AI-based decision support system for enhancing end-of-life value recovery from e-wastes

References

• Andersen, M. S. 2007. “An Introductory Note on the Environmental Economics of the Circular Economy.” Sustainability Science 2 (1): 133–140. https://doi.org/10.1007/s11625-006-0013-6.
   Web of Science ®Google Scholar
• Behdad, S., L. P. Berg, D. Thurston, and J. Vance. 2012. Integrating Immersive Computing Technology with Mixed-Integer Nonlinear Programming for Disassembly Sequence Planning Under Uncertainty. International Design Engineering Technical Conferences & Computers and Information in Engineering Conference (IDETC/CIE), August 2012, Chicago, Illinois, 1–9. https://doi.org/10.1115/DETC2012-70392.
   Google Scholar
• Behdad, S., L. P. Berg, D. Thurston, and J. Vance. 2014. “Leveraging Virtual Reality Experiences with Mixed-Integer Nonlinear Programming Visualization of Disassembly Sequence Planning Under Uncertainty.” Journal of Mechanical Design 136 (4): 041005. https://doi.org/10.1115/1.4026463.
   Web of Science ®Google Scholar
• Bentaha, M. L., O. Battaiä, and A. Dolgui. 2015. “An Exact Solution Approach for Disassembly Line Balancing Problem Under Uncertainty of the Task Processing Times.” International Journal of Production Research 53 (6): 1807–1818. https://doi.org/10.1080/00207543.2014.961212.
   Web of Science ®Google Scholar
• Bogue, R. 2019. “Robots in Recycling and Disassembly.” Industrial Robot 46 (4): 461–466. https://doi.org/10.1108/IR-03-2019-0053.
   Web of Science ®Google Scholar
• de Almeida, S. T., M. Borsato, and C. M. Lie Ugaya. 2017. “Application of Exergy-Based Approach for Implementing Design for Reuse: The Case of Microwave Oven.” Journal of Cleaner Production 168:876–892. https://doi.org/10.1016/j.jclepro.2017.09.034.
   Web of Science ®Google Scholar
• Difilippo, N. M., and M. K. Jouaneh. 2019. “Using the Soar Cognitive Architecture to Remove Screws from Different Laptop Models.” IEEE Transactions on Automation Science and Engineering 16 (2): 767–780. https://doi.org/10.1109/TASE.2018.2860945.
   Web of Science ®Google Scholar
• European Commission Environment. 2011. European Commission Environment: Integrated Product Policy (IPP). European Commission. https://ec.europa.eu/environment/ipp/index_en.htm.
   Google Scholar
• Eurostat. (2021). Eurostat. Recycling Rate of E-Waste. https://ec.europa.eu/eurostat/databrowser/view/t2020_rt130/default/bar?lang=en.
   Google Scholar
• Forti, V., C. P. Baldé, R. Kuehr, G. Bel, S. Adrian, M. Brune Drisse, Y. Cheng, L. Devia, O. Deubzer, F. Goldizen, J. Gorman, S. Herat, S. Honda, G. Iattoni, W. Jingwei, L. Jinhui, D.S. Khetriwal, J. Linnell, F. Magalini, I.C. Nnororm, P. Onianwa, D. Ott, A. Ramola, U. Silva, R. Stillhart, D. Tillekeratne, V. Van Straalen, M. Wagner, T. Yamamoto, and X. Zeng. 2020. The Global E-waste Monitor 2020. United Nations University (UNU)/United Nations Institute for Training and Research (UNITAR). https://www.itu.int/en/ITU-D/Environment/Documents/Toolbox/GEM_2020_def.pdf.
   Google Scholar
• Friedrich, C., A. Lechler, and A. Verl. 2016. The Control Architecture RoVidiasS - a Robotic Visual Disassembly and Assembly System. Proceedings of the IEEE International Conference on Industrial Technology, 2016-May, 113–118. https://doi.org/10.1109/ICIT.2016.7474735
   Google Scholar
• Grimes, S. M., and D. Maguire. 2020. “Assessment of Priorities in Critical Material Recovery from Waste Electrical and Electronic Equipment.” Resources Policy 68 (May): 101658. https://doi.org/10.1016/j.resourpol.2020.101658.
   Google Scholar
• Herrmann, C., A. Raatz, M. Mennenga, J. Schmitt, and S. Andrew. 2012. “Assessment of Automation Potentials for the Disassembly of Automotive Lithium Ion Battery Systems.” Leveraging Technology for a Sustainable World 149–154. https://doi.org/10.1007/978-3-642-29069-5_26.
   Google Scholar
• IDIS. (2021). IDIS | the International Dismantling Information System. https://www.idis2.com/index.php.
   Google Scholar
• Jie, L., M. Barwood, and S. Rahimifard. 2015. An Automated Approach for Disassembly and Recycling of Electric Vehicle Components. 2014 IEEE International Electric Vehicle Conference, IEVC 2014. https://doi.org/10.1109/IEVC.2014.7056158
   Google Scholar
• Jin, X., and G. Tian. 2012. “A New Disassembly Network Graph Model and Its Automatic Generation.” Applied Mechanics & Materials 195–196:1083–1088. https://doi.org/10.4028/www.scientific.net/AMM.195-196.1083.
   Google Scholar
• Kim, H. J., S. Kernbaum, and G. Seliger. 2009. “Emulation-Based Control of a Disassembly System for LCD Monitors.” The International Journal of Advanced Manufacturing Technology 40 (3–4): 383–392. https://doi.org/10.1007/s00170-007-1334-z.
   Web of Science ®Google Scholar
• Kinoshita, Y., T. Yamada, S. M. Gupta, A. Ishigaki, and M. Inoue. 2020. “Decision Support Model of Environmentally Friendly and Economical Material Strategy for Life Cycle Cost and Recyclable Weight.” International Journal of Production Economics 224 (November 2019): 107545. https://doi.org/10.1016/j.ijpe.2019.107545.
   Google Scholar
• Kopacek, P. 2005. “Semiautomatized Disassembly - Some Examples.” In IFAC Proceedings Volumes (IFAC-Papersonline) (Vol. 16, Issue 1). IFAC. https://doi.org/10.3182/20050703-6-CZ-1902.01449.
   Google Scholar
• Laszlo, R., R. Holonec, R. Copîndean, and F. Dragan. 2019. Sorting System for E-Waste Recycling Using Contour Vision Sensors. Proceedings of 2019 8th International Conference on Modern Power Systems, MPS 2019, 8–11. https://doi.org/10.1109/MPS.2019.8759739
   Google Scholar
• Li, J., M. Barwood, and S. Rahimifard. 2018. “Robotic Disassembly for Increased Recovery of Strategically Important Materials from Electrical Vehicles.” Robotics and Computer-Integrated Manufacturing 50 (March 2016): 203–212. https://doi.org/10.1016/j.rcim.2017.09.013.
   Google Scholar
• Liu, Q., Z. Liu, W. Xu, Q. Tang, Z. Zhou, and D. T. Pham. 2019. “Human-Robot Collaboration in Disassembly for Sustainable Manufacturing.” International Journal of Production Research 57 (12): 4027–4044. https://doi.org/10.1080/00207543.2019.1578906.
   Web of Science ®Google Scholar
• Mao, W. L., W. C. Chen, C. T. Wang, and Y. H. Lin. 2021. “Recycling Waste Classification Using Optimized Convolutional Neural Network.” Resources, Conservation & Recycling 164 (July 2020): 105132. https://doi.org/10.1016/j.resconrec.2020.105132.
   Google Scholar
• Nascimento, J. C. D. 2019. “Decision-making and Fuzzy Temporal Logic.” ArXiv 1–11. https://doi.org/10.48550/arXiv.1901.01970.
   Google Scholar
• Parajuly, K., K. Habib, C. Cimpan, G. Liu, and H. Wenzel. 2016. “End-Of-Life Resource Recovery from Emerging Electronic Products – a Case Study of Robotic Vacuum Cleaners.” Journal of Cleaner Production 137:652–666. https://doi.org/10.1016/j.jclepro.2016.07.142.
   Web of Science ®Google Scholar
• Polat, O., O. Capraz, and A. Gungor. 2018. “Modelling of WEEE Recycling Operation Planning Under Uncertainty.” Journal of Cleaner Production 180:769–779. https://doi.org/10.1016/j.jclepro.2018.01.187.
   Web of Science ®Google Scholar
• Radaschin, A., A. Voda, E. Minca, and A. Filipescu. 2012. “Task Planning Algorithm in Hybrid Assembly/Disassembly Process.” In IFAC Proceedings Volumes (IFAC-Papersonline) (Vol. 45, Issue 6 PART 1). IFAC. https://doi.org/10.3182/20120523-3-RO-2023.00336.
   Google Scholar
• Saidani, M., B. Yannou, Y. Leroy, and F. Cluzel. 2020. “Dismantling, Remanufacturing and Recovering Heavy Vehicles in a Circular Economy—Technico-economic and Organisational Lessons Learnt from an Industrial Pilot Study.” Resources, Conservation & Recycling 156 (November 2018): 104684. https://doi.org/10.1016/j.resconrec.2020.104684.
   Google Scholar
• Schwab, K. 2015. The Fourth Industrial Revolution | Foreign Affairs. Foreign Affairs. https://www.foreignaffairs.com/articles/2015-12-12/fourth-industrial-revolution.
   Google Scholar
• Shumon, M. R. H., S. Ahmed, and S. Ahmed. 2016. “Fuzzy Analytical Hierarchy Process Extent Analysis for Selection of End of Life Electronic Products Collection System in a Reverse Supply Chain.” Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 230 (1): 157–168. https://doi.org/10.1177/0954405414553980.
   Web of Science ®Google Scholar
• Tumkor, S., and G. Senol. 2007. Disassembly Precedence Graph Generation. 2007 IEEE International Symposium on Assembly and Manufacturing, 104, 70–75. https://doi.org/10.1109/ISAM.2007.4288451
   Google Scholar
• Ullah, M., and B. Sarkar. 2020. “Recovery-Channel Selection in a Hybrid Manufacturing-Remanufacturing Production Model with RFID and Product Quality.” International Journal of Production Economics 219 (June 2019): 360–374. https://doi.org/10.1016/j.ijpe.2019.07.017.
   Google Scholar
• Vongbunyong, S., S. Kara, and M. Pagnucco. 2013. “Basic Behaviour Control of the Vision‐Based Cognitive Robotic Disassembly Automation.” Assembly Automation 33 (1): 38–56. https://doi.org/10.1108/01445151311294694.
   Web of Science ®Google Scholar
• Vongbunyong, S., M. Pagnucco, and S. Kara. 2016. “Vision-based execution monitoring of state transition in disassembly automation.” International Journal of Automation Technology 10 (5): 708–716. https://doi.org/10.20965/ijat.2016.p0708.
   Google Scholar
• Vongbunyong, S., P. Vongseela, and J. Sreerattana-Aporn. 2017. “A Process Demonstration Platform for Product Disassembly Skills Transfer.” Procedia CIRP 61 (c): 281–286. https://doi.org/10.1016/j.procir.2016.11.197.
   Google Scholar
• Yeh, W. C., and S. C. Wei. 2013. Simplified Swarm Optimization in Efficient Tool Assignment of Disassembly Sequencing Problem. 2013 IEEE Congress on Evolutionary Computation, CEC 2013, 2712–2719. https://doi.org/10.1109/CEC.2013.6557897
   Google Scholar
• Yi, J., B. Yu, L. Du, C. Li, and D. Hu. 2008. “Research on the Selectable Disassembly Strategy of Mechanical Parts Based on the Generalized CAD Model.” The International Journal of Advanced Manufacturing Technology 37 (5–6): 599–604. https://doi.org/10.1007/s00170-007-0990-3.
   Web of Science ®Google Scholar
• Zhang, X. F., G. Yu, Z. Y. Hu, C. H. Pei, and G. Q. Ma. 2014. “Parallel Disassembly Sequence Planning for Complex Products Based on Fuzzy-Rough Sets.” The International Journal of Advanced Manufacturing Technology 72 (1–4): 231–239. https://doi.org/10.1007/s00170-014-5655-4.
   Web of Science ®Google Scholar
• Zhu, B., and U. Roy. 2015. “Ontology-Based Disassembly Information System for Enhancing Disassembly Planning and Design.” The International Journal of Advanced Manufacturing Technology 78 (9–12): 1595–1608. https://doi.org/10.1007/s00170-014-6704-8.
   Web of Science ®Google Scholar
• Ziqiang, Z., D. Guohong, W. Zhaoren, and Z. Xiangyan. 2015. “Fuzzy-Clustering Based Cost Modeling of Disassembly Planning for EOL Products.” The Open Mechanical Engineering Journal 9 (1): 546–551. https://doi.org/10.2174/1874155X01509010546.
   Google Scholar
• Zülch, G., and J. Hrdina. 2010. “Control of Disassembly Systems Based on the Division of Labour by Means of Dynamically Adapting Routing Plans.” Lecture Notes in Business Information Processing 46 LNBI:396–407. https://doi.org/10.1007/978-3-642-12494-5_35.
   Google Scholar
• Zülch, G., and R. Schwarz. 2008. “Planning and Balancing of Disassembly Systems.” IFIP International Federation for Information Processing 257:49–56. https://doi.org/10.1007/978-0-387-77249-3_6.
   Google Scholar