Related Experiment Video

Updated: May 21, 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

An evaluation of statistical process control techniques applied to blood component quality monitoring with particular

M J Nightingale1, S Madden, E Curnow

  • 1Patient Services, NHS Blood and Transplant (NHSBT) Southampton, Coxford Road, Southampton SO16 5AF, UK. mark.nightingale@nbs.nhs.uk

Transfusion Medicine (Oxford, England)
|June 28, 2012
PubMed

More Related Videos

Quality-Controlled Sputum Analysis by Flow Cytometry07:22

Quality-Controlled Sputum Analysis by Flow Cytometry

Published on: August 9, 2021

Related Concept Videos

Introduction to Statistical Process Control01:15

Introduction to Statistical Process Control

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...
The X̄ Chart00:58

The X̄ Chart

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 characteristic in the order in which...
Interpreting X̄ Charts01:13

Interpreting X̄ Charts

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 represents the process mean,...
The R Chart01:02

The R Chart

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...
Controlled-Current Coulometry: Overview01:27

Controlled-Current Coulometry: Overview

Controlled current coulometry, also known as amperostatic coulometry, is a technique used in electrochemical analysis to measure the quantity of a substance through the controlled passage of current. It involves the application of a constant current to an electrochemical cell containing the analyte of interest. As the current flows through the cell, the analyte undergoes a redox reaction at the electrode surface, resulting in a charge transfer. By monitoring the time required for a certain...
Statgraphics01:10

Statgraphics

Statgraphics is a comprehensive statistical software suite designed for both basic and advanced data analysis. Originating in 1980 at Princeton University under Dr. Neil W. Polhemus, it was one of the pioneering tools for statistical computing on personal computers, with its public release in 1982 marking an early milestone in data science software. Over the years, it has evolved into a robust platform for data science, offering tools for regression analysis, ANOVA, multivariate statistics,...