Preprint Article Version 2 Preserved in Portico This version is not peer-reviewed

Methodology to Analyze the Productive and Environmental Performance of a 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.; Tapia, M.; Figueroa, V. Methodology to Analyze the Productive and Environmental Performance of a Supply Chain through Simulation Scenarios. Preprints 2018, 2018090015 (doi: 10.20944/preprints201809.0015.v2). Jiménez, J.A.; Hernández, S.; Ruelas, E.A.; Baheza, R.; Yáñez, P.; Medina, J.M.; Téllez, S.; Tapia, M.; Figueroa, V. Methodology to Analyze the Productive and Environmental Performance of a Supply Chain through Simulation Scenarios. Preprints 2018, 2018090015 (doi: 10.20944/preprints201809.0015.v2).

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.

Subject Areas

supply chains; simulation model; contamination; variability; inventory levels; shipments

Comments (1)

Comment 1
Received: 29 December 2019
Commenter: JOSÉ ALFREDO JIMÉNEZ GARCÍA
Commenter's Conflict of Interests: Author
Comment: The title was modified. The introdution includes more details. The literature review is more colplete. The discussión and the conclusion is more extense. We aggregaed more references
+ Respond to this comment

We encourage comments and feedback from a broad range of readers. See criteria for comments and our diversity statement.

Leave a public comment
Send a private comment to the author(s)
Views 0
Downloads 0
Comments 1
Metrics 0


×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.
We use cookies on our website to ensure you get the best experience.
Read more about our cookies here.