Basics of Statistical Process Control

Statistical Process Control (SPC) helps process engineers regulate and continuously improve production by monitoring processes and detecting deviations before failures occur. It also enables the analysis of process corrections. Every process has natural variation, which is random in stable conditions, but systemic influences can affect the process. SPC focuses on two main objectives: stabilizing the process and improving process variability.

In this course, participants will gain practical experience with SPC techniques through hands-on examples, building confidence in process monitoring and improvement strategies. The learning environment is relaxed and engaging, encouraging a clear understanding of statistical methods.

Course outline: 

1. Statistical basics
2. Control charts
3. Process capability

Overview

Course Content

Statistical Basics

• Central role of normal distribution
• Checking distribution (histogram, QQ plot)
• Other types of distribution (log normal distribution, Weibull)
• Coverage probabilities
• Estimating the expected value and standard deviation as well as associated confidence intervals
• Basic understanding of Six Sigma and DMAIC
  
  

Control Charts

• Basics and structure of control charts
• Calculating action limits
• Measures against noise
• Average run length (ARL)
• Control rules (Nelsen, Western Electric)
• Measures against rule violations
• Embedding in DMAIC
  
  

Process Capability

• Indications for process capability
• Effects of violation of the distribution assumption

Learning Objective

Target Groups & Requirements

Training Methods

• Emphasis on understanding statistical methods, not just mathematical formulas.
• In-depth exploration of the basics of various statistical techniques.
• Key procedures explained through practical examples and simulations.
• Development of confidence and trust in process control.
• Clear, practical strategies for applying Statistical Process Control (SPC).
  
  

This course is designed for:

• Process engineers and scientists
• Professionals looking to optimize the evaluation of running processes
• Individuals interested in refreshing their basic knowledge of statistics
• Participants seeking hands-on exercises to enhance practical understanding

Requirements:

• Mathematical thinking
• Interest in getting to know the noise in the process as a natural value
  
  

The course includes lectures, simulations of specific scenarios, discussions of real-world application examples, and hands-on exercises. Simulations and practical exercises can be completed independently on a laptop, providing participants with a flexible and interactive learning experience.