Reduction of Delivery Times through Supply Chain Tools in a Company of the Chemical Sector

Authors

DOI:

https://doi.org/10.26439/ciii2025.8658

Keywords:

ABC classification, demand forecasting, inventory management, logistics, slotting

Abstract

This article addresses the problem of delivery delays in a Peruvian chemical sector company, where traditional logistics operations and a low level of digitalization have resulted in economic penalties equivalent to 17.14% of its annual sales. Based on a functional and economic diagnosis, the main root causes identified were errors in materials forecasting, product deterioration, and warehouse layout disorganization. To address this issue, an improvement model was designed using Supply Chain Management (SCM) tools, integrating ABC analysis, the Odoo inventory management system, slotting, and demand forecasting. Validation using simulation and performance indicator analysis demonstrated substantial improvements, with the service level increasing from 59% to 92%, picking time reduced by 91%, and economic penalties decreasing by 83%. Furthermore, the warehouse layout redesign led to improved internal flows, reduced unnecessary travel, and more efficient use of storage space. In addition, weekly quality controls were incorporated, together with a barcode-based traceability system for real-time tracking of inventory inflows and outflows. These results confirm the effectiveness of the proposed model and provide applied evidence to optimize logistics processes in medium-sized companies in the chemical sector, contributing to the achievement of Sustainable Development Goals (SDGs) 8, 9, 12, and 13 through a low-cost, highly applicable, and potentially replicable solution in other logistics environments.

 

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Author Biographies

  • Ayme K. Anglas Valerio , Carrera de Ingeniería Industrial, Universidad de Lima, Perú

    Ayme Katherine Anglas Valerio holds a Bachelor’s degree in Industrial Engineering from Universidad de Lima. She currently serves as a Human Resources Assistant at Corporación Cueva. She is co-author of the article “Reduction of Delivery Delays Using Supply Chain Tools in a Chemical Sector Company,” presented at the IV International Congress on Industrial Engineering “AI, Operations Research, and Data Analytics” (2025), which focuses on the application of analytical tools to improve logistics performance. Her areas of interest include process improvement, sustainability, project management, supply chain management, and indicator-based decision-making.

  • Milagros K. Rojas Bravo, Carrera de Ingeniería Industrial, Universidad de Lima, Perú

    Milagros Karen Rojas Bravo holds a Bachelor’s degree in Industrial Engineering from Universidad de Lima. She currently works as an E-Commerce Commercial Intern at Supermercados Tottus S.A. She is co-author and presenter of the article “Reduction of Delivery Delays Using Supply Chain Tools in a Chemical Sector Company,” presented at the IV International Congress on Industrial Engineering “AI, Operations Research, and Data Analytics” (2025), which focuses on the application of analytical tools to improve logistics performance. Her areas of interest include data analytics applied to business management, e-commerce, supply chain management, strategic planning, and indicator-based decision-making.

  • Gustavo A. Luna Victoria León, Carrera de Ingeniería Industrial, Universidad de Lima, Perú

    Gustavo Adolfo Luna Victoria León is a doctoral candidate in Global Business Administration at Universidad Ricardo Palma. He holds a Master’s degree in Business Administration from Universidad del Pacífico and a Bachelor’s degree in Industrial Engineering from Universidad de Lima. He is a certified Project Management Professional (PMP) and Scrum Master. He currently serves as a professor in the Industrial Engineering Program at Universidad de Lima. He has more than 30 years of experience leading consultative sales, operations, and large-scale technology projects for companies such as Telefónica del Perú and GMD, serving both the public and private sectors. He specializes in high-value B2B account management. He has co-authored the articles “The Production Master Plan and Uncertainty in the Manufacturing Sector: A Literature Review” and “Scientific Research on Graphene in the Construction Industry,” both published in the Ingeniería Industrial journal of Universidad de Lima. His research interests include industrial engineering improvement solutions, project management, and applications of artificial intelligence, particularly in project management.

  • Wilson D. Calderón Gonzales, Carrera de Ingeniería Industrial, Universidad de Lima, Perú

    Wilson David Calderón Gonzales is a doctoral candidate in Business Administration at Universidad de Lima. He holds a Master’s degree in Strategic Business Administration from Centrum Católica and a degree in Industrial Engineering from Universidad de Lima. He currently serves as Operations Manager for a Movistar franchise and as a professor in the Industrial Engineering Program at Universidad de Lima. He is a member of the Beta Gamma Sigma international honor society. His research interests include consumer experience, operations management, and process improvement.

References

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Published

2026-06-08

Issue

No. 004 (2025): IV Congreso Internacional de Ingeniería Industrial

Section

Ponencias

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