Methodology and Framework of a Cloud-Based Prognostics and Health Management System for Manufacturing Industry
Lee, J.
Yang, S.
Lapira, E.
Kao, H.A.
Yen, N.
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How to Cite

Lee J., Yang S., Lapira E., Kao H., Yen N., 2013, Methodology and Framework of a Cloud-Based Prognostics and Health Management System for Manufacturing Industry, Chemical Engineering Transactions, 33, 205-210.
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Abstract

Prognostics and Health Management (PHM) as a research discipline has been extensively studied in recent years, with many sophisticated techniques and intelligent algorithms developed for machinery data analysis, health assessment and decision making. PHM solutions for typical components such as roller bearing and machine tool have grown and proved to be reliable enough for industrial application. However utilization of PHM solutions in industry is still much limited due to high research, development and implementation costs. Such limitations are more severe in smaller scale factories and workshops where noample resource is available for implementing PHM systems. Efforts have been made to tackle such issue, for instance, Watchdog Agent® Toolbox developed by the IMS Center enables faster deployment of PHM solutions through algorithm modularization and standardization. With advantages that can be deliveredwith the emerging cloud computing paradigm, a cloud-based prognostics and health management system for manufacturing industry has been developed based on Watchdog Agent® tools and the ideology of PHM as a Service. In addition to traditional data acquisition and management functions in a machine conditionmonitoring system, the cloud based PHM platform is able to further provide on-demand, customizable and low-cost data analysis service. Machinery data accumulated within the cloud system further enables more advanced services such as machine-to-machine comparison, data mining and knowledge discovery.
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