Automação do processo de aplicação de etiquetas de qualidade em unidades condensadoras de ar

Abstract

With the evolution of industry 4.0 automation in the industry has intensified and assists man in improving production processes, human activities that involve repetitive physical exercises by employees, and reallocating participation in monitoring and creating solutions for unexpected problems and decision (MOURA, 2019). Using the public funds of the Informatics Law n.º 8.387, this project sought to create a solution for an air conditioning factory of a South Korean multinational company in the Industrial Pole of Manaus, where there is a production line, in which a product component, called an outdoor or condensing unit, is manufactured. At one of the workstations on this line, the responsible operator performs the following activities: he receives the identification labels in rolls, manually separates them and prepares them for use, and in parallel the condensing units move on the line automatically, for by means of a conveyor belt, which, when arriving at a specific station, the operator applies the label on its moving side. After the label positioning quality inspections, the operator judges whether the product should continue in the process or whether it will be necessary to remove the label and reapply it. This production line has an hourly production rate of 300 units and an error rate in the label application process of 2%, for reasons of label quality or positioning, totaling 6 errors per hour. In this context, the motivation for research and development of a functional prototype for the automation of the described process emerged, working at the same pace as the production line, highlighting the implementation of a robotic gripper working together with a computer vision system for the application and inspection of the printing quality of the labels and their positioning in the condensing units, respectively, which after its implementation, working at the same pace as the production line, showed 1 reduction in human labor and an extreme reduction in the rate of label application errors, out of 2 % to 0.01% per hour, totaling 0.03 errors per hour.