This paper aims to develop an automation approach for inspecting dies, wires, and filaments in the wire drawing process. Historically, manufacturing has advanced significantly, culminating in Industry 4.0, characterized by integrated digital technologies like IoT and AI, which enhance efficiency. The current manual inspection of wire diameter and die integrity is inefficient, error-prone, and requires production stoppages, leading to inaccuracies and compromised product quality. The proposed automation aims to address these issues, by ensuring high precision, continuous production, and reduced operational costs by eliminating human error and minimizing waste. At the core of this automation is a closed-loop control system. It uses laser micrometers for real-time wire and filament diameter measurement due to their precision and speed. Type K temperature sensors monitor die integrity, crucial since die temperature affects material deformation and lifespan. Alternative sensors (LVDTs, optical encoders, video/vision, ultrasonics) were deemed less suitable due to contact needs, limited precision, or environmental sensitivity. Essential actuators include electric motors, hydraulic cylinders, and lead screws for dynamic adjustment of speed, pressure, and die spacing based on sensor feedback. The system features alert levels (orange for tolerance proximity, red for critical deviations) and an ammeter to prevent motor damage by monitoring load. The methodology is qualitative and follows the USA (Understand, Simplify, Automate) principle. It involves thoroughly analyzing current manual processes to identify problems and losses, simplifying to remove non-value-adding activities, and then structuring the automation solution. This approach aligns with Lean Manufacturing, fostering continuous improvement. In conclusion, automating the inspection process with carefully selected sensors and actuators leads to a more precise, efficient, and sustainable wire drawing operation, ultimately enhancing product quality and increasing industry competitiveness.
Juventino et al. (Thu,) studied this question.
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