Automação para controle de peças de estoque: implementação de inteligência artificial e sistema de automação

Abstract

Efficient inventory control is a critical factor for the operational sustainability of companies that rely on automated equipment, such as the GLP gas bottling line, where the lack of maintenance parts can result in unplanned shutdowns and significant losses. Based on this proposal, the present work aims to develop an automation system for controlling maintenance stock parts, with the aid of artificial intelligence. The study conducted consists of a case study in a GLP gas bottling company, which began with the survey of essential parts and the determination of their critical quantities, based on historical usage and integration with the Overall Equipment Effectiveness (OEE) metric. For the development of the automation system, the low- code platform N8N, integrated with a database and artificial intelligence, met the demand for inventory management. Thus, the possibility of inventory management for parts control, with real-time updates and daily sending of parts at a critical level, can bring positive results. The results of the utilization demonstrate the effectiveness of the proposed solution, providing greater agility and precision in inventory control, reducing unplanned equipment downtime, and optimizing replenishment when necessary. It is concluded that the proposed system implementation for inventory management represents a fundamental tool, capable of mitigating operational risks and generating significant savings for the company.