Related Experiment Video
Updated: Oct 1, 2026

Simulation of a Scaled Assembly Process with Collaboration of a Robotic Arm and Monitoring through a Vision System for Quality Control
Published on: August 29, 2025
How do you know that your care is improving? Part II: Using control charts to learn from your data
1R. G. Carey and Associates, Park Ridge, Illinois, USA.
Abstract:
This article builds on my article in the January 2002 issue of JACM on the use of run charts to analyze data variation and document process improvement. It describes a more powerful tool than the run chart for analyzing variation and measuring process improvement, namely, the control chart developed by Walter Shewhart. This article first explains the basic elements of a control chart, the tests for detecting a special cause variation, and how to choose the best control chart for the type of data being collected. It concludes with one case study using a control chart to document a successful intervention and some suggestions regarding computer software.
Related Concept Videos
The R Chart
R charts are pivotal for pinpointing shifts in process variability. Stability is indicated when all data points remain within the defined upper and lower...
Introduction to Statistical Process Control
Interpreting X̄ Charts
An x̄ chart plots the values of individual measurements over time against control limits calculated from historical data. The central line represents the process mean,...
The X̄ Chart
The x̄ chart, often known as the individual control chart, is a crucial tool in statistical process control. It is designed to monitor process behavior and performance over time and is widely used in various industries to ensure that processes are operating at their optimum capacity and within specified limits.
A x̄ chart is constructed by plotting individual measurements of a quality characteristic in the order in which...
Interpreting R Charts
An R chart plots the range of subsets of measurements collected from a process. Each point on the chart represents the range—defined as the difference between the maximum and minimum values—of a sample...
Interpreting Run Charts