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The constant growth in world population and the constant technological advances, which lead to new equipment and solutions that become indispensable in the daily life of human beings, created a considerable increase in electricity's consumption. It is, therefore, essential to use this resource as efficiently as possible and in a way that reaches everyone safely.
The need for resilient infrastructures is now emerging so that there is the ability to ensure their normal functioning after an adverse phenomenon so that the infrastructures and systems we depend on are not compromised. This problem applies to infrastructures that provide essential services on a day-to-day basis to the society, such as in this specific case study, a Data Center. In these cases, proper functioning is essential in times of crisis to technology companies and other entities that provide services to other companies or the average user.
Following this problem arises the theme of this dissertation, whose implementation was carried out in a business context. A methodology is then proposed to quantify and evaluate the impact that an equipment's failure had on a given infrastructure, taking into consideration its im-portance and the time taken to resolve it, in a simple and easy to understand manner. This would be useful for all those who in the future need to recur to a detailed historical data, of critical and non-critical events, of this infrastructure. To obtain a quantitative value, a metric that considers the technical characteristics of the analyzed infrastructure will be used.
These companies need to remain competitive with their target audience so that they can thrive in today's market. It is essential that they can understand how to deal with a failure in an equipment or component without neglecting the economic side since all decisions made thereafter should aim to return to the pre-event state as quickly as possible. There is, therefore, a need to understand the impact that a failure can have on an infrastructure to act accordingly to its severity.
In the carried-out tests, it was concluded that the system provided values that allowed to order the events that occurred over a year according to their real impact and the simulations per-formed on randomly selected components were as intended.
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Resilience Critical Infrastructures Poisson Process Failure Modes Effect Analysis
