Saltar al contenido
República del Perú · Observatorio de la producción científica universitaria
OApol.org Observatorio de Inteligencia Científica Universitaria del Perú
OApol.org
Inicio Universidades Publicaciones Investigadores
Repositorios
Tesis y trabajos académicosRevistas
Indicadores
Ranking trimestralRanking por carreraObjetivos de Desarrollo SostenibleReporte OCDERed neuronal 3D
Acerca
MetodologíaPrivacidad

Improving efficiency in Perfect Order management through a unified model of PDCA, Order Management System, and Blockchain: Case of a company that trades and imports medical equipment

Odria-Lafosse B.; Alvarez-Flores A.; Elias-Giordano C. · Proceedings of the 2025 IEEE 5th International Conference on Advanced Learning Technologies on Education and Research, ICALTER 2025 (2025) · DOI: 10.1109/icalter69698.2025.11355116

Resumen

This study addresses inefficiency in perfect order management at a company in Lima, Peru that trades and imports medical equipment, a problem that negatively affects customer satisfaction and operating costs. This issue is especially relevant in the healthcare sector, where accuracy and timeliness are critical. Prior efforts in the area have explored process optimization through methodologies such as PDCA and order management technologies, without integrating emerging tools such as Blockchain to ensure traceability and control across the entire supply chain. The proposal of this study lies in the combined implementation of PDCA methodologies, an Order Management System (OMS), and Blockchain to optimize accuracy and efficiency in order delivery. Validation was carried out through an experimental design that evaluated key order management indicators such as On Time In Full (OTIF), documentation errors, and product damage. The main results show a 15% improvement in the perfect order rate, exceeding the sector average. In conclusion, the integration of these tools not only increases the company's operational efficiency but also establishes a replicable framework for other organizations in critical sectors.

Instituciones: Universidad Peruana de Ciencias Aplicadas