SS502 Intro to Statistical Methods
This 2-day course will ground you in the fundamentals of statistically sound and effective process monitoring and management. The method is based in Statistical Process Control (SPC.) Dr. Walter Shewhart developed the powerful SPC methodology in 1929 to reduce process variation. The methodology has continued to grow in relevance and capability every year since then. Some have even suggested that the manufacture of semi-conductors wouldn’t be possible without it. “We could have invented them – but not manufactured them.”
Effective process monitoring and management and SPC requires the kind of good sound understanding of what a control chart is. Whether your application is a process to manufacture medical devices, semi-conductors, wind turbines or improve the speed of servicing people in a hospital room or improve an IT service call closure rate, these methods will reveal the process’ character and provide the foundation for solving and sustaining process improvement.
Participants will learn the basic statistics behind control charts. They will learn about individuals (Xi) and Moving Range (MR) charts for variable data and how to assess process capability and performance relative to requirements.
What You Cover
At the end of the course, participants will understand how to:
- Quantitatively and graphically characterize, describe and assess their process performance.
- Use and interpret run and statistical control charts for spotting trends or other types of changes to
- Exploit SPC methodology to assure the effectiveness of day to day operations, project management and improvement methods such as Lean and Six Sigma
- Participants received free time-limited versions of software for conducting measurement system analysis and general statistical analysis
Who Should Attend
- Process owners for any type process or anyone who is responsible for developing processes and process performance reporting
- People working with manufacturing or non-manufacturing processes
- Engineers, manufacturing personnel, non-manufacturing personnel
Discounts may apply, please refer to the registration page for details.
Principal Instructor: Steve Zagarola
Steve Zagarola is an Executive Master Black Belt (EMBB) personally trained and certified at the Six Sigma Management Institute by Dr. Mikel Harry, a co-founder and principle architect of the Six Sigma methodology. Mr. Zagarola is a founding member and managing partner of the Northwest Center for Performance Excellence (NWCPE). He is also founder of The ZDM Group, an organization dedicated to the advancement of statistically based approaches for competitive advantage. He graduated with a BS in mechanical engineering from Georgia Tech with post-graduate studies in Psychology and Statistics at Georgia Tech and Georgia State University. Mr. Zagarola is Six Sigma Master Black Belt with more than 30 years experience in the application of statistical and modern structured approaches to the optimization of manufacturing and transactional processes, quality systems, and R&D for industries ranging from food and beverage, plastics molding, wind energy, and advanced semiconductors. Prior to his current position with NWCPE, he served as the Director of Quality for Cascade Microtech, Six Sigma Program and Quality Manager for Vestas Wind Systems and Senior Manufacturing Manager for The Coca-Cola Company. He teaches Six Sigma, Statistical Process Control, Design of Experiments and other Statistical Quality methodologies and Process Excellence topics in four continents and in English and Spanish.
Co-Instructor: Aubrey Kendall
Aubrey Kendall is a supplier quality engineer at Vestas Wind Systems. He graduated with a BS in manufacturing engineering from Brigham Young University and an MBA from Clemson University. Mr. Kendall is a Six Sigma Black Belt with over 15 years of experience in manufacturing, quality, and engineering management in aerospace, energy, and other industries. His strong combination of technical skills and ease in communicating make him an effective trainer and facilitator.