3rd International Conference on Industrial Engineering
CINDUS 2023
Abstract
Learning curves have been frequently applied in production/operations management and in various logistics processes in many manufacturing and service organizations. However, studies on their integral use in the supply chain are recent. This paper is a contribution to fill this knowledge gap by measuring the impact of learning on lead time in logistics management systems. To demonstrate this, the empirical study was used as a methodological tool. The logarithmic-linear models with their terminology and calculation expressions were applied to three case studies representatives of the logistics systems proposed by the Supply Chain Operations Reference (SCOR) model: make-to-order, make-to-stock and engineer-to-order. As a result, the first two were adjusted to the Stanford model and the third to the De Jong’s model. Their learning curve, mathematical expressions and a sensitivity analysis were determined. This demonstrated the relevance of the approach used and its difference with respect to previous publications that mostly analyze links or parts of the supply chain.
Resumen
La presente ponencia muestra una metodología para determinar las curvas de aprendizaje (CA) en sistemas de gestión logística (SGL), a partir del funcionamiento integral de las cadenas de suministro (CS). Consta de cuatro fases y utiliza como herramientas métodos estadísticos y de gestión. Se aplicó a tres estudios de caso, representativos de los sistemas: fabricación por órdenes, fabricación para inventario y fabricación por proyecto. Como resultado, se obtuvo las CA para cada uno. La metodología difiere de lo tratado en publicaciones anteriores que, en su mayoría, analizan eslabones o partes de la CS y no se enfocan en los SGL.
About The Speaker
Dr. Roberto Cespón Castro
Discussion