Machine Learning, MRP, and Lean Tools as an Internal Innovation Strategy to Improve Efficiency in a Bottling Company

Autores/as

  • Haydee Manuelo Universidad Peruana de Ciencias Aplicadas
  • Hellyn Ruiz Universidad Peruana de Ciencias Aplicadas
  • Martin Saenz-Moron Universidad Peruana de Ciencias Aplicadas
  • Anita Straujuma Riga Technical University

DOI:

https://doi.org/10.18687/LEIRD2025.1.1.309

Palabras clave:

Autonomous Maintenance, Hybrid Forecasting, Machine Learning, MRP, Standardized Work

Resumen

The bottled water sector in Peru has shown sustained growth in recent years, driven by increased consumption and high seasonal demand, particularly during the summer. With a projected market value of $452.90 billion by 2029, companies in the industry face the ongoing challenge of adapting to a competitive and constantly changing environment. In this context, a bottling company identified improvement opportunities within its production system as it faced issues such as mechanical failures, supply shortages, planning errors, and rework, all of which compromised its operational efficiency. In response, strategies were promoted to optimize resource utilization, reduce unproductive time, and ensure product quality. These actions, driven from within the organization, reflected an intrapreneurial initiative focused on strengthening planning, preventive maintenance, and process standardization to enhance responsiveness to demand, particularly during peak months. Additionally, the company reinforced compliance with health and environmental regulations, contributing to the sustainability of its operations. As a result, the company achieved an 11% increase in operational efficiency, reduced losses, and enhanced its competitiveness. This experience illustrates how the pursuit of innovative solutions from within the work environment can transform traditional management practices, enabling organizations to adapt and thrive in a constantly evolving market while maintaining a commitment to efficiency, quality, and continuous improvement.

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Publicado

2025-12-12

Número

Sección

Articles

Licencia

Licencia Creative Commons

Esta obra está bajo una Licencia Creative Commons Atribución-NoComercial-CompartirIgual 4.0 Internacional.

LACCEI conserva el copyright de todos los artículos publicados bajo los términos de su acuerdo de transferencia de copyright. Como titular del copyright, LACCEI distribuye los artículos al público bajo la Licencia Internacional Creative Commons Atribución-NoComercial-CompartirIgual 4.0 (CC BY-NC-SA 4.0).

Cómo citar

Manuelo, H., Ruiz, H., Saenz-Moron, M., & Straujuma, A. (2025). Machine Learning, MRP, and Lean Tools as an Internal Innovation Strategy to Improve Efficiency in a Bottling Company. LACCEI, 2(13). https://doi.org/10.18687/LEIRD2025.1.1.309