A data-driven prognostic model using time series prediction techniques in maintenance decision making

• Main Author: Siti Azirah, Amai
• Format: Thesis
• Language: English; English
• Published: 2014
• Subjects: T Technology (General); TJ Mechanical engineering and machinery
• Online Access: http://eprints.utem.edu.my/id/eprint/14793/1/A%20Data-Driven%20Prognostic%20Model%20Using%20Time%20Series%20Prediction%20Techniques%20In%20Maintenance%20Decision%20Making%2024Pages.pdf; http://eprints.utem.edu.my/id/eprint/14793/2/A%20data-driven%20prognostic%20model%20using%20time%20series%20prediction%20techniques%20in%20maintenance%20decision%20making.pdf; http://eprints.utem.edu.my/id/eprint/14793/; https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=91704&query_desc=callnum%2Cwrdl%3A%20cdr%2010363

In recent years, current maintenance strategies have extensively evolved in condition-based maintenance solution in order to achieve a near-zero downtime of equipment function. One of these support elements is the use of prognostic. Prognostic has progressed as a specific function over for the last...