Data mining methods for data pattern discovery and prediction
Machine critical component failures are the reason for significant process downtime as well as costly repair work. Therefore, detecting early degradation and faults will improve the product reliability as well as reduce the cost of downtime and repairs by carrying out necessary maintenance timely. T...
Saved in:
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | Final Year Project |
| Language: | English |
| Published: |
2013
|
| Subjects: | |
| Online Access: | http://hdl.handle.net/10356/51074 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Nanyang Technological University |
| Language: | English |
| id |
sg-ntu-dr.10356-51074 |
|---|---|
| record_format |
dspace |
| spelling |
sg-ntu-dr.10356-510742023-03-03T20:49:12Z Data mining methods for data pattern discovery and prediction Lin, Biheng. Ng Wee Keong School of Computer Engineering A*STAR SIMTech Centre for Advanced Information Systems DRNTU::Engineering::Computer science and engineering::Data::Data structures Machine critical component failures are the reason for significant process downtime as well as costly repair work. Therefore, detecting early degradation and faults will improve the product reliability as well as reduce the cost of downtime and repairs by carrying out necessary maintenance timely. Theoretically, a good degradation detection and analysis tool can contribute to a near zero loss for potential failures. In this report, the author descript statistical approaches to detect anomalous component and monitor the degradation status of machine critical component in order to predict the remaining useful life of the machine critical component based on the features collected, extracted and selected in previous steps. This approach is implemented in Visual C# and predicted results are compared with actual experimental result for verification of the usefulness of this approach. Bachelor of Engineering (Computer Engineering) 2013-01-03T06:47:24Z 2013-01-03T06:47:24Z 2012 2012 Final Year Project (FYP) http://hdl.handle.net/10356/51074 en Nanyang Technological University 41 p. application/pdf |
| institution |
Nanyang Technological University |
| building |
NTU Library |
| continent |
Asia |
| country |
Singapore Singapore |
| content_provider |
NTU Library |
| collection |
DR-NTU |
| language |
English |
| topic |
DRNTU::Engineering::Computer science and engineering::Data::Data structures |
| spellingShingle |
DRNTU::Engineering::Computer science and engineering::Data::Data structures Lin, Biheng. Data mining methods for data pattern discovery and prediction |
| description |
Machine critical component failures are the reason for significant process downtime as well as costly repair work. Therefore, detecting early degradation and faults will improve the product reliability as well as reduce the cost of downtime and repairs by carrying out necessary maintenance timely. Theoretically, a good degradation detection and analysis tool can contribute to a near zero loss for potential failures. In this report, the author descript statistical approaches to detect anomalous component and monitor the degradation status of machine critical component in order to predict the remaining useful life of the machine critical component based on the features collected, extracted and selected in previous steps. This approach is implemented in Visual C# and predicted results are compared with actual experimental result for verification of the usefulness of this approach. |
| author2 |
Ng Wee Keong |
| author_facet |
Ng Wee Keong Lin, Biheng. |
| format |
Final Year Project |
| author |
Lin, Biheng. |
| author_sort |
Lin, Biheng. |
| title |
Data mining methods for data pattern discovery and prediction |
| title_short |
Data mining methods for data pattern discovery and prediction |
| title_full |
Data mining methods for data pattern discovery and prediction |
| title_fullStr |
Data mining methods for data pattern discovery and prediction |
| title_full_unstemmed |
Data mining methods for data pattern discovery and prediction |
| title_sort |
data mining methods for data pattern discovery and prediction |
| publishDate |
2013 |
| url |
http://hdl.handle.net/10356/51074 |
| _version_ |
1759853776650371072 |