Enhancing productivity in agricultural packing operations through TPM and lean manufacturing: a case study of asparagus processing in Peru

• Autores: Farah Alva, Macarena Thais, Montaño Vaez, Stefanny Milagros
• Formato: tesis de grado
• Fecha de Publicación: 2025
• Institución: Universidad de Lima
• Repositorio: ULIMA-Institucional
• Lenguaje: inglés
• OAI Identifier: oai:repositorio.ulima.edu.pe:20.500.12724/22678
• Enlace del recurso: https://hdl.handle.net/20.500.12724/22678
• Nivel de acceso: acceso abierto
• Materia: Espárragos; Envasado; Proceso de mejora continua; Mantenimiento productivo total; Producción eficiente; Estudio de casos; https://purl.org/pe-repo/ocde/ford#2.11.04

This study evaluates the application of Total Productive Maintenance (TPM) and Lean methodologies in the Peruvian agricultural sector, focusing on asparagus packing operations. To this end, it develops an innovative model with the objective of increasing the productivity of asparagus packing, one of the main problems of the Peruvian agricultural industry. Through the application of an autonomous and preventive maintenance strategy, it seeks to eliminate untimely stops in the asparagus processing line. Meanwhile, with the implementation of standardized work, the aim is to eliminate activities that do not add value and downtime. A pilot project was implemented with a sample of 72.98 kg of processed asparagus, using the processing times of each activity as input data for the validation model, using Kolmogorov- Smirnov and Chi-square statistical tests to define the distributions of the times under study. The proposed model, validated using Arena software, demonstrated a 21% increase in packaging productivity, a 36 kg/H- H-H improvement in labor productivity, and a 26.35% improvement in machinery availability. These results provide a replicable framework for medium-sized agro-exporting companies, improving their operational efficiency and competitiveness in global markets. The research contributes to the scarce literature on Lean and TPM applications in agricultural processes, highlighting their potential to improve industry productivity in developing countries.