A Framework of an Intelligent Maintenance Prognosis Tool

The technology of prognosis has become a significant approach but its implementation in maintenance has a major extension. The ability prognosis in the medical area has been established to estimate the future of human health. However, in maintenance, application of prognosis is not yet seen as a pra...

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Main Authors: Asmai, S. A., Hussin, B., M. Yusof, M.
Format: Conference or Workshop Item
Language:English
Published: IEEE Computer Society 2010
Subjects:
Online Access:http://eprints.utem.edu.my/id/eprint/15/
http://eprints.utem.edu.my/id/eprint/15/2/PID1155457.pdf
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author Asmai, S. A.
Hussin, B.
M. Yusof, M.
author_facet Asmai, S. A.
Hussin, B.
M. Yusof, M.
author_sort Asmai, S. A.
building UTeM Institutional Repository
collection Online Access
description The technology of prognosis has become a significant approach but its implementation in maintenance has a major extension. The ability prognosis in the medical area has been established to estimate the future of human health. However, in maintenance, application of prognosis is not yet seen as a practical use for making better maintenance decision. To date, research in this area has been done in proposing prognosis techniques or model but leaving the implementation of prognosis as their future work. In this paper, an overview of prognosis in maintenance is presented. By using the data-driven approach, a framework for implementing of an intelligent maintenance prognosis tool is introduced. The framework utilizes the existing equipment operating performance data in the industry for prognosis process. Next, the framework combines the ability of prognosis in estimating remaining useful life (RUL) of equipment with the maintenance action knowledge to generate a well-received maintenance plan.
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format Conference or Workshop Item
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institution Universiti Teknikal Malaysia Melaka
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language English
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publishDate 2010
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spelling utem-152015-05-28T02:16:26Z http://eprints.utem.edu.my/id/eprint/15/ A Framework of an Intelligent Maintenance Prognosis Tool Asmai, S. A. Hussin, B. M. Yusof, M. Q Science (General) The technology of prognosis has become a significant approach but its implementation in maintenance has a major extension. The ability prognosis in the medical area has been established to estimate the future of human health. However, in maintenance, application of prognosis is not yet seen as a practical use for making better maintenance decision. To date, research in this area has been done in proposing prognosis techniques or model but leaving the implementation of prognosis as their future work. In this paper, an overview of prognosis in maintenance is presented. By using the data-driven approach, a framework for implementing of an intelligent maintenance prognosis tool is introduced. The framework utilizes the existing equipment operating performance data in the industry for prognosis process. Next, the framework combines the ability of prognosis in estimating remaining useful life (RUL) of equipment with the maintenance action knowledge to generate a well-received maintenance plan. IEEE Computer Society 2010 Conference or Workshop Item PeerReviewed application/pdf en http://eprints.utem.edu.my/id/eprint/15/2/PID1155457.pdf Asmai, S. A. and Hussin, B. and M. Yusof, M. (2010) A Framework of an Intelligent Maintenance Prognosis Tool. In: Second International Conference on Computer Research and Development, 2010 , 7-10 May 2010 , Kuala Lumpur.
spellingShingle Q Science (General)
Asmai, S. A.
Hussin, B.
M. Yusof, M.
A Framework of an Intelligent Maintenance Prognosis Tool
title A Framework of an Intelligent Maintenance Prognosis Tool
title_full A Framework of an Intelligent Maintenance Prognosis Tool
title_fullStr A Framework of an Intelligent Maintenance Prognosis Tool
title_full_unstemmed A Framework of an Intelligent Maintenance Prognosis Tool
title_short A Framework of an Intelligent Maintenance Prognosis Tool
title_sort framework of an intelligent maintenance prognosis tool
topic Q Science (General)
url http://eprints.utem.edu.my/id/eprint/15/
http://eprints.utem.edu.my/id/eprint/15/2/PID1155457.pdf