2day Inperson Seminar on Applied Statistics for QA QC Manufacturing and Design Control
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
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
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
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. 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.
Date, Time and Venue:
Location: Atlantic City NJ
Date: 26th & 27th, July 2014
Time: 9 am to 6 pm
Venue/Hotel: Will Be Announced Soon
Register now and save $200. (Early Bird)
Until May 15, Early Bird Price: $1,295.00
From May 16 to June 24, Regular Price: $1,495.00
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