Review,analysis and synthesis of prognostic-based decision support methods for condition based maintenance |
| |
Authors: | Alexandros Bousdekis Babis Magoutas Dimitris Apostolou Gregoris Mentzas |
| |
Affiliation: | 1.Information Management Unit (IMU), Institute of Communication and Computer Systems (ICCS), School of Electrical and Computer Engineering,National Technical University of Athens (NTUA),Zografou Athens,Greece;2.Department of Informatics,University of Piraeus,Piraeus,Greece |
| |
Abstract: | In manufacturing enterprises, maintenance is a significant contributor to the total company’s cost. Condition based maintenance (CBM) relies on prognostic models and uses them to support maintenance decisions based on the predicted condition of equipment. Although prognostic-based decision support for CBM is not an extensively explored area, there exist methods which have been developed in order to deal with specific challenges such as the need to cope with real-time information, to predict the health state of equipment and to continuously update maintenance-related recommendations. The current work aims at providing a literature review for prognostic-based decision support methods for CBM. We analyse the literature in order to identify combinations of methods for prognostic-based decision support for CBM, propose a practical technique for selecting suitable combinations of methods and set the guidelines for future research. |
| |
Keywords: | |
本文献已被 SpringerLink 等数据库收录! |
|