Análise e Desenvolvimento de Sistemas e Ciência da Computação 2024.2

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    AUTOMAÇÃO ROBÓTICA: SOLUÇÕES SUSTENTÁVEIS E INCLUSIVAS: UNIFEOB
    (Centro Universitário de Ensino Octávio Bastos, 2025-02-11) SOUZA, Carlos Alberto Collozzo de; ALMEIDA, Marcelo Ciacco de; OLIVEIRA, Rodrigo Marudi de; SANTOS, Mariângela Martimbianco; SILVA, João Vitor de Lima Pacheco da; SILVA, Renan Alves da; SOARES, Vitor Antonio Rotha; OLIVEIRA, Willian Machado de
    Our company focuses on SDG 8, which seeks to promote economic growth sustained, inclusive and sustainable, with full and productive employment, in addition to work decent for everyone. In this context, the robotic prototype to be developed must act as a facilitator in an area that directly contributes to the achievement of these objectives, promoting innovative solutions that contribute to the creation of safer working environments inclusive and sustainable. The proposal, therefore, aims not only at technological development, but also at commitment to social and environmental responsibility, ensuring that robotic automation contribute to building a fairer and more sustainable future. The development of the robot will be oriented to directly meet the needs established by SDG 8, more specifically with regard to promoting a inclusive and sustainable economic growth. From this, the robot can be designed to act in several areas, from the automation of repetitive and dangerous tasks, which can reduce risk of work accidents, to support in activities that promote the inclusion of people with disabilities in the labor market.This project consists of the development of a mechanical arm specialized in carry out soldering at fixed points on circuit boards. The main structure of the project involves a movement base in a Cartesian plane, allowing the arm to move in a need for different soldering points. Welding will be carried out with the aid of a welding system. local tin supply, ensuring process efficiency and continuity. The ultimate objective is to create an efficient system capable of performing welding with high precision on circuit boards with an increasing level of autonomy due to the integration of machine learning techniques