Rodríguez Aguilar, Román
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Preferred name
Rodríguez Aguilar, Román
Official Name
Rodríguez Aguilar, Román
Alternative Name
Rodríguez-Aguilar, Román
Rodríguez-Aguilar, R.
Aguilar, R.R.
Rodriguez-Aguiler, R.
Rodríguez, R.
Roman, R.A.
Main Affiliation
ORCID
Scopus Author ID
56717663000
Researcher ID
AAO-6158-2020

Research Output
Now showing 1 - 3 of 3
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Technical evaluation of the opening of facilities in the pharmaceutical industry: optimization to supply chain in Mexico

2019 , Marmolejo Saucedo, José Antonio , Rodríguez Aguilar, Román , Manuell-Barrera, Ofelia S. G.

The pharmaceutical industry is going through a difficult time in Mexico. Despite all the advances and improvements in the methods of production, storage and distribution, many pharmaceutical companies still struggle to meet market demand effectively and consistently. The risks faced by the supply chain of the pharmaceutical industry are diverse and typical of an industry dedicated to health care. So, the location to locate new facilities includes several strategic and tactical decisions that must consider aspects of production, distribution, material flow, optimal inventory, the perishability of products, safety, among other factors. The application of robust hybrid models will allow obtaining the best solutions, taking into account the network optimization, greenfield analysis and risk scenarios. This paper presents a case study for a pharmaceutical company that operates in Mexico and plans to expand its operations seeking the optimal operation of the supply chain. The inherent risks to a supply chain of pharmaceutical products, different scenarios and parameters were considered, which will allow making decisions based on technical evidence in order to improve the performance of the company. Modelling the expansion of operations and the performance of the supply chain was carried out using the specialized software Anylogistix. © 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

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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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