Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

The X̄ Chart00:58

The X̄ Chart

417
The  x̄ chart is a statistical tool for monitoring the means in a process.
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...
417
Interpreting X̄ Charts01:13

Interpreting X̄ Charts

259
Interpreting x̄ charts, a type of control chart used in statistical process control helps monitor the variation in processes over time. The x̄ chart is based on the sample mean and allows for monitoring variations in the process mean over time. These charts are pivotal for quality assurance in manufacturing and other sectors.
An x̄ chart plots the values of individual measurements over time against control limits calculated from historical data. The central line...
259
The R Chart01:02

The R Chart

336
In statistical process control, control charts, particularly R charts, are instrumental in monitoring process variations and identifying non-random patterns that run charts might miss. R charts track the variability within process subgroups, which is crucial when standard deviation use is impractical or unknown process variations exist.
R charts are pivotal for pinpointing shifts in process variability. Stability is indicated when all data points remain within the defined upper and lower...
336
Introduction to Statistical Process Control01:15

Introduction to Statistical Process Control

562
Statistical Process Control (SPC) is a method used to monitor and control quality within processes, particularly in manufacturing and service delivery, by employing statistical methods. SPC aims to distinguish between natural (common cause) variation and variation due to specific changes or events (special cause), allowing for timely improvements and sustained quality. The control chart, a pivotal tool in SPC, visually displays data over time alongside a central line of upper and lower control...
562
Interpreting R Charts01:22

Interpreting R Charts

298
R chart, or range chart, is a fundamental tool in statistical process control used to monitor the variability within a process. It complements the X-bar (x̄) chart by focusing on the range of the data, rather than individual values, providing a clear picture of the process dispersion over time.
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...
298
Time-Domain Interpretation of PD Control01:07

Time-Domain Interpretation of PD Control

341
Proportional-Derivative (PD) control is a widely used control method in various engineering systems to enhance stability and performance. In a system with only proportional control, common issues include high maximum overshoot and oscillation, observed in both the error signal and its rate of change. This behavior can be divided into three distinct phases: initial overshoot, subsequent undershoot, and gradual stabilization.
Consider the example of control of motor torque. Initially, a positive...
341

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Molecular characterization of Marek's disease viruses circulating in small chicken flocks from England and Wales.

Avian pathology : journal of the W.V.P.A·2026
Same author

Predominantly cell-mediated larvicidal activity of an indigenous <i>Bacillus subtilis</i> F1 strain against lepidopteran moth pests.

3 Biotech·2026
Same author

Psychosocial implications, acceptability and ethics of screening for paediatric type 1 diabetes: a systematic review and mixed methods evidence synthesis.

Diabetologia·2026
Same author

Experimental investigation of semi-flexible pavement performance using optimized nano-silica and sugarcane bagasse ash modified grouts.

Scientific reports·2026
Same author

Structured Exercise Modulates Gut Microbiota Composition and Protects Against Diet-Induced Dysbiosis in a Rat Model.

Nutrients·2026
Same author

Interactions and binding mechanisms of soy protein isolate with theasinensin A in different pH conditions by multi-spectroscopy analysis and molecular docking.

Food chemistry·2026
Same journal

Analysis of strength degradation of coal and rock masses and stability of mined areas under long term immersion environment.

PloS one·2026
Same journal

Biogenic Silver-Selenium nanocomposite with anticancer activity and potent efficacy against vancomycin-resistant Staphylococcus aureus.

PloS one·2026
Same journal

Preparation and physicochemical characterization of a biodegradable chitosan/carboxymethyl cellulose hydrogel synthesized in NaOH/urea medium.

PloS one·2026
Same journal

Action-guilt, survivor-guilt, and depression in combat-related PTSD.

PloS one·2026
Same journal

Explainable machine learning for predicting activities of daily living at discharge in stroke patients: A retrospective study using SHAP interpretability.

PloS one·2026
Same journal

Deep learning based two-way feature depiction model for brain tumor detection.

PloS one·2026
See all related articles

Related Experiment Video

Updated: Jan 3, 2026

Simulation of a Scaled Assembly Process with Collaboration of a Robotic Arm and Monitoring through a Vision System for Quality Control
05:47

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

325

An enhanced nonparametric EWMA sign control chart using sequential mechanism.

Muhammad Riaz1, Muhammad Abid2, Hafiz Zafar Nazir3

  • 1Department of Mathematics and Statistics, King Fahad University of Petroleum and Minerals, Dhahran, Saudi Arabia.

Plos One
|November 22, 2019
PubMed
Summary
This summary is machine-generated.

This study introduces a new nonparametric control chart using sequential sampling to better detect small process shifts. The proposed arcsine exponentially weighted moving average sign chart demonstrates superior performance in shift detection.

More Related Videos

Quantification of Global Diastolic Function by Kinematic Modeling-based Analysis of Transmitral Flow via the Parametrized Diastolic Filling Formalism
11:04

Quantification of Global Diastolic Function by Kinematic Modeling-based Analysis of Transmitral Flow via the Parametrized Diastolic Filling Formalism

Published on: September 1, 2014

11.5K
Interactive and Visualized Online Experimentation System for Engineering Education and Research
08:35

Interactive and Visualized Online Experimentation System for Engineering Education and Research

Published on: November 24, 2021

2.9K

Related Experiment Videos

Last Updated: Jan 3, 2026

Simulation of a Scaled Assembly Process with Collaboration of a Robotic Arm and Monitoring through a Vision System for Quality Control
05:47

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

325
Quantification of Global Diastolic Function by Kinematic Modeling-based Analysis of Transmitral Flow via the Parametrized Diastolic Filling Formalism
11:04

Quantification of Global Diastolic Function by Kinematic Modeling-based Analysis of Transmitral Flow via the Parametrized Diastolic Filling Formalism

Published on: September 1, 2014

11.5K
Interactive and Visualized Online Experimentation System for Engineering Education and Research
08:35

Interactive and Visualized Online Experimentation System for Engineering Education and Research

Published on: November 24, 2021

2.9K

Area of Science:

  • Industrial Engineering
  • Statistical Process Control

Background:

  • Control charts are essential for process monitoring.
  • Nonparametric charts are vital when process distributions are unknown.
  • Effective sampling is crucial for nonparametric process monitoring.

Purpose of the Study:

  • To propose a novel nonparametric control chart.
  • To enhance the detection of small process shifts.
  • To utilize a sequential sampling scheme for improved efficiency.

Main Methods:

  • Development of a nonparametric arcsine exponentially weighted moving average sign chart.
  • Implementation of a sequential sampling scheme.
  • Performance evaluation using run length properties (average, median, standard deviation).

Main Results:

  • The proposed chart exhibits superior shift detection capabilities.
  • It outperforms existing nonparametric control charts in detecting small shifts.
  • Demonstrated effectiveness with smartphone accelerometer data.

Conclusions:

  • The proposed sequential sampling-based nonparametric control chart is effective for process monitoring.
  • It offers enhanced sensitivity for detecting small process variations.
  • Applicable in real-world scenarios, such as analyzing sensor data.