Application of the Internet of Things (IoT) to Increase the Perfect Order Fulfillment Index in an Air Cargo Company Through the Integration of SCOR, TPM, and SLP Approaches

Maza-Rodriguez S.; Quispe-Chuquispuma E.; Salas-Castro R. · Proceedings of the 2025 IEEE 32nd International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2025 (2025) · DOI: 10.1109/intercon67304.2025.11244669

Resumen

The perfect order fulfillment rate (POF) is a key indicator in global logistics. Its decrease affects the accuracy and punctuality of shipments, negatively impacting customer satisfaction and operating costs. This article presents a case study of a Peruvian company that transports air cargo, which during 2023 reported an average POF of 93.9%, evidencing a 4 % gap with respect to the expected optimal level of 98%. The root causes are identified as: errors in cargo handling, inaccurate manual records, lack of order traceability, and incomplete dispatches, which ultimately generate penalties and reprocessing. Therefore, the article proposes a comprehensive model that combines emerging technologies, such as the Internet of Things (IoT) for real monitoring, complemented by the SCOR approach for process standardization, TPM, and SLP, to optimize logistics processes and improve the indicator. The proposal was validated through a simulation under real-life operating conditions, the results of which demonstrated a 97.84% increase in the indicator, demonstrating improvements in efficiency and error reduction. Based on the results, the solution is intended to be replicable not only in air cargo transport but also in other logistics sectors, helping to maximize the profitability and sustainability of operations.

Instituciones: Universidad Peruana de Ciencias Aplicadas