- TypeSeminar
- Location Houston, Texas, United States
- Date 08-12-2016 - 09-12-2016
Education/Teaching/Training/Development
Manufacturing
Engineering
OVERVIEW:
This 2-day seminar provides a 1-day introduction to the statistical tools used to analyze Design Verification data and Process Validation results. The entire 2nd day is spent on Statistical Process Control and Process Capability Indices. The goal of the 1st day is to help the student understand how to choose statistical methods and sample sizes, and to correctly interpret the results. The goal of the 2nd say is to explain how to monitor a validated production process, using tools that can also help improve product quality.
Why should you attend?
All design and/or manufacturing companies perform design verification and/or process validation studies. A clear understanding of relevant statistical principles and statistical methods ensures that such studies are efficient and accurate. In addition, all validated processes must be monitored to ensure their continued suitability (per the FDA).
The statistical methods used for such activities are easily misused when their fundamental principles are not well understood. Mistakes in usage can lead to new products being launched that should have been kept in R&D; or, conversely, can lead to erroneously deciding to not launch a new product. And failure to monitor production processes accurately can lead to a slow decline in product quality.
This seminar provides a thorough, practical introduction to the relevant statistical methods and principles that will help ensure that outputs from R&D, Product Transfer, Manufacturing Engineering, and Production are consistently of high quality.
Areas Covered in the Session:
Who will benefit:
AGENDA:
Day 1 Schedule:
STATISTICAL ANALYSIS OF DESIGN VERIFICATION DATA AND PROCESS VALIDATION RESULTS
Lecture 1: Regulatory requirements
Lecture 2: Basic vocabulary and concepts
Lecture 3: How to interpret Linear Regression Correlation coefficients
Lecture 4: How to calculate Confidence Intervals (for proportions & for measurements)
Lecture 5: How to perform and interpret simple t-Tests of Statistical Significance, including consideration of "p-values" and sample-size, and the concepts of "superiority" and "non-inferiority".
Lecture 6: Calculation of confidence and reliability (= % in-specification) for
Day 2 Schedule:
STATISTICAL PROCESS CONTROL (SPC) AND PROCESS CAPABILITY INDICES
Lecture 1: What is Quality?
Lecture 2: Process Variation
Lecture 3: What is Statistical Process Control?
Lecture 4: Basic Types of Control Charts and how to construct them: XbarR, XbarS, XmR, P, and U.
Lecture 5: Control Limits: Calculation & Re-calculation
Lecture 6: Out of Control: How to Detect It, & What to Do if Detect It?
Lecture 7: Sample Issues: Random, Sub-grouping, & Sample Size
Lecture 8: Capability Indices and how to calculation them
Lecture 9: Non-normal Data, and its impact on SPC.
Lecture 10: How to Initiate & Implement a Successful SPC Program
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