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Training of thermoelectric generator maintenance using virtual reality in oil and gas industry


Alsaeed, Adel S M A (2021) Training of thermoelectric generator maintenance using virtual reality in oil and gas industry. Doctoral thesis, Universiti Putra Malaysia.


Major oil and gas companies in recent years have advocated for the design and development of virtual maintenance training system for the greater benefit of people and the environment, focusing on sustainable development. The oil and gas industry often require people to work in hazardous environments; these environments are constantly increasing in size and complexity, hence companies continue to look for new more cost-effective ways of doing training for maintenance. Furthermore, VR training platform eliminates injuries from the training session. Providing training to a fresh maintenance worker is highly risky as they might have zero knowledge on TEGs and its handling. Hence, implementation of VR training platform will eliminate the risk of accidents in the maintenance area. This research work was conducted in companies where the business scope includes thermoelectric generators (TEG). The aim of this work is to design and develop virtual reality (VR) system for maintenance training of the cooling system in oil and gas industry. Evaluation of the efficiency in implementing series of training through the Virtual Reality (VR) system was performed and finally process performance data was compared. The activity of removing and installing heat pipe in thermoelectric generator in onshore pipeline activity was selected for the VR training platform. Maya software was used to design heat pipe system. Meanwhile, Unity 2017 software was used to create heat pipe assembly and VR interfaces. VR training platform was built using a personal computer, HTC Vive was used as monitor base and controller, and SteamVR 1.2.1 and VRTK 3.1.0 sub-component of Unity software were used. The developed VR software was evaluated by ten maintenance workers in the oil and gas industry, associated with the TEG companies. The effectiveness of the developed VR training platform was also studied. Evaluation of the experts gave a mean score of 2.73 out of 5 for pre-questionnaire and 3.27 out of 5 for post-questionnaire of the VR software, indicating that the software developed has potential of providing effective and significant training to the maintenance personnel after VR training had been done in VR environment. Furthermore, the effectiveness of the VR training platform was compared with the existing maintenance training method. Maintenance workers verified that they have gained beneficial input and experience in VR training platform compared to the existing maintenance method. Finally, the research provides a framework for oil and gas industry adoption with VR technology. This framework was evaluated by ten industrial experts in oil and gas industry and which recommends the VR technology adoption for the oil and gas industry based on its remarkable points in each department of the industry. The framework will help policy makers, managers, designers, engineers, and researchers to decide more easily and efficiently for technology implementation in VR. The developed framework was validated using another set of questionnaire survey. Overall for framework applicability on VR adoption, seven of the respondent agree that the framework is applicable to oil and gas industry while three of the respondent commented that the framework need a certain adjustment and still good enough to helps workers in oil and gas industry for training program, comprehensive approach, covers all major aspects of VR adoption in Kuwait oil and gas industry, and it provides a straightforward guidance even for beginners.

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Additional Metadata

Item Type: Thesis (Doctoral)
Subject: Thermoelectric generators
Subject: Virtual reality in engineering
Subject: Gas industry
Call Number: FK 2021 50
Chairman Supervisor: Faieza binti Abdul Aziz, PhD, PEng
Divisions: Faculty of Engineering
Depositing User: Ms. Nur Faseha Mohd Kadim
Date Deposited: 14 Jul 2022 03:14
Last Modified: 08 Nov 2022 02:34
URI: http://psasir.upm.edu.my/id/eprint/97930
Statistic Details: View Download Statistic

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