In this paper the use of cloud computing technologies and expert systems will be analyzed. Furthermore, the use of expert systems in a cloud computing environment will be addressed. Specifically a Cloud-Based Expert System (CBES) model for decision making will be presented. The mentioned model will include the model’s infrastructure and its application. In addition, a theoretical approach will be used as a basis for the research and analysis. The CBES model offers effective, fast and reliable support for individuals or organizations when it comes to fast-paced decision making.
The availability of real-time data on the state of railway facilities and the state-of-the art technologies for data collection and analysis allow transition to the fourth generation maintenance. It is based on the prediction of the facility functional safety and dependability and the risk-oriented facility management. The article describes an approach to assessing the risks of hazardous facility failures using the latest digital data processing methods. The implementation of this approach will help set maintenance objectives and contribute to the efficient use of resources and the reduction of railway facility managers’ expenditures.
The availability of real-time data on the state of railway facilities and the state-of-the art technologies for data collection and analysis allow transition to the fourth generation maintenance. It is based on the prediction of the facility functional safety and dependability and the risk-oriented facility management. The article describes an approach to assessing the risks of hazardous facility failures using the latest digital data processing methods. The implementation of this approach will help set maintenance objectives and contribute to the efficient use of resources and the reduction of railway facility managers’ expenditures.
