\n

Lecture 1:\n

**Regu
latory Requirements**

Lecture 2:\n

**Vocabular
y and Concepts**

Lecture 3:\n

**Confidence Int
ervals (attribute and variables data)**

Lecture 4:\n

**Normality Tests and Normality Transformations**

Lecture 5:\n

**Statistical Process Control (with focus on XbarR
charts)**

Lecture 6:\n

**Confidence/Reliabili
ty calculations for Proportions**

Lecture 7:\n

Lecture 8:\n

**Process Capability Indi
ces calculations(Cp\, Cpk\, Pp\, Ppk)**

Lecture 1:\n

**Confidence/Reliability calculations us
ing Reliability Plotting (e.g.\, for non-normal data and/or censored studi
es)**

Lecture 2:\n

**Confidence/Reliability ca
lculations for MTTF and MTBF (this typically applies only to electronic eq
uipment)**

Lecture 3:\n

**Statistical Signific
ance: t-Tests and related "\;power"\; estimations**

Lecture 4:\n

**Metrology (Gage R&\;R\, Correlation\, Line
arity\, Bias\, and Uncertainty Budgets)**

Lecture 5:\n

**QC Sampling Plans (C=0 and Z1.4 attribute AQL plans\, and alter
natives to such plans)\, including OC curves\, AQL vs. LQL/LTPD\, AOQL\, a
nd calculation of acceptance rates.**

Lecture 6:\n

< strong>Statistically valid statements for use in reports

\n\n< hr />Lecture 7:\n**Summary and Implementation Recommendations\n\n \;**

\n \;\n

**John N. Zorich\,** \;has spent 35 years in t
he medical device manufacturing industry\; the first 20 years were as a &q
uot\;regular"\; employee in the areas of R&\;D\, Manufacturing\, QA
/QC\, and Regulatory\; the last 15 years were as consultant in the areas o
f QA/QC and Statistics. His consulting clients in the area of statistics h
ave included numerous start-ups as well as large corporations such as Bost
on Scientific\, Novellus\, and Siemens Medical. His experience as an instr
uctor in statistics includes having given 3-day workshop/seminars for the
past several years at Ohlone College (San Jose CA)\, 1-day training worksh
ops in SPC for Silicon Valley Polytechnic Institute (San Jose CA) for seve
ral years\, several 3-day courses for ASQ Biomedical\, numerous seminars a
t ASQ meetings and conferences\, and half-day seminars for numerous privat
e clients. He creates and sells formally-validated statistical application
spreadsheets that have been purchased by more than 75 companies\, world-w
ide.

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\nPlease contact Marilyn Turner: Phone: +1 929 900 1853
\;Email: marilyn.turner [a] nyeventslist.com for registrations