Data mining and fault diagnosis based on wafer acceptance test data and in-line manufacturing data

2002 ◽  
Author(s):  
Chih-Min Fan ◽  
Ruey-Shan Guo ◽  
A. Chen ◽  
Kuo-Ching Hsu ◽  
Chih-Shih Wei
Keyword(s):  
Data Mining ◽  
Fault Diagnosis ◽  
Test Data ◽  
Acceptance Test ◽  
Manufacturing Data

Data Visualization Indicator Disease (Malaria, Dengue Fever, and Measles) in The Year 2012-2015

2017 ◽  
Vol 4 (2) ◽  
pp. 87-93
Author(s):  
Immanuel Luigi Da Gusta ◽  
Johan Setiawan
Keyword(s):  
Data Mining ◽  
Human Resources ◽  
Data Visualization ◽  
Health Sector ◽  
Medical Personnel ◽  
Database Systems ◽  
Process Time ◽  
Acceptance Test ◽  
Visual Data Mining ◽  
The Government

The aim of this paper are: to create a data visualization that can assist the Government in evaluating the return on the development of health facilities in the region and province area in term of human resources for medical personnel, to help community knowing the amount of distribution of hospitals with medical personnel in the regional area and to map disease indicator in Indonesia. The issue of tackling health is still a major problem that is not resolved by the Government of Indonesia. There are three big things that become problems in the health sector in Indonesia: infrastructure has not been evenly distributed and less adequate, the lack of human resources professional health workforce, there is still a high number of deaths in the outbreak of infectious diseases. Data for the research are taken from BPS, in total 10,600 records after the Extract, Transform and Loading process. Time needed to convert several publications from PDF, to convert to CSV and then to MS Excel 3 weeks. The method used is Eight-step Data Visualization and Data Mining methodology. Tableau is chosen as a tool to create the data visualization because it can combine each dasboard inside a story interactive, easier for the user to analyze the data. The result is a story with 3 dashboards that can fulfill the requirement from BPS staff and has been tested with a satisfied result in the UAT (User Acceptance Test). Index Terms—Dashboard, data visualization, disease, malaria, Tableau REFERENCES [1] S. Arianto, Understanding of learning and others, 2008. [2] Rainer; Turban, Introduction to Information Systems, Danvers: John Wiley & Sons, Inc, 2007. [3] V. Friedman, Data Visualization Infographics, Monday Inspirition, 2008. [4] D. A. Keim, "Information Visualization and Visual Data Mining," IEEE Transactions on Visualization and Computer Graphics 8.1, pp. 1-8, 2002. [5] Connolly and Begg, Database Systems, Boston: Pearson Education, Inc, 2010. [6] E. Hariyanti, "Pengembangan Metodologi Pembangunan Information Dashboard Untuk Monitoring kinerja Organisasi," Konferensi dan Temu Nasional Teknologi Informasi dan Komunikasi untuk Indonesia, p. 1, 2008. [7] S. Darudiato, "Perancangan Data Warehouse Penjualan Untuk Mendukung Kebutuhan Informasi Eksekutif Cemerlang Skin Care," Seminar Nasional Informatika 2010, pp. E-353, 2010.

Fault Diagnosis of Automobile ECUs with Data Mining Technologies

2010 ◽  
Vol 40-41 ◽  
pp. 156-161 ◽  
Author(s):  
Yang Li ◽  
Yan Qiang Li ◽  
Zhi Xue Wang
Keyword(s):  
Data Mining ◽  
Fault Diagnosis ◽  
Decision Tree ◽  
Data Stream ◽  
Electronic Control Unit ◽  
Rapid Development ◽  
Reliability And Validity ◽  
Control Unit ◽  
Use Of Data ◽  
The Cost

With the rapid development of automotive ECUs(Electronic Control Unit), the fault diagnosis becomes increasingly complicated. And the link between fault and symptom becomes less obvious. In order to improve the maintenance quality and efficiency, the paper proposes a fault diagnosis approach based on data mining technologies. By making full use of data stream, we firstly extract fault symptom vectors by processing data stream, and then establish a diagnosis decision tree through the ID3 decision tree algorithm, and finally store the link rules between faults and the related symptoms into historical fault database as a foundation for the fault diagnosis. The database provides the basis of trend judgments for a future fault. To verify this approach, an example of diagnosing faults of entertainment ECU is showed. The test result testifies the reliability and validity of this diagnostic method and reduces the cost of ECU diagnosis.

A Digital Computer Program for Processing Turbine-Generator Acceptance Test Data

1962 ◽  
Vol 84 (3) ◽  
pp. 295-304 ◽  
Author(s):  
G. A. Maneatis ◽  
W. H. Barr
Keyword(s):  
Thermodynamic Properties ◽  
Computer Program ◽  
Steam Turbine ◽  
Test Data ◽  
Digital Computer ◽  
Heat Rate ◽  
Acceptance Test ◽  
Turbine Generator

This paper describes a digital computer program which processes rapidly all of the data taken during a steam turbine-generator acceptance test. Specifically, it determines all thermodynamic properties of steam and water, computes corrected test heat rate, and finally develops a contract heat rate for purposes of comparison with manufacturer’s guarantees. The application of this program on two 330-megawatt units is discussed. The thinking leading to certain key decisions involving the ultimate approach taken is presented for the benefit of those contemplating a similar effort.

Data Mining Applications to Fault Diagnosis in Power Electronic Systems: A Systematic Review

2021 ◽  
pp. 1-1
Author(s):  
Arash Moradzadeh ◽  
Behnam Mohammadi-ivatloo ◽  
Kazem Pourhossein ◽  
Amjad Anvari-Moghaddam
Keyword(s):  
Systematic Review ◽  
Data Mining ◽  
Fault Diagnosis ◽  
Electronic Systems ◽  
Power Electronic
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