Alias, Mohd. Azahar (2013) Risk model for electrical and instrumentation installation for power generation system onboard ship. Masters thesis, Universiti Teknologi Malaysia, Faculty of Mechanical Engineering.
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Abstract
Installation of electrical and instrumentation of power generation system onboard ship is not without risk. Risks exist in many stages of the installation process and may lead to system failure. For decades it has been accepted by all the installation engineers representing the shipowner, the shipyard, the equipment manufacturer and the classification society that risk from each of the six main installation stages namely site preparation (P1), installation of prime mover and alternator (P2), cabling works including laying and termination (P3), installation of instrumentation equipment and accessories (P4), system interfacing and integration (P5) and system testing and commissioning (P6) is remote and independent. Separate contractors are engaged for each of the first four stages and without the knowledge that risk from one stage may be connected to the next immediate stage and may finally accumulate to cause total system failure. Data were collected using questionnaires and analysed using Statistical Package for Social Science (SPSS). Descriptive analysis is used to determine the level of risk, Pearson Chi Square method is used to check risk dependency and Pearson r2 method is used to check correlations between risks. The aim is to verify the correct sequence of installation stages, their levels or risk, risks‘ dependencies and correlations and finally develop the failure model for the installation process. The research has verified and later validated using data from Bunga Seroja ship that P1, P2, P3, P4, P5 and P6 are in that right order. The respondents agree that risks for P1, P2, P3 and P4 are low (mean of 1.71 to 2.10 corresponding to ―Agree‖ on the Likert scale used) while P5 and P6 are high (mean of 2.0 and 1.73 respectively). Risk on P2 is dependent on risk on P1, P3 is dependent on P2, P4 is dependent on P3, P5 is dependent on P4 and P6 is dependent on P5. There are strong correlations between the risks as indicated by the relatively high r2-value between P1 and P2 is 0.648, 0.774 between P1 and P3, 0.684 between P1 and P4, 0.654 between P2 and P3, 0.676 between P2 and P4, 0.673 between P3 and P4 and 0.519 between P5 and P6. The model developed indicates that the installation process will fail when P5 or P6 fails
Item Type: | Thesis (Masters) |
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Additional Information: | Thesis (Sarjana Kejuruteraan (Mekanikal - Teknologi Marin)) – Universiti Teknologi Malaysia, 2013; Supervisor : Assoc. Prof. Dr. Mohd. Zamani Ahmad |
Uncontrolled Keywords: | electric power production |
Subjects: | T Technology > TJ Mechanical engineering and machinery |
Divisions: | Mechanical Engineering |
ID Code: | 40600 |
Deposited By: | Siti Zulaiha Salim |
Deposited On: | 21 Aug 2014 07:46 |
Last Modified: | 23 Jul 2017 07:05 |
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