Rodríguez Aguilar, Román
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Preferred name
Rodríguez Aguilar, Román
Official Name
Rodríguez Aguilar, Román
Alternative Name
rrodrigueza
Main Affiliation
ORCID
Scopus Author ID
56717663000
Researcher ID
AAO-6158-2020

Research Output
Now showing 1 - 4 of 4
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Selecting the Distribution System using AHP and Fuzzy AHP Methods

2024 , Saucedo-Martínez, Jania Astrid , Salais-Fierro, Tomás Eloy , Rodríguez Aguilar, Román , Marmolejo Saucedo, José Antonio

In this research, we present a supporting tool for decision making by designing a distribution system for a trading company of supplies for the welding industry in Mexico. The case study encompasses a distribution system with shortage problems and poor fleet capacity. To address these problems, improvement options were grouped into three possible scenarios through a third-party logistics (3PL) service. Furthermore, for the evaluation and selection of one of the scenarios, the Analytic Hierarchy Process (AHP) methodology was proposed integrating fuzzy logic as a tool for decision making, including factors of uncertainty and subjectivity as well as a comparison with traditional AHP obtaining the best scenario, meeting the requirements of the company, and showing potential improvements in the desired service level for its distribution system. © 2024 Springer Nature

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Digital Twins and Blockchain: Empowering the Supply Chain

2022 , Aguilar Ramírez, José Eduardo , Marmolejo Saucedo, José Antonio , Rodríguez Aguilar, Román

Industry 4.0 is here, and it arrived with very promising new technologies that can foster he supply chain management across industries. In this paper we review multiple sources to identify the main characteristics of Digital Twins and Blockchain technologies and how they can work together to fulfill the needs of the supply chain. We identify some advantages and disadvantages that must be properly analyzed before adopting this approach into any business. Many applications behind these new benefits are still in development, but we believe these two technologies have great potential. © Springer Nature

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Structural Dynamics and disruption events in Supply Chains using Fat Tail Distributions

2019 , Rodríguez Aguilar, Román , Marmolejo Saucedo, José Antonio

The analysis of structural dynamics in a supply chain requires robust methods for the modeling of disruption events that can be faced. Statistical modeling, the machine learning application and access to large amounts of data require much more realistic models to manage risk in the supply chain. This study proposes a statistical methodology for the modeling of disruption events in the supply chain with heavy tailed distributions, which will allow the construction of models more closely linked to reality for risk management in the supply chain. © 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

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The supply chain event management application: a case study

2019 , Palma, Fanny , Saucedo, Jania A. , Marmolejo Saucedo, José Antonio , Rodríguez Aguilar, Román

A deviation from planned processes reveals the consequences that a disruption can cause in any area, even more a disruption with Ripple Effect (RE), which implied for the global Supply Chain (SC) when depends essentially from the stakeholders in all levels and chains. The learnt lessons from these tragical events show that many companies could not assess the impact and its side effects, therefore they cannot respond adequately, prolonging the crisis and expanding the disruption. A disruption evaluation model would allow to know from the beginning the potential impact to check carefully into the critical events to provide the necessary resources to control it. Hence, it is relevant that SC managers know and employ the right tools to focus on the control and the solution; as well to evaluate the impact and the disruption criticality level to mitigate and control the impact with total certainty that the appropriate actions are being taken according to the problematic. © 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

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