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https://link.springer.com/article/10.1007%2Fs001700170173
The intelligent predictive decision support system (IPDSS) for condition-based maintenance (CBM) supplements the conventional CBM approach by adding the capability of intelligent condition-based fault diagnosis and the power of predicting the trend of equipment deterioration.Cited by: 470
https://www.researchgate.net/publication/225745767_Intelligent_Predictive_Decision_Support_System_for_Condition-Based_Maintenance
The intelligent predictive decision support system (IPDSS) for condition-based maintenance (CBM) supplements the conventional CBM approach by adding the capability of intelligent condition-based fault diagnosis and the pou er of predicting the trend...
https://pdfs.semanticscholar.org/89ed/aeb115ca1c736fe9a428156c389c7b4ceccc.pdf
The intelligent predictive decision support system (IPDSS) for condition-based maintenance (CBM) supplements the conven-tional CBM approach by adding the capability of intelligent condition-based fault diagnosis and the power of predicting the trend of equipment deterioration. An IPDSS model, based on the recurrent neural network (RNN) approach, was
https://www.sciencedirect.com/science/article/pii/S1018363917303720
In this study, a general overview of the condition based maintenance (CBM) sciences is presented using bibliometric analysis indicators. The aim of the bibliometric analysis indicators is to measure the size and impact of publications and articles of other formats based on the count of scientific papers published and citations received.Cited by: 5
https://cordis.europa.eu/project/rcn/104632/en
The EU-funded project 'A novel decision support system for intelligent maintenance' (IMAIN) is developing an advanced cloud-based monitoring and predictive maintenance solution for forming machines. The system will integrate embedded information devices, artificial intelligence methods and an eMaintenance cloud for collecting data with novel ...
https://www.sciencedirect.com/science/article/pii/S1474667015361085
With the design of an Intelligent Predictive Decision Support System (IPDSS) for Condition-Based Maintenance, Yam et al. integrate equipment condition monitoring, intelligent condition-based fault diagnosis and prediction of the trend of equipment deterioration strongly improving the quality of maintenance decisions.Author: Marzio Sorlini, Andrea Zangiacomi, Rosanna Fornasiero
https://www.researchgate.net/profile/Mark_Lawley/publication/3412602_A_Neural_Network_Integrated_Decision_Support_System_for_Condition-Based_Optimal_Predictive_Maintenance_Policy/links/0fcfd50900e30072bd000000.pdf
WU etal.: NEURAL NETWORK INTEGRATED DECISION SUPPORT SYSTEM 227 II. LITERATUREREVIEW For the condition-based predictive maintenance, Campbell and Jardine [2] state the concept of condition-based main-
http://iict.bas.bg/acomin/docs/sci-forums/19-21-June-2013/An%20Intelligent%20Approach%20to%20Optimal%20Predictive%20Maintenance%20Strategy%20Defining.pdf
Condition based maintenance is a decision-making strategy based on real-time diagnosis of impending failures and prognosis of future equipment health [15]. To provide optimal decision making on when to take equipment down for maintenance should be integrated with overall manufacturing operations. This is why additional information about sensing
https://ieeexplore.ieee.org/document/4100783/
Abstract: This paper develops an integrated neural-network-based decision support system for predictive maintenance of rotational equipment. The integrated system is platform-independent and is aimed at minimizing expected cost per unit operational time. The proposed system consists of …Cited by: 151
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