Production Line Virtualization Process Using Plant Simulation Tool




Optimization, Simulation, Plant Simulation, Engineering, Decision-Making


The constant changes in the world generate demands for improvements in processes, either by reducing costs or increasing capacity. One of the most used methods today for process optimization is Discrete Simulation. This research presents a discrete simulation application, using the Tecnomatix Plant Simulation software to simulate a production line in the Manaus Industrial Pole. Mathematical modeling made it possible to understand the parameters involved in the production process and worked as a guide for the production line's composition in the Plant Simulation environment. The production line modeled in Plant Simulation used real input data obtained in two months of production in 2020. The results obtained showed that the modeling reached the objective of virtualizing the production process, once that the differences between the simulation and the real process were at most 1.07%.


Download data is not yet available.

Author Biographies

José Henrique da Costa Queiroz Gonzalez, Federal University of Amazonas

Master Degree Student

Nelson Kuwahara, Federal University of Amazonas



BEHUNOVA, Annamaria; BEHUN, Marcel; KNAPCIKOVA, Lucia. (2018) Simulation software support of manufacturing processes in engineering industry. TEM Journal, Vol. 7, No. 4, pp. 849-854. Available at <>. (Accessed 15 April 2020).

DALENOGARE, Lucas Santos; BENITEZ, Guilherme Brittes; AYALA, Néstor Fabián; FRANK, Alejandro Germán. (2018). The expected contribution of Industry 4.0 technologies for industrial performance. International Journal of Production Economics 204, pp. 383-394. Available at <>. (Accessed 15 Apr 2020). DOI:

DANESHJO, Naqib; PAJERSKÁ, Erika Dudaš; KLIMEK, Miroslav, DANISHJOO, Enayat. (2018). Software support for optimizing layout solution in lean production. TEM Journal, Vol. 7, No. 1, pp. 33 - 40. Available at <>. (Accessed 15 April 2020).

DEBEVEC, Mihael; HERAKOVIC, Niko; SIMIC, Marko. (2014). Virtual Factory as an Advanced Approach for Production Process Optimization. International Journal of Simulation Modeling, Vol. 13, No. 1, pp.66-78. Available at: <>. (Accessed 15 April 2020). DOI:

DRAGOVIC, Branislav; TZANNATOS, Ernestos; PARK, Nam Kuy. (2017). Simulation modeling in ports and container terminals: literature overview and analysis by research field, application area and tool. Flexible Services and Manufacturing Journal, Vol. 29, No. 1, pp.4 – 34. Available at <>. (Accessed 15 April 2020). DOI:

DUMITRASCU, Nicolae-Adrian; DINCA, Alexandru; PREDINCEA, Nicolae. (2017). Virtual Commissioning of a Robotic Cell Using Tecnomatix Process Simulate. Annals of the Academy of Romanian Scientists. Series on Engineering Sciences. Vol. 9, No. 1. pp. 45 - 60. Available at: <>. (Accessed 07 April 2020).

GUERRERO, Luis Villagómez; LÓPEZ, Virgilio Vásquez; MEJÍA, Julián Echeverry. (2014). Virtual commissioning with process simulation (tecnomatix). Computer-aided design and applications. pp. 11 - 19. Available at: <>. (Accessed 07 April 2020). DOI:

KIKOLSKI, Mateusz. (2016). Identification of production bottlenecks with the use of plant simulation software. Economics and management, Vol. 8, No. 4, pp. 103-112. Available at <>. (Accessed 15 April 2020). DOI:

KLIMENT, Marek; TREBUňA, Peter. (2014). Simulation As An Appropriate Way Of Verifying The Efficiency Of Production Variants In The Design Of Production And Non-Production Systems. Acta Logistica - International Scientific Journal, Vol. 1, No. 4, pp.17-21. Available at: <>. (Accessed 21 April 2020). DOI:

O'REGAN, Gerard. (2016). Guide to Discrete Mathematics. An Accessible Introduction to the History, Theory, Logic and Applications. Ireland. Springer. DOI:

O'REGAN, Gerard. (2017). Concise Guide to Software Engineering. From Fundamentals to Application Methods. Ireland. Springer. DOI:

RODIČ, Blaž. (2017). Industry 4.0 and the New Simulation Modeling Paradigm. Organizacija. Vol 50, No. 3. pp. 193-207. Available at: <>. (Accessed 19 April 2019). DOI:

ROLLE, R.; MARTUCCI, V.; GODOY, E. (2020). Architecture for Digital Twin implementation Focusing on Industry 4.0. IEEE LATIN AMERICA TRANSACTIONS, Vol. 18, No. 5, pp.889-898. Available at: <>. (Accessed 02 July 2020). DOI:

ROSTKOWSKA, Marta. (2014). Simulation of Production Lines in the Education Of Engineers: How to Choose the Right Software? Management And Production Engineering Review, Vol. 5, No. 4, pp.53-65. Available at: <>. (Accessed 21 April 2020). DOI:

SIDERSKA, Julia. (2016). Application of Tecnomatix Plant Simulation for Modeling Production and Logistics Processes. Business, Management and Education. pp. 64 - 73. Available at: <>. (Accessed 25 March 2020). DOI:

ZHONG, Ray Y .; XU, Xun, KLOTZ, Eberhard, NEWMAN, Stephen T. (2017). Intelligent Manufacturing in the Context of Industry 4.0: A Review. Engineering. Vol 3, Issue 5, pp.616-630, ISSN 2095-8099. Available at: <(>. (Accessed 21 April 2020). DOI:




How to Cite

Gonzalez, J. H. da C. Q., & Kuwahara, N. (2021). Production Line Virtualization Process Using Plant Simulation Tool. International Journal for Innovation Education and Research, 9(9), 188–201.