scholarly journals Statistical-Economic Design of Control Chart If The Vector of Target Values of Multi-Variables Shifts With Time

2021 ◽  
Vol 2 (1) ◽  
pp. 97-112
Author(s):  
Hong Mao ◽  
Jin Wang
Keyword(s):  
False Alarm ◽  
Control Chart ◽  
Quality Characteristics ◽  
Economic Design ◽  
Optimal Solutions ◽  
Probability Of False Alarm ◽  
Multi Objective Programming ◽  
Target Values ◽  
Sample Interval ◽  
Financial Indices

In this paper, the statistical-economic design of a multivariate special triangle control chart is proposed to control the processes of the quality characteristics or financial indices shifting with time. A multi-objective programming with several constraints is used to determine optimal solutions of control region (probability of false alarm), the power of finding out assignable cause(s), sample interval and sample size. An application of the statistical-economic design of a Multivariate special triangle control chart is illustrated to control the soundness of insurers of U.S

scholarly journals Spectrum Sensing for Cognitive Radio Using Genetic Algorithm

2018 ◽  
Vol 14 (09) ◽  
pp. 190 ◽  
Author(s):  
Shewangi Kochhar ◽  
Roopali Garg
Keyword(s):  
Genetic Algorithm ◽  
Cognitive Radio ◽  
False Alarm ◽  
Spectrum Sensing ◽  
Optimization Technique ◽  
Primary User ◽  
Time Frame ◽  
Probability Of False Alarm ◽  
Sensing Time ◽  
Better Than

<p>Cognitive Radio has been skillful technology to improve the spectrum sensing as it enables Cognitive Radio to find Primary User (PU) and let secondary User (SU) to utilize the spectrum holes. However detection of PU leads to longer sensing time and interference. Spectrum sensing is done in specific “time frame” and it is further divided into Sensing time and transmission time. Higher the sensing time better will be detection and lesser will be the probability of false alarm. So optimization technique is highly required to address the issue of trade-off between sensing time and throughput. This paper proposed an application of Genetic Algorithm technique for spectrum sensing in cognitive radio. Here results shows that ROC curve of GA is better than PSO in terms of normalized throughput and sensing time. The parameters that are evaluated are throughput, probability of false alarm, sensing time, cost and iteration.</p>

AN ECONOMIC DESIGN OF TUKEY'S CONTROL CHART

2009 ◽  
Vol 26 (1) ◽  
pp. 53-59 ◽  
Author(s):  
Chau-Chen Torng ◽  
Pei-Hsi Lee ◽  
Chun-Chieh Tseng
Keyword(s):  
Control Chart ◽  
Economic Design

Study on Quality Control Method in Multi-Specification and Small-Batch Production

2014 ◽  
Vol 1006-1007 ◽  
pp. 363-366
Author(s):  
Hai Dong ◽  
Qing Quan Tong ◽  
Yi Kai Wang
Keyword(s):  
Quality Control ◽  
Process Control ◽  
Control Chart ◽  
Control Method ◽  
Quality Characteristics ◽  
Batch Production ◽  
Factors Affecting ◽  
Quality Control Method ◽  
Element Theory

Aiming at the problem of less quality characteristics data in multi-specification and small-batch production, matter-element theory was applied to adjust similarity of factors affecting the quality during the processing, thus similar processes was divided and data shortage problem was resolved. In addition, the relative range method was applied to translate characteristics data, thus drawing the control chart to judge process control state.Through the analysis of a case,the validity of quality control method was verified in the multi-specification and small-batch production.

Effect of Preventive Maintenance on the Economic Design of Control Chart

2009 ◽  
Vol 42 (4) ◽  
pp. 1704-1707 ◽  
Author(s):  
Ching Pou Chang ◽  
Hsiang Chin ◽  
Yuan-Du Hsiao ◽  
Fong-Jung Yu
Keyword(s):  
Control Chart ◽  
Preventive Maintenance ◽  
Economic Design

Probability of false alarm based interference suppression methods in Internet of Things (IoT) systems

2018 ◽  
Vol 144 ◽  
pp. 201-215
Author(s):  
Natthanan Promsuk ◽  
Attaphongse Taparugssanagorn ◽  
Johanna Vartiainen
Keyword(s):  
Internet Of Things ◽  
False Alarm ◽  
Interference Suppression ◽  
Probability Of False Alarm

Performance Evaluation of Geolocation Based Opportunistic Spectrum Access in Cloud-Assisted Cognitive Radio Networks

2016 ◽  
Vol 4 (1) ◽  
pp. 24-41
Author(s):  
Swetha Reddy ◽  
Isaac Cushman ◽  
Danda B. Rawat ◽  
Min Song
Keyword(s):  
Cognitive Radio ◽  
False Alarm ◽  
Estimation Error ◽  
Time Of Arrival ◽  
Spectrum Access ◽  
Angle Of Arrival ◽  
Secondary Users ◽  
Probability Of False Alarm ◽  
Computing Platform ◽  
Overall Performance

The popularity of cloud-assisted database-driven cognitive radio network (CRN) has increased significantly due to three main reasons; reduced sensing uncertainties (caused by the use of spectrum scanning and sensing techniques), FCC mandated use of a database for storing and utilizing idle channels, and leveraging cloud computing platform to process big data generated by wideband sensing and analyzing. In database-driven CRN, secondary users periodically query the database to find idle channels for opportunistic communications where secondary users use their geolocation (with the help of Global Positioning System - GPS) to find idle channels for given location and time. Use of GPS makes the overall CRN vulnerable where malicious users falsify their geolocations through GPS spoofing to find more channels. The other main drawback of GPS is estimation error while finding location of users and idle bands. Due to this there will be probability of misdetection and false alarm which will have its effect on overall performance and efficiency of the system. In this paper, the authors present a three-stage mechanism for detecting GPS spoofing attacks using angle of arrival, received signal strength and time of arrival. They also evaluate the probability of misdetection and probability of false alarm in this system while detecting location of secondary users. The authors evaluate the performance of the proposed approach using numerical results.

scholarly journals Multivariate Control Chart Based on Kernel PCA for Monitoring Mixed Variable and Attribute Quality Characteristics

Symmetry ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 1838
Author(s):  
Muhammad Ahsan ◽  
Muhammad Mashuri ◽  
Wibawati ◽  
Hidayatul Khusna ◽  
Muhammad Hisyam Lee
Keyword(s):  
Control Chart ◽  
Control Charts ◽  
Synthetic Data ◽  
Principal Component ◽  
Quality Characteristics ◽  
Kernel Functions ◽  
Quality Characteristic ◽  
Kernel Pca ◽  
Asymmetric Pattern ◽  
Attribute Quality

The need for a control chart that can visualize and recognize the symmetric or asymmetric pattern of the monitoring process with more than one type of quality characteristic is a necessity in the era of Industry 4.0. In the past, the control charts were only developed to monitor one kind of quality characteristic. Several control charts were created to deal with this problem. However, there are some problems and drawbacks to the conventional mixed charts. In this study, another approach is used to monitor mixed quality characteristics by applying the Kernel Principal Component Analyisis (KPCA) method. Using the Hotelling’s T2 statistic, the kernel PCA mix chart is proposed to simultaneously monitor the variable and attribute quality characteristics. Due to its ability to estimate the asymmetric pattern of the mixed process, the kernel density estimation (KDE) used in the proposed chart has successfully estimated the control limits that produce ARL0 at about 370 for α=0.00273. Through several experiments based on the proportion of the attribute characteristics and kernel functions, the proposed chart demonstrates better performance in detecting outlier and shift in the process. When it is applied to monitor the synthetic data, the proposed chart can detect the shift accurately. Additionally, the proposed chart outperforms the performance of the conventional mixed chart based on PCA mix by producing lower false alarm with more accurate detection of out of control processes.

Sign in / Sign up

Export Citation Format

Share Document