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Statistical Process Control with QCC in R

Preface

This tutorial provides a comprehensive introduction to Statistical Process Control (SPC) using the qcc package in R. It is designed for Continuous Improvement (CI) professionals, Process Engineers, and anyone interested in applying statistical methods to monitor and improve process quality.

About Me

Anas Tassaoui
Process & Continuous Improvement Engineer

Bridging engineering excellence with modern technology. I create modern industrial solutions and help enhance already setup plans throughout continuous improvement methodologies and create new ones. My name is Anas Tassaoui and I’m passionate about driving operational excellence through data-driven quality management.

About This Tutorial

Statistical Process Control is a powerful methodology for understanding process behavior, detecting changes, and driving continuous improvement. This tutorial combines theoretical foundations with practical R implementations using real-world examples.

Prerequisites

To get the most from this tutorial, you should have:

  • Basic knowledge of R programming
  • Understanding of basic statistics (mean, standard deviation, normal distribution)
  • Familiarity with quality concepts (helpful but not required)

Software Requirements

  • R (version 4.0 or higher)
  • RStudio (recommended)
  • qcc package
  • Additional packages: ggplot2, dplyr, knitr

How to Use This Tutorial

Each chapter builds upon previous concepts, so we recommend reading sequentially.
Key features include:

Learning Objectives

Each section begins with clear learning objectives to guide your study.

Important Concepts

Critical SPC principles and formulas are highlighted in blue boxes.

Common Pitfalls

Yellow boxes warn about frequent mistakes and misconceptions.

Practical Examples

Green boxes contain R code examples and real-world applications.

Installing Required Packages

Before starting, install the necessary R packages:

# Install required packages
install.packages(c("qcc", "ggplot2", "dplyr", "knitr"))

# Load the qcc package
library(qcc)