Statistical analysis for condition base monitoring on auxiliary engine / Nur Hidayah Mohd Razali
Auxiliary engines are well known for their operational robustness and efficient performance. Lube oil used by auxiliary engine need to be improved in order to increase the performance of overall availability. The oil analysis interpretation should include a discussion of the equipment wear state, le...
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| Format: | Thesis |
| Language: | English |
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2012
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| Online Access: | https://ir.uitm.edu.my/id/eprint/33260/ |
| _version_ | 1848808236787957760 |
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| author | Mohd Razali, Nur Hidayah |
| author_facet | Mohd Razali, Nur Hidayah |
| author_sort | Mohd Razali, Nur Hidayah |
| building | UiTM Institutional Repository |
| collection | Online Access |
| description | Auxiliary engines are well known for their operational robustness and efficient performance. Lube oil used by auxiliary engine need to be improved in order to increase the performance of overall availability. The oil analysis interpretation should include a discussion of the equipment wear state, level of oil contamination, oil condition and a recommendation outlining any corrective maintenance actions that are necessary. The baseline of this study involved 45 data of oil starting from month of July 2008 until December 2011. There are many methods that had been used in analyzing the data which are Pareto chart, cause and effect diagram, histogram, shewhart inidividual control chart, process capability analysis and multiple regression model. For the skewness normality test, all variable are remaining normal since all variable are between -3 and 3. Moreover, the histogram also shown bell shaped model which indicates that the data are normally distributed. Based from the result, for fresh oil, the percentage of viscosity at 400C is 62.1%, Total Base Number (TBN) is 15.4%, flash point 12.8%, viscosity at 1000C is 6.7% and others are 3.0%. Overall, the most defect item in analyzing of oil is measurements during viscosity at 400C follow up by TBN, flash point, water content and wear metals. However, commonly, others variables will be affected as well when the viscosity at 400C is out of control because this is the main affected variable. On the other hand, using individual control charts, the oil needs to be changed to new fresh oil when time taken of oil is between 2200 and 2500 hours. During this hours, majority all the variables are out of control. There are specific limits had been documented for each variable. Next, according to the bar chart, we can conclude that iron gives the most abnormal condition to oil, followed by aluminum, copper, chromium and lead |
| first_indexed | 2025-11-14T22:55:31Z |
| format | Thesis |
| id | uitm-33260 |
| institution | Universiti Teknologi MARA |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T22:55:31Z |
| publishDate | 2012 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | uitm-332602020-08-25T04:35:10Z https://ir.uitm.edu.my/id/eprint/33260/ Statistical analysis for condition base monitoring on auxiliary engine / Nur Hidayah Mohd Razali Mohd Razali, Nur Hidayah Mathematical statistics. Probabilities Factor analysis. Principal components analysis. Correspondence analysis Analysis Auxiliary engines are well known for their operational robustness and efficient performance. Lube oil used by auxiliary engine need to be improved in order to increase the performance of overall availability. The oil analysis interpretation should include a discussion of the equipment wear state, level of oil contamination, oil condition and a recommendation outlining any corrective maintenance actions that are necessary. The baseline of this study involved 45 data of oil starting from month of July 2008 until December 2011. There are many methods that had been used in analyzing the data which are Pareto chart, cause and effect diagram, histogram, shewhart inidividual control chart, process capability analysis and multiple regression model. For the skewness normality test, all variable are remaining normal since all variable are between -3 and 3. Moreover, the histogram also shown bell shaped model which indicates that the data are normally distributed. Based from the result, for fresh oil, the percentage of viscosity at 400C is 62.1%, Total Base Number (TBN) is 15.4%, flash point 12.8%, viscosity at 1000C is 6.7% and others are 3.0%. Overall, the most defect item in analyzing of oil is measurements during viscosity at 400C follow up by TBN, flash point, water content and wear metals. However, commonly, others variables will be affected as well when the viscosity at 400C is out of control because this is the main affected variable. On the other hand, using individual control charts, the oil needs to be changed to new fresh oil when time taken of oil is between 2200 and 2500 hours. During this hours, majority all the variables are out of control. There are specific limits had been documented for each variable. Next, according to the bar chart, we can conclude that iron gives the most abnormal condition to oil, followed by aluminum, copper, chromium and lead 2012-07 Thesis NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/33260/1/33260.pdf Mohd Razali, Nur Hidayah (2012) Statistical analysis for condition base monitoring on auxiliary engine / Nur Hidayah Mohd Razali. (2012) Degree thesis, thesis, Universiti Teknologi MARA, Kelantan. |
| spellingShingle | Mathematical statistics. Probabilities Factor analysis. Principal components analysis. Correspondence analysis Analysis Mohd Razali, Nur Hidayah Statistical analysis for condition base monitoring on auxiliary engine / Nur Hidayah Mohd Razali |
| title | Statistical analysis for condition base monitoring on auxiliary engine / Nur Hidayah Mohd Razali |
| title_full | Statistical analysis for condition base monitoring on auxiliary engine / Nur Hidayah Mohd Razali |
| title_fullStr | Statistical analysis for condition base monitoring on auxiliary engine / Nur Hidayah Mohd Razali |
| title_full_unstemmed | Statistical analysis for condition base monitoring on auxiliary engine / Nur Hidayah Mohd Razali |
| title_short | Statistical analysis for condition base monitoring on auxiliary engine / Nur Hidayah Mohd Razali |
| title_sort | statistical analysis for condition base monitoring on auxiliary engine / nur hidayah mohd razali |
| topic | Mathematical statistics. Probabilities Factor analysis. Principal components analysis. Correspondence analysis Analysis |
| url | https://ir.uitm.edu.my/id/eprint/33260/ |