Operational Efficiency Enhancement through Industry 4.0 Technologies: A Case Study in a Peruvian Metalworking Company

Chang A.M.C.; Ruiz D.F.I.; Bardalez F.N. · Proceedings of the 2025 IEEE 32nd International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2025 (2025) · DOI: 10.1109/intercon67304.2025.11244672

Resumen

Peruvian metalworking companies face increasing challenges due to global competition and growing pressure to optimize production costs. These conditions demand continuous improvements in operational efficiency to remain competitive. The main causes of inefficiency are frequent machine stoppages, delays in die changeovers, delays in die testing and delay resulting from a shortage of maintenance personnel. To address these issues, this study proposes the integrated application of advanced technologies, specifically combining Single-Minute Exchange of Die (SMED) with Artificial Intelligence (AI) to optimize and reduce changeover and setup times through data-driven predictive decision-making. In addition, Autonomous Total Productive Maintenance (TPM) will be implemented alongside Internet of Things (IoT) solutions to enable real-time monitoring and train operators to perform basic autonomous maintenance tasks, thereby minimizing unplanned downtime due to equipment failures. To ensure the effectiveness of these strategies, a simulation model will be used to validate the proposed improvements, enabling a comprehensive assessment of their impact on operational efficiency before actual implementation. This strategic combination is expected to strengthen operational discipline, improve equipment availability, and provide a model for improvement.

Instituciones: Universidad Peruana de Ciencias Aplicadas