Faculty Opinions recommendation of Quality control chart method for analyzing PEF variability in occupational asthma.

2008 ◽  
Author(s):  
Andrea Siracusa
Keyword(s):  
Quality Control ◽  
Control Chart ◽  
Occupational Asthma ◽  
Quality Control Chart

Quality control chart method for analyzing PEF variability in occupational asthma

2008 ◽  
Vol 51 (3) ◽  
pp. 223-228 ◽  
Author(s):  
Fazel Hayati ◽  
Seed Maghsoodloo ◽  
Michael J. DeVivo ◽  
Robert E. Thomas ◽  
Catherine Lemiere
Keyword(s):  
Quality Control ◽  
Control Chart ◽  
Occupational Asthma ◽  
Quality Control Chart

Simulink-based uncertain abnormal pattern recognition of quality control chart

2013 ◽  
Vol 32 (10) ◽  
pp. 2940-2943
Author(s):  
Shi-wang HOU ◽  
Hui-ming ZHU ◽  
Rong LI
Keyword(s):  
Pattern Recognition ◽  
Quality Control ◽  
Control Chart ◽  
Abnormal Pattern ◽  
Quality Control Chart

scholarly journals A Fuzzy Control Chart Approach for Attributes and Variables

2018 ◽  
Vol 8 (5) ◽  
pp. 3360-3365 ◽  
Author(s):  
N. Pekin Alakoc ◽  
A. Apaydin
Keyword(s):  
Quality Control ◽  
Fuzzy Control ◽  
Control Chart ◽  
Control Charts ◽  
Fuzzy Numbers ◽  
Fuzzy Theory ◽  
New Approach ◽  
Shewhart Control Charts ◽  
Shewhart Control ◽  
Quality Control Chart

The purpose of this study is to present a new approach for fuzzy control charts. The procedure is based on the fundamentals of Shewhart control charts and the fuzzy theory. The proposed approach is developed in such a way that the approach can be applied in a wide variety of processes. The main characteristics of the proposed approach are: The type of the fuzzy control charts are not restricted for variables or attributes, and the approach can be easily modified for different processes and types of fuzzy numbers with the evaluation or judgment of decision maker(s). With the aim of presenting the approach procedure in details, the approach is designed for fuzzy c quality control chart and an example of the chart is explained. Moreover, the performance of the fuzzy c chart is investigated and compared with the Shewhart c chart. The results of simulations show that the proposed approach has better performance and can detect the process shifts efficiently.

The contribution of statistical processes in the control of technological processes

2021 ◽  
Vol 66 (1) ◽  
pp. 5-16
Author(s):  
Olga-Ioana Amariei ◽  
Codruța-Oana Hamat ◽  
Alexandru-Victor Amariei
Keyword(s):  
Quality Control ◽  
Control Chart ◽  
Manufacturing Process ◽  
Quality Characteristic ◽  
Screw Head ◽  
Technological Processes ◽  
Quality Control Chart ◽  
The Way

In this paper, a manufacturing process is analyzed, having as quality characteristic the “height of the screw head”, using analyzes and representative diagrams. Based on this case study, the way to solve these types of problems using the Quality Control Chart module of the WinQSB program, as well as the XLSTAT program is presented.

scholarly journals Study on the Quality Control Chart for Determination of Soil Organic Carbon by Instrumental Analysis

2020 ◽  
Vol 206 ◽  
pp. 01004
Author(s):  
Zhang Fuling ◽  
Zhang Zhuo ◽  
Diao Er-long ◽  
Zhao Meiliang ◽  
Liu Menglin ◽  
...  
Keyword(s):  
Quality Control ◽  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Carbon Content ◽  
Control Chart ◽  
Control Line ◽  
Organic Carbon Content ◽  
Content Determination ◽  
Warning Limit ◽  
Quality Control Chart

【Objective】To ensure that each analysis step is in the monitoring state. The quality control chart is used to control the process of soil organic carbon content determination, and the reasons for drifting or exceeding the allowable value of the result data can be found out in time.【Method】The content of soil organic carbon in quality control samples was determined by instrumental analysis, and the quality control chart was drawn based on the determination data in Excel 2007, which was used for the quality control of the soil organic carbon content determination process.【Result】The control line of the mean control chart was 41.94% ~ 40.51%, and the warning limit was 41. 70% ~ 41. 74%. The control line range of the range control chart is 0.00% ~ 2.75%, and the warning limit is 0.00% ~ 2. 12%.【Conclusion】The quality control chart method is simple to operate,easy to master, and can timely find the abnormal points or abnormal trends of data, which has high application value in test analysis, and can ensure the accuracy of laboratory test results.

Quality Control Chart for the Mean using Double Ranked Set Sampling

2004 ◽  
Vol 31 (10) ◽  
pp. 1185-1201 ◽  
Author(s):  
Mu'azu Abujiya ◽  
Hassen Muttlak
Keyword(s):  
Quality Control ◽  
Control Chart ◽  
Ranked Set Sampling ◽  
The Mean ◽  
Quality Control Chart

scholarly journals Adjusting Quality Control Chart Limits for WBC, RBC, Hb, and PLT Counts to Reduce Daily Control Risks in Hospital Laboratory

2020 ◽  
Vol Volume 13 ◽  
pp. 3039-3049
Author(s):  
Chen-Mao Liao ◽  
Chih-Ming Lin ◽  
Chin-Chia Kuo ◽  
Ming-Shu Chen ◽  
Chun-Yang Huang ◽  
...  
Keyword(s):  
Quality Control ◽  
Control Chart ◽  
Hospital Laboratory ◽  
Quality Control Chart
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