Model to Increase On-Time Delivery Using Predictive Maintenance 4.0, SMED, and SLP With Digital Support in a Metalworking Company

Cardozo-Espinoza C.; Carrion-Ninasque J.; MacEda-Cerdán C.; Trillo-Rivera G. · ETCM 2025 - 9th Ecuador Technical Chapters Meeting (2025) · DOI: 10.1109/etcm67548.2025.11304410

Resumen

This study analyzed order delivery delays that negatively impacted the On-Time Delivery (OTD) indicator, crucial for maintaining competitiveness in a company in the metalworking sector. The analysis identified a 17.91% technical gap in OTD, with the company's current performance at 67.09% compared to the industry average of 85%. This delay incurs an annual economic impact of S/. 352,167.48, representing 10.87% of the company's annual revenue. The study detailed that 79.77% of downtime is caused by machinery downtime, prolonged setup times, and unnecessary routes. To address these inefficiencies, techniques such as Predictive Maintenance 4.0 to optimize machinery, SMED to reduce setup times, and SLP with digital support to improve route efficiency were implemented. With these improvements, validated through simulation in Arena software, the company was able to increase its OTD by 25.09%, reduce machine downtime by 47.87%, setup times by 39.99%, and distance traveled by 36.56%, according to the performance indicators defined for each root cause. These results helped close the identified gap and demonstrate the effectiveness of the tools implemented in the metalworking sector.

Instituciones: Universidad Peruana de Ciencias Aplicadas