The 2-day seminar explains how to apply statistics to manage risk in R&D, QA/QC, and Manufacturing, with examples derived mainly from the medical device design/manufacturing industry. The flow of topics over the 2 days is as follows:
ISO standards and FDA/MDD regulations regarding the use of statistics.
Basic vocabulary and concepts.
Statistical Process Control
Statistical methods for Design Verification
Statistical methods for Product/Process Qualification
Metrology: the statistical analysis of measurement uncertainty, and how it is used to establish QC specifications
How to craft “statistically valid conclusion statements” (e.g., for reports)
Summary, from a risk management perspective
Why should you attend:
Almost all design and/or manufacturing companies evaluate product and processes either to manage risks, 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. If used incorrectly or inappropriately, statistical 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 in 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 not only significantly increasing its complaint rates, scrap rates, and time-to-market, but also risks significantly reducing its product and service quality, its customer satisfaction levels, and its profit margins.