Integration of ROS and Tecnomatix for the development of digital twins based decision-making systems for smart factories

Authors

  • Carolina Saavedra Sueldo INTELYMEC, Centro de Investigaciones en Física e Ingeniería del Centro –UNICEN – CICpBA – CONICET
  • Sebastian Aldo Villar INTELYMEC, Centro de Investigaciones en Física e Ingeniería del Centro –UNICEN – CICpBA – CONICET
  • Mariano De Paula INTELYMEC, Centro de Investigaciones en Física e Ingeniería del Centro –UNICEN – CICpBA – CONICET https://orcid.org/0000-0001-7582-9188
  • Gerardo Gabriel Acosta INTELYMEC, Centro de Investigaciones en Física e Ingeniería del Centro –UNICEN – CICpBA – CONICET

Keywords:

Digital Twin, Autonomous Decision System, industry 4.0, Integration, Tecnomatix

Abstract

Digital twins employs simulation in conjunction with virtual environments and a variety of data coming from different plant equipment and physical systems to continuously update the digital models of the world in a feedback loop scheme to facilitate the decision-making processes. The heterogeneity of existing hardware and software requires the development of software architectures able to deal with the information exchange due to the integration and interaction of several system components and autonomous decision-making systems. In this work we propose the design and construction of a software architecture that integrates a manufacturing process simulator with the well-known robot operating system (ROS-Robot Operating System) to easily interchange information with an autonomous decision-making system. The proposal is tested with the simulator Tecnomatix and the free distribution ROS Melodic. We present an instance of software architecture for a typical complex case study of manufacturing plants and demonstrate its easy integration with an autonomous decision-making system based on the reinforcement- learning paradigm.

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Author Biographies

Carolina Saavedra Sueldo, INTELYMEC, Centro de Investigaciones en Física e Ingeniería del Centro –UNICEN – CICpBA – CONICET

Nació en Olavarría, Buenos Aires, Argentina en 1989. Se graduó como Ingeniera Industrial en 2014, por la Universidad Nacional del Centro de la Pcia. De Buenos Aires y desde el año 2019 es estudiante del Doctorado en Ingeniería, mención Tecnología Elctromecánica de la misma Universidad. Como becaria doctoral de la CIC, sus investigaciones se centran en la Industria 4.0 y en el uso de técnicas de simulación e inteligencia artificial para el desarrollo de gemelos digitales.

Sebastian Aldo Villar, INTELYMEC, Centro de Investigaciones en Física e Ingeniería del Centro –UNICEN – CICpBA – CONICET

Ingeniero en Sistemas en la Facultad de Ciencias Exactas de la Universidad Nacional Centro de la Provincia de Buenos Aires (UNCPBA), Argentina (2009), y de la Maestría en Administración de Empresas (MBA) en la Facultad de Ciencias Económicas de la UNCPBA (2011), y doctor en Ingeniería en la Facultad de Ingeniería de la UNCPBA (2014). También investigador asistente de la Comisión de Investigaciones Científicas de la Provincia de Buenos Aires (CICBA), trabajando en el Grupo de Ingeniería INTELYMEC del Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aires (CIFICEN). Tema principal de interés procesamiento de imágenes Robótica, SONAR (Av. Del Valle 5737-B7400JWI Olavarría; Argentina), UNCPBA. svillar@fio.unicen.edu.ar.

Mariano De Paula, INTELYMEC, Centro de Investigaciones en Física e Ingeniería del Centro –UNICEN – CICpBA – CONICET

Ingeniero Industrial, graduado en la Facultad de Ingeniería de la Universidad Nacional del Centro de la Provincia de Buenos Aires (UNCPBA), Argentina (2007). Se ha graduado como Doctor en Ingeniería en la Universidad Tecnológica Nacional (UTN-FRSF), Argentina (2013). Es miembro investigador del Concejo Nacional de Investigaciones Científicas y Técnicas de Argentina (CONICET) y desempeña su actividad en el grupo INTELYMEC (Av. del Valle 5737-B7400JWI Olavarría; Argentina), UNCPBA. Además, se desempeña como profesor en la Facultad de Ingeniería de la UNCPBA. mariano.depaula@fio.unicen.edu.ar, marianodepauala@gmail.com.

Gerardo Gabriel Acosta, INTELYMEC, Centro de Investigaciones en Física e Ingeniería del Centro –UNICEN – CICpBA – CONICET

Ingeniero en Electrónica por la Universidad Nacional de La Plata, Argentina (1988) y Doctor en Informática por la Universidad de Valladolid, España (1995). Es Profesor Titular en Sistemas de Control y Director del Programa de Doctorado en la Facultad de Ingeniería de la Universidad Nacional del Centro de la Provincia de Buenos Aires (UNCPBA), Argentina. Investigador Independiente del Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Argentina, Director del Grupo de Investigación y Desarrollo "INTELYMEC", en la FI-UNCPBA e integrante del Consejo Directivo del CIFICEN (UNCPBA – CICPBA – CONICET). Sus intereses de trabajo comprenden el uso de la inteligencia computacional en el control automático, particularmente las técnicas de control inteligente en robótica, terrestre y subacuática. Cuenta con más de ciento ochenta publicaciones y dos registros de propiedad intelectual en éste y otros temas relacionados. Ha sido premiado con el segundo premio INNOVAR 2011 en Robótica, por el robot autónomo CARPINCHO, y con el primer premio INNOVAR 2012 en Robótica por el vehículo autónomo submarino ICTIOBOT, ambos desarrollados en el INTELYMEC-UNCPBA. Es Senior Member del IEEE desde 2001, Presidente del Capítulo Argentino de CIS IEEE (2007-2008), recibiendo el Premio 2010 al Capítulo Sobresaliente, y uno de los socios fundadores. También es socio fundador y actual presidente del Capítulo Argentino de OES IEEE, establecido en 2011, y forma parte del Administrative Committee de la OES de IEEE por el período 2015-2016 y 2018-2023. Forma parte de Ad Hoc Strategic Planning Committee de dicha sociedad y es editor asociado en temas oceánicos de la revista EARTHZINE patrocinada por IEEE OES. Ha liderado más de quince proyectos de I + D, financiados por el Gobierno argentino, el Gobierno español y la Unión Europea. Ha sido invitado como profesor de programas de doctorado en Argentina y España, y actualmente es Director del programa de doctorado en la Facultad de Ingeniería-UNCPBA. Actúa como revisor y miembro del comité científico de varias revistas y conferencias nacionales e internacionales.

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Published

2021-03-29

How to Cite

Saavedra Sueldo, C., Villar, S. A., De Paula, M., & Acosta, G. G. (2021). Integration of ROS and Tecnomatix for the development of digital twins based decision-making systems for smart factories. IEEE Latin America Transactions, 19(9), 1546–1555. Retrieved from https://latamt.ieeer9.org/index.php/transactions/article/view/4925