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About 10,000 papers for “Control chart”

control chart

2024

Citation: 'control chart' in the IUPAC Compendium of Chemical Terminology, 5th ed.; International Union of Pure and Applied Chemistry; 2025. Online version 5.0.0, 2025. 10.1351/goldbook.08068 • License: The IUPAC Gold Book is licensed under Creative Commons Attribution-ShareAlike CC BY-SA 4.0 International for individual terms. Requests for commercial usage of the compendium should be directed to IUPAC.

Cited by 0

Shewhart control chart

2024

Citation: 'Shewhart control chart' in the IUPAC Compendium of Chemical Terminology, 5th ed.; International Union of Pure and Applied Chemistry; 2025. Online version 5.0.0, 2025. 10.1351/goldbook.08125 • License: The IUPAC Gold Book is licensed under Creative Commons Attribution-ShareAlike CC BY-SA 4.0 International for individual terms. Requests for commercial usage of the compendium should be directed to IUPAC.

Cited by 0

Control Chart Techniques

Peter Hackl · 1980

Control charts are widely used to monitor the quality of the output of production processes. This quality may be characterized by same variable X which obeys a probability law f(x,θ) where θ is a vector of parameters such as mean p or variance σ2 At regular intervals of time t=1,...,T, samples Xti,...,Xta of fixed size n ≥ 1 are taken and statistics Yt are computed. The samples are assumed to be independent. The quantity T can be unknown (continuous inspection scheme) or known (fixed sample scheme). The Yt’s are plotted on the chart; if a sample point falls outside the control limits the process is assumed to be out of control and a rectifying action is taken.

Cited by 1

Quality control chart.

Ke Gong (709665), Kai Yang (73590), Ting Xie (191025) et al. · Figshare · 2023

<div><p>Background</p><p>Hypertrophic cardiomyopathy (HCM) is a grave hazard to human health. Circular RNA (circRNAs) and micro RNA (miRNAs), which are competitive endogenous RNA, have been shown to play a critical role inHCM pathogenicity. However, to a great extent, the biological activities of ceRNA in HCM pathophysiology and prognosis remain to be investigated.</p><p>Materials and methods</p><p>By analyzing the expression files in the Gene Expression Comprehensive (GEO) database, differentially expressed (DE) circRNAs, miRNAs, and mRNAs in HCM were identified, and the target molecules of circRNAs and miRNAs were predicted. The intersection of the differentially expressed RNA molecules and the expected target was then calculated, and a ceRNA network was subsequently constructed using RNA molecules. Using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses, the potential etiology was elucidated. qPCR was used to validate a portion of the hub gene using Angiotensin II to generate a cell hypertrophy model.</p><p>Results</p><p>Three large-scale HCM sample datasets were extracted from the GEO database. After crossing these molecules with their expected targets, the circRNA-miRNA-mRNA network had two DEcircRNAs, two DEmiRNAs, and thirty DEmRNAs, compared to normal tissues. Functional enrichment analysis of GO and KEGG demonstrated that many of the HCM pathways and mechanisms were associated with calcium channel release, which is also the primary focus of future research. The qPCR results revealed that circRNA, miRNA, and mRNA expression levels were different. They may include novel noninvasive indicators for the early screening and prognostic prediction of HCM.</p><p>Conclusion</p><p>In this study, we hypothesized a circRNA-miRNA-mRNA regulation network that is closely related to the progression and clinical outcomes of HCM and may contain promising biomarkers and treatment targets for HCM.</p></div>

Cited by 0Open access

Spectral Control Chart

Téodor Tiplica, Abdessamad Kobi, Alain Barreau · Quality Engineering · 2005

In this article, we are proposing a new control chart, named the spectral control chart, whose construction is based on the spectral analysis. We are showing that it is possible to detect small mean shifts by using the information contained in the coefficients of the signal Fourier decomposition.

Cited by 3

The control chart

Thomas Hanslik, Pierre‐Yves Boëlle, Antoine Flahault · Public Health · 2001

Cited by 5

Page Control Chart

A Reasons For Amendment · 2013

Subparagraph 1523 A has been amended to add Application for Coverage options. Subparagraph 1523 B has been amended to update the Main Menu example. Subparagraph 1523 C has been amended to update the fields, descriptions and actions to be taken on the Main Menu. Subparagraph 1632 C has been amended to add instructions for using the "Affected Acres " field when COC determines a line item is not eligible. Subparagraph 1633 C has been amended to provide additional information on handling approvals and disapprovals of 2013 and future years Notices of Loss. Part 14, Section 2 has been added to provide procedure for the Application for Coverage software.

Cited by 0

weight control chart

Vissio Claudina · Mendeley Data · 2022

Excel spreadsheets templates in "empiric.xls" are from the Quality Digest website at www.qualitydigest.com/pdfs/empiric.xls (Levinson and Tumbelty, 1997). Data in "weight.xlsx" are BW measurements of 2, 9, and 14.5-month-old sampled heifers born during the years 2017 to 2019 provided by a commercial dairy farm in Córdoba province. These data were used to build control charts to monitor mean and process variability. Every sample mean or deviation outside the control limits imply a potentially identifiable cause has occurred and the producer should explore the event causing the deviation and make appropriate changes according to the age of the heifers. Control charts provide the producer and consultant with graphical information and quick alarms to support the decision-making process in the replacement program. These tools are useful at the farm level to monitor heifer growth and support management decisions.

Cited by 0Open access

Control flow chart.

Ruitao Gao (11134337), Huachao Yan (11134340), Zhou Yang (329522) · Figshare · 2021

Cited by 0Open access

Multivariate Control Chart.

Li Xu (108702), Min Li (12799), Jingpu Zhang (1430263) et al. · Figshare · 2024

<p>The PC1 results indicated overall stable of the QC. The horizontal coordinate is the order in which all samples were tested, and the vertical coordinate is the PC1 scores. Each black dot in the graph represents a sample, and yellow dots represent quality control samples.</p> <p>(TIF)</p>

Cited by 0Open access

Tukeyʼs Control Chart

Farrokh Alemi · Quality Management in Health Care · 2004

This article presents the idea of Tukey's Control Chart, a method of analyzing data based on the concepts developed by John Tukey for calculation of confidence intervals for medians. The procedure is simple to implement (no need to calculate averages or standard deviations); it does not assume any distribution of the data; it can be applied to small data sets; and it is robust and not affected by occasional unusual observations (outliers). The article provides examples of the application of Tukey's Control Chart to both patients' lifestyle management and business process improvement.

Cited by 50

Page Control Chart

A Overview · 2013

Paragraph 107 has been amended to do the following: include references to recording/control and nonrecording/noncontrol County Office

Cited by 0

weight control chart

Vissio Claudina · Data Archiving and Networked Services (DANS) · 2022

Excel spreadsheets templates in "empiric.xls" are from the Quality Digest website at www.qualitydigest.com/pdfs/empiric.xls (Levinson and Tumbelty, 1997). Data in "weight.xlsx" are BW measurements of 2, 9, and 14.5-month-old sampled heifers born during the years 2017 to 2019 provided by a commercial dairy farm in Córdoba province. These data were used to build control charts to monitor mean and process variability. Every sample mean or deviation outside the control limits imply a potentially identifiable cause has occurred and the producer should explore the event causing the deviation and make appropriate changes according to the age of the heifers. Control charts provide the producer and consultant with graphical information and quick alarms to support the decision-making process in the replacement program. These tools are useful at the farm level to monitor heifer growth and support management decisions.

Cited by 0Open access