Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Analysis of the Environmental and Productive Performance of a Lean Supply Chain through Simulation Scenarios

Version 1 : Received: 1 September 2018 / Approved: 3 September 2018 / Online: 3 September 2018 (08:36:12 CEST)
Version 2 : Received: 27 December 2019 / Approved: 29 December 2019 / Online: 29 December 2019 (08:36:38 CET)

How to cite: Jiménez, J.A.; Hernández, S.; Ruelas, E.A.; Baheza, R.; Yáñez, P.; Medina, J.M.; Téllez, S.; Figueroa, V. Analysis of the Environmental and Productive Performance of a Lean Supply Chain through Simulation Scenarios. Preprints 2018, 2018090015. https://doi.org/10.20944/preprints201809.0015.v1 Jiménez, J.A.; Hernández, S.; Ruelas, E.A.; Baheza, R.; Yáñez, P.; Medina, J.M.; Téllez, S.; Figueroa, V. Analysis of the Environmental and Productive Performance of a Lean Supply Chain through Simulation Scenarios. Preprints 2018, 2018090015. https://doi.org/10.20944/preprints201809.0015.v1

Abstract

This article aims to serve as a guide for the construction of supply chain simulation models designed with a lean approach, using Promodel software. To achieve this, a supply chain was designed for a fictitious company located in the City of Celaya, Guanajuato and a set of suppliers located in different cities within the same State. It was used as a google tool to define the distances between each of the companies. As a final result, a representative model of a supply chain was obtained, as well as a methodology that allows the construction of lean supply chains regardless of the number of companies that comprise it. The effect of the variability in the delivery times between suppliers was incorporated into the simulation model, as well as an equation that calculates the pollution emissions of the vehicles that integrate the network that moves the products between the companies. With this work it is possible to represent networks of supply chains of real world companies, where the variability and contamination factor is included, to facilitate the decision making regarding the number of vehicles, inventory levels, quantities to be shipped, frequency in the shipments, etc. with the purpose of contaminating as little as possible and at the same time preventing interruptions in the supply chain using the least amount of resources possible.

Keywords

supply chains; simulation model; contamination

Subject

Engineering, Industrial and Manufacturing Engineering

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