Improvement model for on time delivery in a textile SME using demand forecast, MRP, MPS and Kanban

Gil-Sequeiros X.R.; Orihuela-Toscano L.G.; Chavez-Ugaz R.; Leon-Chavarri C.C. · Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI (2025) · DOI: 10.1109/coniiti68560.2025.11366161

Resumen

The global textile industry faces persistent operational challenges, with delivery timeliness being one of the most critical. Various studies indicate that this problem significantly limits the development of Peruvian MSMEs. To address this issue, a comprehensive model was designed that sequentially and complementarily articulates four key tools: demand forecasting using the SARIMA method, MPS, MRP, and the Kanban system. This model's main contribution lies in its ability to significantly reduce delivery times by synchronizing the forecasting, planning, and execution stages, improving operational fluidity and the ability to respond to variations in demand. The proposal was validated through pilot testing and simulation in Arena. The results show an increase in the on-time delivery indicator from 72.73% to 83.33%, along with improvements in out-of-stocks from 22.83 min/dozen to 16.10 min/dozen, incomplete orders from 45.45% to 60.08%, and inventory accuracy from 66% to 88.42%. The model has proven replicable in other SMEs in the sector, contributing to more efficient and competitive management. It has been validated through simulations in scenarios specific to the textile sector, confirming its applicability to companies with similar operating conditions.

Instituciones: Universidad de Lima