Abstract
This paper presents an experimental study of different approaches for disassembling an end-of-life (EOL) product, using a computer as an example, we have conceived a disassembly line consisting of two stations, where the first station is dedicated only to remove the screws through a human operator, whereas the second station is assigned to extract the desired components via two human operators. In the case study, three different approaches will be carried out, beginning with the manual disassembly method as a reference, given that this technique is the most used worldwide, then followed by robotic disassembly using a computer, Finally, a human-robot collaborative approach in which the human and the robot will simultaneously work at the extraction station. Tasks will be allocated to determine which task is best suited to everyone. The main contribution of this work is to determine the optimal disassembly method based on time, making the process more adaptable and efficient.
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References
BASEL CONVENTION, Controlling transboundary movements of hazardous wastes and their disposal. https://www.basel.int/Implementation/Ewaste/Overview/tabid/4063/Default.aspx
Ylä-Mella, J., Keiski, R.L., Pongrácz, E.: End-of-Use vs. End-of-Life: when do consumer electronics become waste? Resources 11, 18 (2022). https://doi.org/10.3390/resources11020018
Walle, A.H.: Remanufacturing marketing strategies and developing countries. J. Glob. Mark. 1, 75–90 (1988)
Wang, Y.: Robotic disassembly and remanufacturing automation. In: 2022 27th International Conference on Automation and Computing (ICAC), p. 1 (2022)
Torres, F., Gil, P., Puente, S.T., et al.: Automatic PC disassembly for component recovery. Int. J. Adv. Manuf. Technol. 23, 39–46 (2004). https://doi.org/10.1007/s00170-003-1590-5
Torres, F.: Santiago Puente Intelligent disassembly in the demanufacturing process. https://rua.ua.es/dspace/bitstream/10045/7315/3/Intelligent_Disassembly.pdf
Umeda, Y., Miyaji, N., Shiraishi, Y., Fukushige, S.: Proposal of a design method for semi-destructive disassembly with split lines. CIRP Ann. 64(1), 29–32 (2015). https://doi.org/10.1016/j.cirp.2015.04.045
ElSayed, A., Kongar, E., Gupta, S.M., et al.: A robotic-driven disassembly sequence generator for end-of-life electronic products. J. Intell. Robot. Syst. 68, 43–52 (2012). https://doi.org/10.1007/s10846-012-9667-8
Meng, K., Guiyin, X., Peng, X., Kamal Youcef-Toumi, J., Li, I.: Intelligent disassembly of electric-vehicle batteries: a forward-looking overview. Resour. Conserv. Recycling 182, 106207 (2022). https://doi.org/10.1016/j.resconrec.2022.106207
Prioli, J.P.J., Rickli, J.L.: Collaborative robot based architecture to train flexible automated disassembly systems for critical materials. Procedia Manuf. 51, 46–53 (2020). https://doi.org/10.1016/j.promfg.2020.10.008
Foo G., Kara S., Pagnucco M.: Challenges of robotic disassembly in practice. Procedia CIRP 105, 513–518 (2022)
Mete, S., Çil, Z.A., Özceylan, E., Ağpak, K.: Resource constrained disassembly line balancing problem. IFAC-PapersOnLine 49(12), 921–925 (2016). https://doi.org/10.1016/j.ifacol.2016.07.893
Ren, Y., Meng, L., Zhang, C., Lu, Q., Tian, G.: Multi-criterion decision making for disassembly line balancing problem. Procedia CIRP 80, 542–547 (2019). https://doi.org/10.1016/j.procir.2019.01.008
Duta, L., Filip, F.G., Caciula, I.: Real time balancing of complex disassembly lines. IFAC Proc. 41(2), 913–918 (2008). https://doi.org/10.3182/20080706-5-KR-1001.00156
HezerKara, S.: A network-based shortest route model for parallel disassembly line balancing problem. Int. J. Prod. Res. 53(6), 1849–1865 (2015). https://doi.org/10.1080/00207543.2014.965348
Bushehri, F.I.: UNEP’s role in promoting environmentally sound management of e-waste. In: 5th ITU Symposium on ‘‘ICTs, the Environment and Climate Change’’ Cairo, Egypt (2010)
Md IslamHuda, T.: Material flow analysis (MFA) as a strategic tool in E-waste management: Applications, trends and future directions. J. Environ. Manage. 244(15), 344–361 (2019). https://doi.org/10.1016/j.jenvman.2019.05.062
Movilla, N.A., Zwolinski, P., Dewulf, J., Mathieux, F.: A method for manual disassembly analysis to support the ecodesign of electronic displays. Resour. Conserv. Recycling 114, 42–58 (2016). https://doi.org/10.1016/j.resconrec.2016.06.018
Kopacek, P., Kopacek, B.: Intelligent, flexible disassembly. Int. J. Adv. Manuf. Technol. 30, 554–560 (2006). https://doi.org/10.1007/s00170-005-0042-9
Lambert, A.J.D.: Disassembly sequencing: a survey. Int. J. Prod. Res. 41(16), 3721–3759 (2003). https://doi.org/10.1080/0020754031000120078
Knoth, R., Brandstotter, M., Kopacek, B., Kopacek, P.: Automated disassembly of electr(on)ic equipment. In: Conference Record 2002 IEEE International Symposium on Electronics and the Environment (Cat. No.02CH37273), San Francisco, CA, USA, pp. 290–294 (2002).https://doi.org/10.1109/ISEE.2002.1003282
Santochi, M., Dini, G., Failli, F.: Disassembly for recycling, maintenance and remanufacturing: state of the art and perspectives. In: Kulianic, E. (eds) AMST’02 Advanced Manufacturing Systems and Technology. International Centre for Mechanical Sciences, vol. 437. Springer, Vienna (2002). https://doi.org/10.1007/978-3-7091-2555-7_6
Letcher, B.: Old and new LCD television assemblies—disassembly differences. Report of the project sustainable recycling of flat panel displays—project HÅPLA a Swedish initiative towards a comprehensive solution, Private communication (2011)
Seliger, G., Keil, T., Rebafka, U., Stenzel, A.: Flexible disassembly tools. In: Proceedings of the 2001 IEEE International Symposium on Electronics and the Environment. 2001 IEEE ISEE (Cat. No.01CH37190), Denver, CO, USA, pp. 30–35 (2001). https://doi.org/10.1109/ISEE.2001.924498
Guo, X., Bi, Z., Wang, J., Qin, S., Liu, S., Qi, L.: Reinforcement learning for disassembly system optimization problems: a survey. Int. J. Network Dyn. Intell. 2(1), 1–14 (2023). https://doi.org/10.53941/ijndi0201001
Brogan, D., DiFilippo, N., Jouaneh, M.: ‘Deep learning computer vision for robotic disassembly and servicing applications.’ Array 12, 100094 (2021). https://doi.org/10.1016/j.array.2021.100094
Deng, W., Liu, Q., Pham, D., Hu, J., Lam, K., Wang, Y., Zhou, Z.: Predictive exposure control for vision-based robotic disassembly using deep learning and predictive learning. Robot. Comput.-Integr. Manuf., 85 (2024). https://doi.org/10.1016/j.rcim.2023.102619
Javier Ramírez, F., Aledo, J.A., Gamez, J.A., Pham, D.T.: Economic modelling of robotic disassembly in end-of-life product recovery for remanufacturing. Comput. Ind. Eng. 142, 106339 (2020). https://doi.org/10.1016/j.cie.2020.106339
Chen, W.H., Wegener, K., Dietrich, F.: A robot assistant for unscrewing in hybrid human-robot disassembly. In: 2014 IEEE International Conference on Robotics and Biomimetics (ROBIO 2014), Bali, Indonesia, pp. 536–541 (2014). https://doi.org/10.1109/ROBIO.2014.7090386
Huang, J., Pham, D.T., Wang, Y., et al.: A case study in human–robot collaboration in the disassembly of press-fitted components. Proc. Instit. Mech. Eng. Part B: J. Eng. Manuf. 234(3), 654–664 (2020). https://doi.org/10.1177/0954405419883060
Li, R., et al.: Unfastening of hexagonal headed screws by a collaborative robot. IEEE Trans. Autom. Sci. Eng. 17(3), 1455–1468 (July 2020). https://doi.org/10.1109/TASE.2019.2958712
System service parts listing - IBM IntelliStation Z Pro (Type 6899). https://www.ibm.com/support/pages/system-service-parts-listing-ibm-intellistation-z-pro-type-6899
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Ameur, S., Tabaa, M., Hamlich, M., Hidila, Z., Bearee, R. (2024). Human-Robot Collaboration in Remanufacturing: An Application for Computer Disassembly. In: Hamlich, M., Dornaika, F., Ordonez, C., Bellatreche, L., Moutachaouik, H. (eds) Smart Applications and Data Analysis. SADASC 2024. Communications in Computer and Information Science, vol 2168. Springer, Cham. https://doi.org/10.1007/978-3-031-77043-2_6
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