Statistical Process Control

Summary

Our one-day Statistical Process Control (SPC) course provides a practical introduction to monitoring and controlling process performance using data.

While many organisations track performance using KPIs, they often struggle to distinguish between normal process variation and signals that require action. This can lead to overreaction, missed warning signs, and ineffective decision-making.

SPC provides a structured, statistical approach to understanding process behaviour, enabling earlier detection of issues and more informed responses.

During this course, participants will learn how to select, create, and interpret control charts, and how to use SPC to support effective, data-driven decision making.

How will I benefit?

After the course you will be able to:

  • Understand the difference between common cause and special cause variation
  • Understand process capability and its relationship to performance
  • Understand different types of data and how this impacts the type of SPC chart required
  • Recognise when a process is stable and when it requires intervention
  • Interpret control charts correctly and avoid overreaction
  • Use SPC to identify early warning signals before issues arise
  • Apply SPC using your own process data

Who should attend?

This course is ideal for delegates responsible for monitoring, managing, or improving process performance. It is particularly suited to:

  • Manufacturing and process engineers
  • Quality engineers and specialists
  • Operations and production managers
  • Continuous improvement practitioners
  • Process Owners who are responsible for KPIs and performance reporting

Course Outline / Key Topics

Introduction

  • The limitations of traditional KPI monitoring
  • Understanding variation in processes
  • Overview of SPC and its purpose

Understanding Variation

  • Common vs special cause variation
  • Process stability vs capability
  • The role of Normality

Data and Measurement

  • Types of data (variable vs attribute)
  • Data collection considerations
  • Measurement system awareness

Control Charts

  • Selection of appropriate charts
  • Constructing control charts
  • Interpreting control charts

Responding to Signals

  • Identifying out-of-control conditions
  • When to act—and when not to
  • Avoiding over-adjustment

Practical Application

  • Creating charts using real or simulated data
  • Interpreting scenarios and making decisions
  • Applying SPC to your own processes