Statistical Process Control (SPC) Training

What is Statistical Process Control?

SPC uses statistical techniques to distinguish between natural or common causes of variation, and variations that could be attributed to specific problems. Originating in the 1920s and used in defence manufacturing, over time it would be regularly incorporated into continual improvement efforts, rather than a reactive quality control method. SPC is characterised by practical thinking. It acknowledges that variation will always exist, but helps to support decision-making around when to intervene in a process.

Course Description

SPC is module three of the Core Tools Certification Training. This module can be completed as a standalone course or part of the full Core Tools Certification Training. The full Core Tools Certification is achieved by completing all 5 modules of Core Tools Certification Training (APQP, Control Plan, FMEA, SPC, MSA and PPAP) and upon successful completion of the exam. Modules can either be taken as consecutive days (which can be booked here) or individually.

More information about the contents of each module and SMMT Quality Management’s upcoming module dates can be found here:

Advanced Product Quality Planning (APQP) and Control Plan Training
Failure Mode and Effects Analysis (FMEA) Training
Measurement Systems Analysis (MSA) Training
Production Part Approval Process (PPAP) Training

Please note: The statistical techniques used during the Measurement Systems Analysis course are covered in detail in our 1-day Statistical Process Control (SPC) programme. Therefore, we strongly recommend that you attend our SPC course before attending an MSA course unless you are already familiar with the statistical tools used.

This course is designed for people involved in the auditing or implementation of Statistical Process Control (SPC).

Manufacturing, Quality and Production Specialists: To identify and manage sources of variation in their processes.

Implementation Teams: To improve their practical decision-making and efforts to standardise processes.

Internal Auditors: To support them in identifying operational weaknesses and making data-driven improvements.

Familiarity with basic statistical concepts would be beneficial but not necessary.

Overview of SPC: Its origins as a way of statistical thinking with practical applications, and the transition from process inspections to preventative measures.

Concepts of Process Variation: Understanding the different sources of variation, including natural process variation and variation introduced by external or environmental factors.

Understanding Common and Special cause variation: Identifying which variations require analysis and potential improvement.

Charting for Variable and Attribute Data: Going from producing charts to interpreting them to support insights-driven decision making.

Control Limits: How these help identify special causes of variation and offer guidance on when to intervene.

Capability Calculation: Measuring the extent to which process stability fits within customer specification limits.

By understanding the types of variation present, actions can be taken either to eliminate the variation or reduce its impact. If the variation is excessive, the process can be stopped to avoid making nonconforming products.

It is often mandated by automotive, aerospace and other engineering primary manufacturers as a specific requirement to support the management of critical product or process characteristics. Companies that apply SPC successfully see improved yield and product quality, better and more consistent on-time delivery performance, and reduction in costs associated with non-quality such as scrap and rework.

Delegates will become more confident in interpreting statistical data into clear actions to reduce process variation. More specifically, this course will improve their competency in implementing, undertaking and auditing Statistical Process Control concepts including variable and attribute studies. 

Upon completion of the course you will receive an SMMT Quality Management certificate of attendance.