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Augmented Reality in Maintenance.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Augmented Reality in Maintenance./
作者:	Yung, Siew Chi.
面頁冊數:	1 online resource (125 pages)
附註:	Source: Dissertations Abstracts International, Volume: 84-04, Section: A.
Contained By:	Dissertations Abstracts International84-04A.
標題:	Physiology. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29353125click for full text (PQDT)
ISBN:	9798352687314

Augmented Reality in Maintenance.
Yung, Siew Chi.

Augmented Reality in Maintenance. - 1 online resource (125 pages)

Source: Dissertations Abstracts International, Volume: 84-04, Section: A.

Thesis (Ph.D.)--National University of Singapore (Singapore), 2019.

Includes bibliographical references

Maintenance plays an important role in ensuring the performance, reliability, and safety of equipment set-ups. However, the role of a maintenance operator has become significantly more challenging in recent times due to the ever-increasing complexity of modern machinery. As an interface between the virtual and the real world, Augmented Reality (AR) can potentially act as a supportive platform for modern maintenance operators. Unfortunately, most of the current approaches for AR in maintenance mainly focus on presenting manuals and guidance to the users with no consideration of other important maintenance-related factors such as their skill level. The quality of maintenance is strictly determined only by the ability of the users to understand the static information being presented. This PhD work aims to address these issues by investigating the possibility of leveraging new and existing developments in AR to enhance the ability of the operators in maintenance beyond the scope of just conducting the basic replacement or periodical maintenance of parts.As part of this PhD work, an AR-Assisted Maintenance (ARMS) framework was developed. A novel adaptive level-based AR content display approach was introduced to address the different requirements of maintenance operators, with each level corresponding to a different user's requirements. During maintenance, an operator can request for information to be presented either through an implicit mechanism or an explicit mechanism. The adaptive level-based approach is coupled with a wrist-based step evaluation approach to evaluate a user's maintenance performance via the measurement and comparison of the user's wrist position with the expected wrist position constrained by the tool used within the maintenance environment. This performance evaluation allows the system to modify the maintenance information displayed to be presented to the user. Together with an image detection module, the user profile module, and the back-angle monitoring module, the comprehensive ARMS system provides feedback to a user, resulting in a close-loop maintenance system. Compared to the existing state-of-the-art where most AR-assisted maintenance system are open-loop in nature, this work represents a significant advancement in AR-assisted maintenance system.Based on the two user studies that were conducted in conjunction with the case study to prove the effectiveness of the framework, it was observed that the system has the potential to alleviate the problems faced by a maintenance operator. Possible future directions include expanding the framework to allow the automatic authoring of the AR content in the maintenance environment and the integration of the Internet-of-Things (IOT) concept to ensure the ready adoption of the framework by the industry.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023

Mode of access: World Wide Web

ISBN: 9798352687314Subjects--Topical Terms:

518431
Physiology.
Index Terms--Genre/Form:

542853
Electronic books.

Augmented Reality in Maintenance.
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500 $a Source: Dissertations Abstracts International, Volume: 84-04, Section: A.
500 $a Advisor: Ching, Andrew Nee Yeh; Khim, Ong Soh.
502 $a Thesis (Ph.D.)--National University of Singapore (Singapore), 2019.
504 $a Includes bibliographical references
520 $a Maintenance plays an important role in ensuring the performance, reliability, and safety of equipment set-ups. However, the role of a maintenance operator has become significantly more challenging in recent times due to the ever-increasing complexity of modern machinery. As an interface between the virtual and the real world, Augmented Reality (AR) can potentially act as a supportive platform for modern maintenance operators. Unfortunately, most of the current approaches for AR in maintenance mainly focus on presenting manuals and guidance to the users with no consideration of other important maintenance-related factors such as their skill level. The quality of maintenance is strictly determined only by the ability of the users to understand the static information being presented. This PhD work aims to address these issues by investigating the possibility of leveraging new and existing developments in AR to enhance the ability of the operators in maintenance beyond the scope of just conducting the basic replacement or periodical maintenance of parts.As part of this PhD work, an AR-Assisted Maintenance (ARMS) framework was developed. A novel adaptive level-based AR content display approach was introduced to address the different requirements of maintenance operators, with each level corresponding to a different user's requirements. During maintenance, an operator can request for information to be presented either through an implicit mechanism or an explicit mechanism. The adaptive level-based approach is coupled with a wrist-based step evaluation approach to evaluate a user's maintenance performance via the measurement and comparison of the user's wrist position with the expected wrist position constrained by the tool used within the maintenance environment. This performance evaluation allows the system to modify the maintenance information displayed to be presented to the user. Together with an image detection module, the user profile module, and the back-angle monitoring module, the comprehensive ARMS system provides feedback to a user, resulting in a close-loop maintenance system. Compared to the existing state-of-the-art where most AR-assisted maintenance system are open-loop in nature, this work represents a significant advancement in AR-assisted maintenance system.Based on the two user studies that were conducted in conjunction with the case study to prove the effectiveness of the framework, it was observed that the system has the potential to alleviate the problems faced by a maintenance operator. Possible future directions include expanding the framework to allow the automatic authoring of the AR content in the maintenance environment and the integration of the Internet-of-Things (IOT) concept to ensure the ready adoption of the framework by the industry.
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538 $a Mode of access: World Wide Web
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650 4 $a Augmented reality. $3 1620831
650 4 $a Software. $2 gtt. $3 619355
650 4 $a User behavior. $3 3564661
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650 4 $a Speeches. $3 3564740
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650 4 $a Algorithms. $3 536374
650 4 $a Biology. $3 522710
650 4 $a Computer science. $3 523869
650 4 $a Information technology. $3 532993
650 4 $a Logic. $3 529544
650 4 $a Rhetoric. $3 516647
650 4 $a Web studies. $3 2122754
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