Statistical Methods for Process Validation

Overview:

This course will focus on teaching how to efficiently and effectively apply recommended statistical methods and tools to process validation. Using hands-on exercises (complete with realistic process data), participants will learn how to apply these tools, interpret results, and draw meaningful conclusions throughout Installation Qualification (IQ), Operational Qualification (OQ), and Performance Qualification (PQ).

In the application of statistical methods in IQ, the following will be discussed and demonstrated: sample size calculations and power, hypothesis testing and confidence intervals, and measurement systems analysis (MSA). In the application of statistical methods in OQ, the following will be discussed and demonstrated: failure modes and effects analysis (FMEA) and cause-and-effect diagrams, statistical process control (SPC), design of experiments (DOE) as well as response surface methodology (RSM), and process capability. In the application of statistical methods in PQ, the following will be discussed and demonstrations: SPC, process capability, and FMEA.

Although this is not a course on statistical theory, participants will gain an understanding and exposure to the appropriate statistical methods that should be applied through process validation.

Why you should Attend:

According to 21 CFR Part 820, medical device manufacturers are required to validate as well as monitor and control parameters for their processes. The guideline on Quality Management Systems does not specify how this is accomplished; only that "a process is established that can consistently conform to requirements" and "studies are conducted demonstrating" this. Thorough process development, optimization, and control using appropriate statistical methods and tools are recommended for demonstrating your process is both stable and capable.

Areas Covered in the Session:

• Know which statistical methods are recommended by the guidance documents
• Understand where these statistical methods should be applied
• Understand different types of data intervals
• Understand the benefits of a measurement systems analysis (MSA)
• Be able to analyze a hypothesis test and interpret data intervals
• Be able to design and analyze an experiment
• Be able to generate and interpret process control charts and capability indices

Who Will Benefit:

• Process Engineer
• Design Engineer
• Design Controls Engineer
• Six Sigma Green Belt
• Six Sigma Black Belt
• Product Development Engineer
• Continuous Improvement Manager