A Simulation-Based Tool to Support Decision-Making in Logistics Design of a Can Packaging Line
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Victoria G. Achkar
Victoria G. Achkar is an industrial engineer and PhD student at the National Scientific and Technical Research Council (CONICET). Her research interests include hybrid simulation & optimization tools for logistic management of complex production and distribution processes of industrial interest.
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Valentina Bär
Valentina Bär is an advanced industrial engineering student conducting research in optimization and simulation tools for production planning and scheduling of automated production systems.Franco Cornú is an advanced industrial engineering student conducting research in optimization and simulation tools for production planning and scheduling of automated production systems.Dr Carlos A. Méndez is a titular professor of Industrial Engineering at Universidad Nacional del Litoral (UNL) in Argentina as well as a senior researcher of the National Scientific and Technical Research Council (CONICET) in the area of Process Systems Engineering. He has published over 200 refereed journal articles, book chapters and conference papers. His research and teaching interests include modeling, simulation and optimization tools for production planning and scheduling, vehicle routing and logistics. His group’s web page ishttp://servicios.intec.santafe-conicet.gob.ar/grupos/capse/ .
Abstract
This study proposes an advanced discrete-event simulation-based tool to support decision-making in the internal logistic design of a packaging line of a multinational brewery company. The selected software, Simio, allows emulating, advising and predicting the behavior of complex real-world systems. The simulation model provides a 3D interface that facilitates verification and validation. In this work, the designed model is used to understand the dynamic interactions between multiple factors and performance measures including both material-handling and inventory systems and to define necessary quantities and/or capacities of resources for a future can packaging line. Based on the proposed model, a what-if analysis is performed to determine inventory threshold values and other critical variables in order to optimize the configuration of internal logistics in potential scenarios.
Funding source: CONICET, Universidad Nacional del Litoral
Award Identifier / Grant number: 112 20150100641
Award Identifier / Grant number: 2016-UNL/PIC
Funding statement: The authors gratefully acknowledge the financial support from CONICET: [Grant Number PIP 112 20150100641] and from Universidad Nacional del Litoral: [Grant Number CAI+D 2016-UNL/PIC 50420150100101LI].
About the authors
Victoria G. Achkar is an industrial engineer and PhD student at the National Scientific and Technical Research Council (CONICET). Her research interests include hybrid simulation & optimization tools for logistic management of complex production and distribution processes of industrial interest.
Valentina Bär is an advanced industrial engineering student conducting research in optimization and simulation tools for production planning and scheduling of automated production systems.
Franco Cornú is an advanced industrial engineering student conducting research in optimization and simulation tools for production planning and scheduling of automated production systems.
Dr Carlos A. Méndez is a titular professor of Industrial Engineering at Universidad Nacional del Litoral (UNL) in Argentina as well as a senior researcher of the National Scientific and Technical Research Council (CONICET) in the area of Process Systems Engineering. He has published over 200 refereed journal articles, book chapters and conference papers. His research and teaching interests include modeling, simulation and optimization tools for production planning and scheduling, vehicle routing and logistics. His group’s web page is http://servicios.intec.santafe-conicet.gob.ar/grupos/capse/.
Appendix
A Glossary
Path (Figure 15): used to define a pathway between two node locations where the travel time is determined by the path length and a traveler’s speed. Entities or vehicles can go through it. Some of its properties are speed, capacity and length.
Path module and characteristics.
Server (Figure 16): represents a processing activity in the model. Among its properties, there are processing time, resources needed failures, internal process and events associated.
Server module and characteristics.
Sink: represents a final point in the model where entities go to be eliminated.
Vehicle (Figure 17): transports entities from one point to another. It has assigned a pick up and drops off point. Other properties are speed, loading and unloading time and capacity.
Vehicle module and characteristics.
Workstation: represents a more complex server. It has properties such as setup time and it considers consumption and production of materials based on a BOM matrix.
Internal logic process (Figure 18): A sequence of commands that dictate the behavior of an object. It allows including some tasks into standard modules in order to custom them such as seizing or releasing resources, assigning variables and firing events [6].
Path module and characteristics.
References
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Supplementary Material
The online version of this article offers supplementary material (DOI:https://doi.org/10.1515/ijfe-2017-0089).
© 2019 Walter de Gruyter GmbH, Berlin/Boston
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Articles in the same Issue
- Editorial
- Special issue “Selected papers from the International Food Operations & Processing Simulation Workshop”
- Articles
- Economic Assessment of Pig Meat Processing and Cutting Production by Simulation
- A Simulation-Based Tool to Support Decision-Making in Logistics Design of a Can Packaging Line
- Word of Mouth, Viral Marketing and Open Data: A Large-Scale Simulation for Predicting Opinion Diffusion on Ethical Food Consumption
- Development of a Dynamic Information Fractal Framework to Monitor and Optimise Sustainability in Food Distribution Network
- Estimating the Impact of Blockchain Adoption in the Food Processing Industry and Supply Chain
- Developing a Linearization Method to Determine Optimum Blending for Surimi with Varied Moisture Contents Using Linear Programming
- Developing an Accurate Heat Transfer Simulation Model of Alaska Pollock Surimi Paste by Estimating the Thermal Diffusivities at Various Moisture and Salt Contents
- Utilisation of the REA-method to a Convective Drying of Apple Rings at Ambient Temperature
- Shelf life analysis of a ricotta packaged using Modified Atmosphere Packaging or High Pressure Processing
