Abstract
This paper discusses the Reliability, Availability, Maintainability, and Safety (RAMS) of an electrical power supply system in a large European hospital. The primary approach is based on fuzzy logic and Petri nets, using the CPNTools software to simulate and determine the most important modules of the system according to the Automatic Transfer Switch. Fuzzy Inference System is used to analyze and assess the reliability value. The stochastic versus fuzzy approach is also used to evaluate the reliability contribution of each system module. This case study aims to identify and analyze possible system failures and propose new solutions to improve the system reliability of the power supply system. The dynamic modeling is based on block diagrams and Petri nets and is evaluated via Markov chains, including a stochastic approach linked to the previous analysis. This holistic approach adds value to this type of research question. A new electrical power supply system design is proposed to increase the system’s reliability based on the results achieved.
Highlights
Electric power supply systems play a strategic function in any big hospital
Section one corresponds to the introduction; section two presents the state-of-the-art, which discusses some theoretical framework about maintenance of electrical power systems in hospitals, their Reliability, Availability, Maintainability, and Safety (RAMS), the Petri nets, the Fuzzy Inference system, the Stochastic Time Petri Nets, Markov Chains, and the CPNTols simulator software; section three presents a description of the electrical power supply system of a large European hospital, including the profile of thre hospital, the modeling the hospital electrical systems using block diagrams, focusing on generators, Automatic Transfer Switches (ATS), and Uninterruptible Power Supplies (UPS); section four presents a dynamic modeling of the hospital’s electrical system using Petri nets, which discusses the modeling of the hospital electrical system using Petri set software simulator
The results convincingly demonstrated the superiority of the Sugeno-type Fuzzy Inference System (FIS) for Weight On Bit (WOB) prediction [27]
Summary
Electric power supply systems play a strategic function in any big hospital. the manager must have a high level of maintenance services to keep the electric power installation running. Section one corresponds to the introduction; section two presents the state-of-the-art, which discusses some theoretical framework about maintenance of electrical power systems in hospitals, their Reliability, Availability, Maintainability, and Safety (RAMS), the Petri nets, the Fuzzy Inference system, the Stochastic Time Petri Nets, Markov Chains, and the CPNTols simulator software; section three presents a description of the electrical power supply system of a large European hospital, including the profile of thre hospital, the modeling the hospital electrical systems using block diagrams, focusing on generators, Automatic Transfer Switches (ATS), and Uninterruptible Power Supplies (UPS); section four presents a dynamic modeling of the hospital’s electrical system using Petri nets, which discusses the modeling of the hospital electrical system using Petri set software simulator. CPNTools, the hospital electrical system block diagrams, the fuzzification data processing, the modeling based on Markov chains and stochastic matrixes processes, and analyzing stochastic versus fuzzy process; section five discusses solutions and results; and section six presents the conclusions
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