Abstract
Industry 4.0 has expanded the alternatives to design more sustainable processes. Among the technologies of this industrial phase, IoT (Internet of Things) technology allows the linkage of devices that generate data at high volumes (big data), supporting the creation of Artificial Intelligence (AI) models to perform optimal operating standards to minimize waste in the production. By means of vision sensor and AI deployment, this study aimed to reduce the polybutylene plastic waste in an extrusion line of colored tubes, in which most of the waste is generated during the color transition. For that, a vision sensor that transfers the tube color in real-time was installed, which made it possible to set acceptance ranges for the standard colors of the tubes based on the elicitation of the operators' knowledge. These ranges allowed the setup of an expert system that warns the operator, by a light signal, the right time to start the production. The suggested technology demonstrated to be 11.47% more efficient in waste reduction in color transitions. It also allowed the identification of the requirements for the deployment of this technology in plastic extrusion, so it can promote overall waste reduction, which requires improvements in operation, standardization, and employee training.
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