eesti teaduste
akadeemia kirjastus
SINCE 1952
Proceeding cover
of the estonian academy of sciences
ISSN 1736-7530 (Electronic)
ISSN 1736-6046 (Print)
Impact Factor (2021): 1.024
Simulation based feasibility analysis of autonomously movable robot arm; pp. 422–428
PDF | 10.3176/proc.2021.4.08

Kristo Vaher, Kashif Mahmood, Tauno Otto, Jüri Riives

The use of industrial robots in production is rapidly growing. However, the vast use of industrial robots and implementation of new manufacturing technologies are mostly adopted by large industrial companies. It is due to the nature of the production volume, as robots perform a fair amount of the same work in one specific position in the production process. In smaller companies where robots do not often have sufficient workload in a single specific workplace, the process of robotization has not been so successful. SMEs (small and medium-sized enterprises) need a solution how the robot can be moved from one workplace to another in order to utilize the resources, such as a robot arm, efficiently. This paper aims to analyse the feasibility of the usage of a robotic arm (a col­laborative robot) to serve more than a single production cell intermittently. Production machines are located at a particular distance from each other and the movement of the robotic arm between the machines is carried out autonomously with the help of an autonomous mobile robot. Simulation and 3D visualization were used to conduct and analyse two different scenarios of an autonomously moving robot. Utilization of production equipment was considered as a key performance indicator.


1. Kangru, T., Riives, J., Mahmood, K. and Otto, T. Suitability analysis of using industrial robots in manufacturing. Proc. Est. Acad. Sci., 2019, 68(4), 383–388.

2. Barosz, P., Gołda, G. and Kampa, A. Efficiency analysis of manufacturing line with industrial robots and human operators. Appl. Sci., 2020, 10(8), 2862.

3. Unger, H., Markert, T. and Müller, E. Evaluation of use cases of autonomous mobile robots in factory environments. Procedia Manuf., 2018, 17, 254–261.

4. Vaher, K., Otto, T. and Riives, J. Positioning error correction of autonomously movable robot arm. J. Mach. Eng., 2020, 20(4), 152−160.

5. Mahmood, K., Lanz, M., Toivonen, V. and Otto, T. A performance evaluation concept for production systems in an SME network. Procedia CIRP, 2018, 72, 603–608.

6. Kangru, T., Riives, J., Otto, T., Pohlak, M. and Mahmood, K. Intelligent decision making approach for performance evalu­ation of a robot-based manufacturing cell. In Proceedings of the ASME 2018 International Mechanical Engineering Congress and Exposition: IMECE2018, Pittsburgh, PA, USA, November 9–15, 2018. ASME, IMECE2018-86666.

7. Lima, F., de Carvalho, C. N., Acardi, M. B. S., dos Santos, E. G., de Miranda, G. B., Maia, R. F. and Massote, A. A. Digital manufacturing tools in the simulation of collaborative robots: towards Industry 4.0. Braz. J. Oper. Prod. Manag., 2019, 16(2), 261–280.

8. Vaher, K., Kangru, T., Otto, T. and Riives, J. The mobility of robotised work cells in manufacturing. In Proceedings of the 30th International DAAAM Symposium “Intelligent Manufacturing & Automation”, Zadar, Croatia, October 23–26, 2019. DAAAM International, Vienna, 1049–1055.

9. Kousi, N., Michalos, G., Aivaliotis, S. and Makris, S. An outlook on future assembly systems introducing robotic mobile dual arm workers. Procedia CIRP, 2018, 72, 33–38.

10. Nielsen, I. E., Dang, Q. V., Bocewicz, G. and Banaszak, Z. A methodology for implementation of mobile robot in adaptive manufacturing environments. J. Intell. Manuf., 2017, 28(5), 1171–1188.

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