SS503 Intermediate and Advanced Statistical Process Control (SPC) Methods
This 2-day workshop builds on the concepts from the “Process Management and Improvement - An Introduction to Effective Statistically Sound Process Management and Improvement”. It takes participants to next level to enable them to account for differences in the nature of processes in developing the best methods for managing them for control and continual improvement.
Participants will leave with the knowledge and skills to recognize the treatment diverse process situations require to effectively control and manage them. They will learn about means (Xbar) charts for variable data and about P, nP, C and U charts for attribute data and powerful exponentially weighted moving averages (EWMA) charts for both. They will also learn how to conduct studies to assess the capability of a process to meet requirements for attribute data like the number of defects (for manufacturing processes) or errors (for administrative or service processes) and the proportion defective (for manufacturing processes) or acceptable (for administrative or service processes.)
What You Cover
- How to select, construct, use and interpret statistical control charts and design data collection strategies for spotting trends or other types of changes to processes for diverse process situations
- How to assess the capability of a process to meet requirement and how it is performing relative to requirements for attribute data
- How 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.
Recommended: SS502- Statistically Sound Process Management and Improvement, or the equivalent knowledge.
Please contact Carmen Schwisow about bringing this course onsite.