2015 - Applied Statistics for QA, QC, Manufacturing, and Design Control - In-person Training Workshop

Overview:
The 2-day seminar begins with an examination of ISO and FDA regulations and guidelines regarding the use of statistics. Basic vocabulary and concepts are then reviewed and discussed. The flow of subsequent topics over the 2 days is as follows:
How to calculate confidence intervals (for proportions and for measurements), including a discussion of how to choose sample size
How to perform an interpret t-Tests, including consideration of "significance", "p-values", "power" and sample-size considerations
How to perform calculation of confidence/reliability for attribute data
How to perform calculation of confidence/reliability for Normally-distributed variables (measurement) data, including a discussion of how to choose sample size
How to assess Normality and how to "transform" non-normal data into Normality so that they can be used with Normal K-tables
How to calculate confidence/reliability for non-Normal data, including data with many replicates, data composed of more than one distribution, and data from studies that have been terminated early (i.e., "censored data").
How to choose which statistical analysis to use in assessing measurement equipment variation, and how to use data from such analyses to set product QC specifications
How to evaluate and use QC sampling plans; how to understand if they are worth the time and money to use vs. using confidence/reliability calculations
How to understand and implement an SPC program
How to calculate "Process Capability Indices", including a discussion of their value vs. confidence/reliability calculations.
Why should you attend:
Almost all design and/or manufacturing companies evaluate product and processes either to establish product/process specifications, to QC to such specifications, and/or to monitor compliance to such specifications.
The various statistical methods used to support such activities can be intimidating to master. If used incorrectly, such methods can result in new products being launched that should have been kept in R&D; or, conversely, deciding to not launch a new product because of incorrectly calculated product reliability or process capability. In QC, mistakenly chosen sample sizes and inappropriate statistical methods may result product being rejected that should have passed, and vice-versa.
This seminar provides a practical approach to understanding how to interpret and use a standard tool-box of statistical methods, including confidence intervals, t-tests, Normal K-tables, Normality tests, confidence/reliability calculations, AQL sampling plans, measurement equipment analysis, and Statistical Process Control. Without a clear understanding and correct implementation of such methods, a company risks significantly increasing its complaint rates, scrap rates, and time-to-market; and significantly reducing its product and service quality, its customer satisfaction levels, and its profit margins.
Areas Covered in the Session:
FDA, ISO 9001/13485, and MDD requirements related to statistical methods
QA/QC processes (sampling plans, monitoring of validated processes, setting of QC specifications, evaluation of measurement equipment)
Manufacturing processes (process validation, equipment qualification)
Design Control processes (verification, validation, risk management, design input)
Who Will Benefit:
QA/QC Supervisor
Process Engineer
Manufacturing Engineer
QC/QC Technician
Manufacturing Technician
R&D Engineer
Agenda:
Day One
Lecture 1: Regulatory Requirements
Lecture 2: Vocabulary and Concepts
Lecture 3: Confidence Intervals (attribute and variables data)
Lecture 4: t-Tests and related "power" estimations
Lecture 5: Confidence/Reliability calculations for Proportions
Lecture 6: Confidence/Reliability calculations for Normally distributed data (K-tables)
Lecture 7: Normality Tests and Normality Transformations
Day Two:
Lecture 8: Reliability Plotting (e.g., for non-normal data and/or censored studies)
Lecture 9: Statistical Analysis of Gages (introduction to Gage R&R, Gage Correlation, etc.)
Lecture 10: QC Sampling Plans (attribute AQL plans, and alternatives to such plans)
Lecture 11: Statistical Process Control (introduction, with focus on XbarR charts)
Lecture 12: Process Capability Indices calculations(Cp, Cpk, Pp, Ppk)
Lecture 13: Implementation Recommendations
Speaker:
John N. 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.
Quick Contact:
GlobalCompliancePanel
USA Phone: 1-800-447-9407
Fax: 302-288-6884
support-AT-globalcompliancepanel.com
http://www.globalcompliancepanel.com