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Publicação
Intelligent Process Automation: Advancing Efficiency in Business Processes
| Nome: | Descrição: | Tamanho: | Formato: | |
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| 1.22 MB | Adobe PDF |
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Orientador(es)
Resumo(s)
Robotic Process Automation (RPA) has significantly transformed how companies handle
repetitive tasks by automating routine, rule-based processes. However, traditional RPAs
struggle with complex, unstructured tasks requiring decision-making and adaptability. This
thesis explores the transition from RPA to Intelligent Process Automation (IPA), which
combines RPA with advanced technologies like Artificial Intelligence and Machine Learning to
address these limitations. The research focuses on developing and implementing an IPA
solution for the Charging Station Operators’ invoicing process at EDP Comercial. Through a
structured five-phase methodology, including a comprehensive literature review, detailed
work plan, design and development, implementation, and evaluation, the study demonstrates
the substantial benefits of IPA. The developed IPA system utilizes UiPath’s Robotic Enterprise
Framework, Azure services, and a GPT-powered API for data extraction and processing.
Evaluation results highlighted a 65.2% reduction in processing time, significant cost savings,
and a notable increase in accuracy from 90% to 97%. The automation not only streamlined
the invoice validation process but also allowed the billing team to focus on higher-value tasks,
enhancing overall productivity and job satisfaction. Despite the promising outcomes, the
project encountered limitations such as initial investment costs, ethical challenges, and
integration with legacy systems. Future work should focus on expanding IPA to other
processes, continuous improvement of AI models, enhancing data analytics capabilities, and
exploring emerging technologies. This project underscores the transformative potential of IPA
in optimizing business processes, aligning with global trends toward digital transformation and
intelligent automation, and contributing to the development of smarter and more adaptive
business environments.
Descrição
Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Data Science
Palavras-chave
Intelligent Process Automation Artificial Intelligence Robotic Process Automation EDP Comercial SDG 8 - Decent work and economic growth SDG 9 - Industry, innovation and infrastructure