Related Experiment Video
Updated: Jan 6, 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
Development of a VSS-EWMA chart for coefficient of variation with application to production process
Amna Safeer1, Maysaa Elmahi Abd Elwahab2, Muhammad Nabi3
1Brock University, St. Catharines, Canada.
None:
This study introduces a novel Variable Sample Size Exponentially Weighted Moving Average (VSS-EWMA) control chart for monitoring the coefficient of variation, termed as Dynamic Adaptive CV (DACV) chart. Tailored for dynamic production settings where both the process mean and variability are subject to change, the proposed chart integrates an adaptive sampling strategy within the EWMA framework, allowing real-time adjustment of sample size in response to process conditions. Comparative analysis with the conventional Fixed Sample Size EWMA (FEWMA) chart reveals that DACV chart exhibits enhanced sensitivity in detecting small to moderate shifts in variability. Its performance is rigorously evaluated using Average Run Length (ARL), Standard Deviation of Run Length (SDRL), and run-length percentiles. Visualizations through heat maps further affirm its robustness across a wide range of shift magnitudes and smoothing parameters. A real-world application using semiconductor manufacturing data demonstrates the practical utility of DACV chart, underscoring its potential in contemporary quality monitoring systems.
Related Concept Videos
Coefficient of Variation
The coefficient of variation is a practical statistical tool in finance. It allows investors to assess the volatility or...
Interpreting X̄ Charts
An x̄ chart plots the values of individual measurements over time against control limits calculated from historical data. The central line...
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...
Introduction to Statistical Process Control
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...
Interpreting Run Charts

