(8b) Ferramenta Baseada Em IA Para Criação De "e Se" e Análise De Risco Em Segurança De Processos

This presentation introduces the development of an innovative software tool designed to streamline and optimize the creation of "What-If" analyses in process safety management (PSM), leveraging artificial intelligence as a core feature. The tool addresses the need for increased productivity and quality in risk management across industrial facilities, offering robust technological support that automates repetitive tasks and generates insights based on historical data.

Traditional "What-If" methodologies often demand significant time and effort from teams, requiring extensive brainstorming sessions, information gathering, and manual formatting of scenarios and responses. The developed software employs AI algorithms to accelerate these stages by automatically identifying risk scenarios based on inputs provided by the team and existing risk analysis databases. Furthermore, the tool suggests control measures aligned with CCPS best practices and generates structured reports compliant with regulatory standards.

One of the tool's standout features is its capacity for continuous learning. As it is used, the software refines its recommendations by analyzing patterns from historical data, improving the precision and relevance of its outputs. This approach not only reduces the time required to complete analyses but also enhances the reliability of results, minimizing the subjectivity inherent to manual methods.

The tool also features a user-friendly and collaborative interface, enabling multidisciplinary teams to interact with the system seamlessly. With intuitive dashboards and configurable modules, it supports varying levels of detail, adapting to projects of different sizes and complexities.

Presentation Goal:
The goal is to demonstrate how artificial intelligence can revolutionize the way risk analyses are conducted, focusing on productivity and result quality. The presentation will cover the software development process, key features, and case studies that highlight its efficiency and the benefits of integrating it into process safety teams.

This proposal aligns with CCPS principles, promoting the adoption of innovative technologies to elevate safety standards in industrial environments.