Published date: Jan 30 2018

Journal Title: KnE Engineering

Issue title: Simposio Iberoamericano en Programación Informática (Ibero-American Symposium on Computer Programming)

Pages: 179-191

DOI: 10.18502/keg.v1i2.1494

Iván Menes Camejo

Gladys Lorena Aguirre Sailema

Katherine Maribel Gallegos Carrillo

Jorge Ariel Menéndez Verdecia

Abstract. Computational simulation is a powerful tool that allows the experimentation of variants in production environments, which made on real scenarios, would entail heavy costs for the company. For this, it is necessary to correctly define the model that represents the actual processes involved. This paper presents the development of a computational simulation model, developed with "Siman" programming language and "Arena" software, based on queuing theory for the processes of milk production process in the Dairy Plant FCP-ESPOCH. We sought to determine the efficiency of the computational model using the scientific method, techniques of descriptive statistics and hypothesis demonstration. The results indicate that the data of the model are similar to the real ones in the processes of Daily Crude Milk Reception and Production Daily Pasteurized Milk, concluding that the computational model is valid for future experimentation.

[1] Pazos J., Andrés S. y Rebeca D.: Teoría de colas y simulación de eventos discretos. Pearson Educación (2003).


[2] Banks J., Carson J., Nelson B. y Nicol D.: Discrete-event system simulation. Prentice Hall (2001).


[3] Naylor T., Balinffy J., Burdick D. y Chu K.: Computer Simulation Techniques. John Wiley & Sons, Inc (1966).


[4] Kelton D., Sadowski R. y Sadowski D.: Simulation with ARENA. McGraw Hill (2002).


[5] Rockwell Automation, ¿rockwellautomation,¿ [En línea]. Available: http://www.rockwellautomation.com/. [Último acceso: marzo 2012].


[6] Pegden D.: Introduction to SIMAN. Systems Modeling Corporation (1984).


[7] Fishman G.: Concepts and Methods in Discrete Event Digital Simulation. John Wiley & Sons Inc (1973).


[8] Guasch A., Piera M., Casanovas J. y Figueras J.: Modelado y simulación: aplicación a procesos logísticos de fabricación y servicios. Edicions UPC (2002).


[9] Glover F., April J., Kelly J. y Laguna M.: Simulation-based optimization: practical introduction to simulation optimization. Winter Simulation Conference (2003) 71- 78.


[10] Menes I.: Texto Básico Técnicas de Simulación. ESPOCH Riobamba (2007).


[11] Feller W.: Introduction to Probability Theory and Its Applications. John Wiley & Sons, Inc (1968).


[12] Morse P.: Queues, Inventories and Maintenance: The Analysis of Operational Systems with Variable Demand and Supply. Dover Publications (2004).


[13] Saaty T.: Elements of Queueing Theory. McGraw-Hill New York (1961).


[14] Jun Son Y. y A Wysk R.: Automatic simulation model generation for simulationbased, real-time shop floor control. Computers in Industry (2001) 291-308.


[15] Gordon G.: System Simulation. Prentice-Hall New Yersey (1969).


[16] Saaty T.: Mathematical Methods of Operations Research. Dover Publications (2004)