Understanding variation in processes is essential for monitoring performance, identifying trends, and improving quality. Statistical Process Control (SPC) provides a structured approach to analyzing time series data, distinguishing between natural and special cause variation, and ensuring that processes remain stable and capable.
This Introduction to Statistical Process Control session will introduce participants to SPC principles, process control charts, and key rules for identifying "out of control" processes. Participants will also have the opportunity to bring their own data and apply SPC methods to create simple process control charts from first principles.
✔ The importance of understanding your data before analysis
✔ Identifying patterns and trends in time series data
✔ Common issues with traditional data visualization methods
✔ Differentiating between natural variation and special cause variation
✔ Introduction to different types of process control charts
✔ Rules for identifying "out of control" processes
✔ Understanding process capability and performance
By the end of this 3-hour session, participants will be able to:
✔ Understand the importance of correctly analyzing process data
✔ Recognize how time series data differs from other types of data
✔ Identify common pitfalls in data visualization and how to avoid them
✔ Differentiate between natural variation and special cause variation in processes
✔ Learn about key process control charts and their applications
✔ Apply SPC rules to detect "out of control" processes
✔ Gain an introduction to process capability analysis
Participants will have the opportunity to work with their own count data, ensuring practical application of SPC concepts.
This session is highly interactive and hands-on, combining structured discussions, real-world applications, and guided exercises. Participants will:
✔ Work with their own data to apply SPC techniques
✔ Create simple process control charts from first principles
✔ Discuss and interpret process variation using real-world examples
✔ Explore best practices for monitoring and improving processes
By the end of the session, participants will have a practical understanding of SPC and its application to real-world data.
This course is ideal for professionals who need to monitor, analyze, and improve processes using data-driven methods. It is particularly relevant for:
✔ Quality & Process Improvement Specialists
✔ Operations & Production Managers
✔ Business Analysts & Data Analysts
✔ Healthcare & Public Sector Professionals monitoring performance data
✔ Manufacturing & Engineering Teams seeking process stability
✔ Basic numeracy skills
✔ Participants should bring their own count data for analysis
✔ Why data quality and structure matter in SPC
✔ Common mistakes in process data analysis
✔ How time series analysis differs from standard data analysis
✔ Identifying trends, cycles, and shifts in process data
✔ The limitations of traditional charts and tables
✔ How inappropriate visualization can lead to incorrect conclusions
✔ Understanding common cause (natural) variation
✔ Recognizing special cause variation and when action is needed
✔ Introduction to different types of control charts
✔ How to choose the right chart for your data
✔ Creating simple control charts from first principles
✔ Understanding SPC rules for detecting unstable processes
✔ Real-world examples of process shifts and anomalies
✔ How to measure process capability and performance
✔ Interpreting process capability indices
⏳ 3 Hours
This session provides a practical and accessible introduction to SPC, equipping participants with the tools to analyze process variation, create control charts, and monitor process stability.
Upon successful completion of this session, participants will receive a John Varlow | Training and Consultancy Certificate of Completion.