Discrete event simulation and ergonomic software for the design of a visual testing system in an automatized workshop of jacket nodes

Abstract

Offshore wind power is poised to make a major difference to decarbonizing the energy sector yet still faces a certain degree of uncertainty with respect to its eventual cost competitiveness. In the case of jacket foundations, the leap from manual to robotized node welding may lead to a reduction of 30% in terms of manufacturing costs. For this reason, in this paper we present a case study where we have used the 3D discrete event simulator FlexSim along with the ergonomic package Tecnomatix Jack to design and optimize the implementation of a new visual test system for jacket nodes. This system will be integrated by NAVANTIA to a future workshop which is a fundamental investment in its medium-term roadmap. To this end, after the definition and creation of several scenarios in FlexSim to analyze the new production system, we developed detailed 3D animations of the worker performance. These animations raised the need for a more detailed ergonomic study. Hence, we then performed RULA analyses of the task with Tecnomatix Jack and proposed more ergonomic alternatives out of them. Finally, we adopted these changes into new 3D animation in FlexSim and obtained a final integrated model.

Keywords

• Discrete Event Simulation
• Ergonomic analysis
• Industry 4.0
• Jackets nodes welding
• Offshore wind

References

1. [1] Sun, X., Huang, D., & Wu, G. The current state of offshore wind energy technology development 2012. Energy, 41(1): 298–312. DOI: 10.1016/j.energy.2012.02.054.
2. [2] Poudineh, R., Brown, C., Foley, B., Poudineh, R., Brown, C., & Foley, B. Global offshore wind market 2017. Econ. Offshore Wind Power. 15–31. DOI: 10.1007/978-3-319-66420-0_2.
3. [3] Ramirez, L., Fraile, D., & Brindley, G. Offshore wind in Europe - Key trends and statistics 2019. DOI: 10.1016/s1471-0846(02)80021-x.
4. [4] International Energy Agency, Offshore wind outlook 2019 – Analysis - IEA. [Online]. Available: https://www.iea.org/reports/offshore-wind-outlook-2019.
5. [5] W. Energy and O. Special. Off shore Wind Outlook 2019.
6. [6] Milborrow, D.J. Wind energy: A technology that is still evolving 2011. Proc. Inst. Mech. Eng. Part A J. Power Energy, 225(4): 539–547. DOI: 10.1177/0957650910395874.
7. [7] Dvorak, P. Global wind network updates state of U.S. wind-turbine manufacturing for onshore and off 2014. https://www.windpowerengineering.com/global-wind-network-updates-state-u-s-wind-turbine-manufacturing-onshore/ (accessed Mar. 23, 2020).
8. [8] Sustainability in jacket structures for offshore wind energy plants | Automated node welding, maintenance-free corrosion protection 2020. https://magazin.mannesmann-linepipe.com/en/04-2016/coverstory/energy-plants/ (accessed Mar. 23, 2020).

9. [9] Laudante, E. Industry 4.0, Innovation and Design. A new approach for ergonomic analysis in manufacturing system 2017. Des. J., vol. 20, no. sup1, pp. S2724–S2734. DOI: 10.1080/14606925.2017.1352784.
10. [10] Dangelmaier, W., Fischer, M., Gausemeier, J., Grafe, M., Matysczok, C., & Mueck, B. Virtual and augmented reality support for discrete manufacturing system simulation 2005. Comput. Ind., 56(4): 371–383, DOI: 10.1016/j.compind.2005.01.007.
11. [11] Lasi, H., Fettke, P., Kemper, H.G., Feld, T., & Hoffmann, M. Industry 4.0 2014. Bus. Inf. Syst. Eng., vol. 6, pp. 239–242. doi: 10.1007/s12599-014-0334-4.
12. [12] Muhabie, Y.T., Rigo, P., Cepeda, M., D’Agosto, M. de A., & Caprace, J.D. A discrete-event simulation approach to evaluate the effect of stochastic parameters on offshore wind farms assembly strategies 2018. Ocean Eng., vol. 149, pp. 279–290. DOI: 10.1016/j.oceaneng.2017.12.018.
13. [13] Rodríguez, A.L., Pereira, D.C., & Tutor, R.T. Discrete events simulation to improve manufacturing process of jackets offshore structures 2016. In 15th International Conference on Modeling and Applied Simulation, MAS 2016, pp. 85–94.
14. [14] Rodríguez. A.L., Álvarez, D.C., & Muiña Dono, J.A. 3D discrete events simulation to evaluate the internal logistic strategies in a shipyard 2019. pp. 73–86.
15. [15] Rodríguez, A.L., Álvarez, D.C., & Muiña-Dono J.A. Analysis of resource management methodologies for the development of discrete event simulation models representative of the works developed in shipyards 2018. In 30th European Modeling and Simulation Symposium, EMSS 2018, pp. 187–193.
16. [16] Li, X., Han, S., Gül, M., & Al-Hussein, M. Automated post-3D visualization ergonomic analysis system for rapid workplace design in modular construction 2019. Autom. Constr., vol. 98, no. February 2019, pp. 160–174. doi: 10.1016/j.autcon.2018.11.012.
17. [17] Pekarčíková, M., Trebuňa, P., Kronová, J., & Ižariková, G. The Application of software tecnomatix jack for design the ergonomics solutions 2018. In Intelligent Systems in Production Engineering and Maintenance, C. Springer, Ed., pp. 325–336.
18. [18] Pekarčíková, M., Trebuňa, P., Popovič, R., & Kliment, M.utilization of the software product tecnomatix jack in optimizing of working activities 2015. Int. Sci. J. about Simul., 1(4): 5–11.
19. [19] Peruzzini, M., Carassai, S., & Pellicciari, M. The benefits of human-centred design in industrial practices: re-design of workstations in pipe industry 2017. Procedia Manuf., vol. 11, pp. 1247–1254. DOI: 10.1016/j.promfg.2017.07.251.
20. [20] Caputo, F., Greco, A., Fera, M., & Macchiaroli, R. Digital twins to enhance the integration of ergonomics in the workplace design 2019. Int. J. Ind. Ergon., vol. 71, pp. 20–31. DOI: 10.1016/j.ergon.2019.02.001.
21. [21] Budiyanto, T., Adiputra, N., Sutjana, I.D.P., & Tirtayasa, K. Application of RULA analysis on work posture improvement to reduce workers’ fatigue and musculoskeletal complaints and to accelerate processing time of wok molding 2019. Int. Res. J. Eng. IT Sci. Res., 5(4): 8–15. DOI: 10.21744/irjeis.v5n4.648.
22. [22] Medina Barrón, K.F., Realyvásquez Vargas, A., & Torres López, A. Ergonomic study of the final quality inspection process based on the rula method in an aerospace product company in the city of tijuana 2019. In Ergonomía Ocupacional Investigaciones Y Aplicaciones, vol. 12, pp. 569–575.
23. [23] Gómez-Galán, M., Callejón-Ferre, Á.J., Pérez-Alonso, J., Díaz-Pérez, M., & Carrillo-Castrillo, J. A. Musculoskeletal risks: RULA bibliometric review 2020. Int. J. Environ. Res. Public Health, 17(2): 1–52. DOI: 10.3390/ijerph17124354.
24. [24] Ramli, R. Work posture analysis of welding workers using the rula method 2020. J. la medihealtico, 1(1): 13–23. doi: 10.37899/journallamedihealtico.v1i1.15.
25. [25] Robinson, S. Simulation: The practice of model developmentand use 2004. John Wiley & Sons.