Robotic Process Automation Extended with Artificial Intelligence Techniques in Power Distribution Utilities

• Autor(a) principal: Pedretti,André
• Data de Publicação: 2021
• Outros Autores: Santini,Mariana, Scolimoski,Josnei, Queiroz,Mauro Henrique Brito de, Toshioka,Frank, Rocha Junior,Eloy de Paula, Pauli Júnior,Nelson de, Yomura,Marcio Takashi, Costa,Clayton Hilgemberg da, Guerra,Fabio Alessandro, Mulinari,Bruna Machado, Grando,Flavio Lori, Mumbelli,Joceleide Dalla Costa, Costa,Cláudio Inácio Almeida, Torres,Germano Lambert, Ramos,Milton Pires
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Brazilian Archives of Biology and Technology
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-89132021000200214
• topic: Artificial Intelligence; Robotic Processes Automation; Machine Learning; Data Analytics; Power Distribution Utilities

Abstract Robotic Process Automation (RPA) is one of the several important techniques currently available for companies in search of performance improvement. The step forward in RPA is its association with Artificial Intelligence for more skilled robots. This scenario is not different in Power Distribution Utilities, in which a multitude of complex processes must be executed over different data sources. Making such situation even more complex, these processes are frequently regulated and subject to audit by external bodies. However, an old question remains: what should be robotized and what should be done by humans? This paper aims at partially answering the question in the context of data analysis tasks used for making decisions in complex processes. The research development is conducted based on an Artificial Intelligence methodology incorporated into one software robot (RPA) which acquires data automatically, treats and analyzes these data, helping the human professional take decisions in the process. It is applied to a real case process that is important for validating the research. Four approaches are tested in the data analysis, but only two are really used. The robot analyzes a series of information from an energy consumption meter. The detection of possible behavior deviations in the meter data is made by comparison with its data series. The robot is capable of prioritizing the detected occurrences in the energy consumption data, indicating to the human operator the most critical situations that require attention. The association of Artificial Intelligence and RPA is viable and can really apport important benefits to the company and teams, valuing human work and bringing more efficiency to the processes.