Monitoring of robotized sealing process using artificial intelligence techniques

• Grant number: 24/06316-4
• Support Opportunities: Regular Research Grants
• Start date: March 01, 2025
• End date: February 28, 2027
• Field of knowledge: Engineering - Mechanical Engineering - Manufacturing Processes
• Principal Investigator: Gustavo Franco Barbosa
• Grantee: Gustavo Franco Barbosa
• Host Institution: Centro de Ciências Exatas e de Tecnologia (CCET). Universidade Federal de São Carlos (UFSCAR). São Carlos , SP, Brazil
• City of the host institution: São Carlos
• Associated researchers: Adailton Gomes Pereira ; João Gustavo Pereira da Silva ; Loris Roveda ; luis antonio oliveira araujo ; marco maccarini ; Renan Oscar de Oliveira ; Roberto Santos Inoue ; Sidney Bruce Shiki
• Associated scholarship(s): 25/06300-3 - Computer aided design, assembly, methods and processes of the robotized sealing cell, BP.IC; 25/06494-2 - Development of artificial intelligence algorithms for robotic sealing process monitoring, BP.IC

Abstract

The sealing process is present in many branches of the industry, such as: automotive, aerospace, electronics, oil & gas, packaging, chemical, medical, optical, assembly, among others. It is responsible for preventing leaks, corrosion and lightning, filling gaps, and also, to seal pressurized areas, tasks that need to be performed with precision, safety, and efficiency. Faced to that, the objective of this research project is to design, assemble and integrate the main Industry 4.0 (I4.0) technologies to develop a customized Robotized Sealing Cell (RSC) oriented by Artificial Intelligence (AI). A collaborative robot (cobot) equipped with a Sealer End-Effector (SEE) will be used for the present study aiming to improve human-robot interaction. The development of the RSC will be focused on technological development of the deposition process together with the real-time monitoring of the process based on computer vision and sensor pattern recognition, assisted by generative AI-based path generation improving the interaction with operators. The RSC will be driven by a software that will receive the 3D CAD files of sealing paths, defining the deposition strategy, and controlling the cobot and SEE. The main expected contributions of this project are on the integration of state-of-the-art AI algorithms with an important industrial process that specially requires precision, productivity, and standardization. (AU)