📈 Statistical Process Control (SPC)

Statistical Process Control (SPC) is the discipline of using data to understand a process, keep it stable and steadily reduce its variation. This course teaches SPC end to end — what variation is and why every process has it, the difference between common-cause and special-cause variation, how a control chart works with its centre line and control limits, how to choose variables charts (X-bar & R / X-bar & S) and attributes charts (p, np, c, u), how to read out-of-control signals with the Western Electric and Nelson rules, and how to judge process capability with Cp, Cpk, Pp and Ppk. It is aligned with the AIAG SPC reference manual and ASQ / NIST guidance. The course is organized into 6 modules, ending with a final exam (pass mark 80%). It is free awareness-level training designed for anyone who needs a practical, working understanding of the topic.

What you'll learn

• What SPC is and why every process varies — common cause vs special cause
• Control chart basics: centre line, control limits, variables and attributes charts
• Reading charts and out-of-control rules (Western Electric / Nelson)
• Process capability — Cp, Cpk, Pp, Ppk and the sigma level
• Sampling, rational subgroups and measurement system variation
• Using SPC to reduce variation — and the common mistakes to avoid

Learning objectives

• Explain what SPC is and distinguish common-cause from special-cause variation
• Describe the structure of a control chart and how control limits differ from specification limits
• Select the correct chart for variables (X-bar & R/S) and attributes (p, np, c, u) data
• Interpret out-of-control signals using runs, trends and the Western Electric / Nelson rules
• Calculate and interpret process capability indices (Cp, Cpk, Pp, Ppk)
• Apply rational subgrouping and avoid tampering and other common SPC errors