Industry 4.0 in Remanufacturing

Bibliography

[1] Chakraborty, K. u. a.: A Study on Remanufacturing Possibility of a Product. In: Microsystem Technologies 25 (5), S. 1765–1770 (2019).
[2] Steinhilper, R.: Remanufacturing: The Ultimate Form of Recycling. Stuttgart (1998).
[3] Ijomah, W. L. u. a.: Development of Robust Design-for-Remanufacturing Guidelines to Further the Aims of Sustainable Development. In: International Journal of Production Research 45 (18-19), S. 4513–4536 (2007).
[4] Huang, W. u. a.: Remanufacturing Scheme Design for Used Parts Based on Incomplete Information Reconstruction. In: Chinese Journal of Mechanical Engineering 33 (5), 41 (2020).
[5] Kerin, M.; Pham, D. T.: Smart Remanufacturing: A Review and Research Framework. In: Journal of Manufacturing Technology Management 31 (6), S. 1205–1235 (2020).
[6] Yang, S. u. a.: Opportunities for Industry 4.0 to Support Remanufacturing. In: Applied Sciences 8 (7), S. 1177 (2018).
[7] Pistorius, J.: Industrie 4.0 – Schlüsseltechnologien fur die Produktion: Grundlagen, Potenziale, Anwendungen. Berlin, Heidelberg (2020).
[8] Sundin, E. u. a.: Design for Automatic End-of-Life Processes. In: Assembly Automation 32 (4), S. 389–398 (2012).
[9] Wang, X. u. a.: From Cloud Manufacturing to Cloud Remanufacturing: A Cloud-based Approach for WEEE Recovery. In: Manufacturing Letters 2 (4), S. 91-95 (2014).
[10] Wang, X. V.; Wang, L.: WRCloud: A Novel WEEE Remanufacturing Cloud System. In: Conference: Procedia CIRP 29, S. 786–791 (2015).
[11] Wang, X. V.; Wang, L.: Digital Twin-based WEEE Recycling, Recovery and Remanufacturing in the Background of Industry 4.0. In: International Journal of Production Research 57 (12), S. 3892–3902 (2019).
[12] Fang, H. C. u. a.: Use of Embedded Smart Sensors in Products to Facilitate Remanufacturing. In: Handbook of Manufacturing Engineering and Technology, S. 3265–3290 (2015).
[13] Zhou, W.; Piramuthu, S.: Remanufacturing with RFID Item-level Information: Optimization, Waste Reduction and Quality Improvement. In: International Journal of Production Economics 145 (2), S. 647–657 (2013).
[14] Zhang, Y. u. a.: The ‘Internet of Things’ Enabled Real-Time Scheduling for Remanufacturing of Automobile Engines. In: Journal of Cleaner Production 185, S. 562–575 (2018).
[15] Okorie, O. u. a.: Towards a Simulation-Based Understanding of Smart Remanufacturing Operations: A Comparative Analysis. In: Journal of Remanufacturing 14 (2), (2020).
[16] Ondemir, O.; Gupta, S. M.: Quality Management in Product Recovery Using the Internet of Things: An Optimization Approach. In: Computers in Industry 65 (3), S. 491–504 (2014).
[17] Gros, S. u. a.: Agentbased, Hybrid Control Architecture for Optimized and Flexible Production Scheduling and Control in Remanufacturing. In: Journal of Remanufacturing 14 (2), (2020).
[18] French, R. u. a.: Intelligent Sensing for Robotic Re-Manufacturing in Aerospace: An Industry 4.0 Design-Based Prototype. In: 2017 IEEE International Symposium on Robotics and Intelligent Sensors (IRIS), S. 272–277 (2017).
[19] Ruggeri, S. u. a.: Micro-Robotic Handling Solutions for PCB (Re-)Manufacturing. In: Procedia Manufacturing 11, S. 441–448 (2017).
[20] Huang, J. u. a.: A Strategy for Human-Robot Collaboration in Taking Products Apart for Remanufacture. In: FME Transactions 47 (4), S. 731–738 (2019).
[21] Li, R. u. a.: Unfastening of Hexagonal Headed Screws by a Collaborative Robot. In: IEEE Transactions on Automation Science and Engineering, S. 1-14 (2020).
[22] Gerbers, R. u. a.: Safe, Flexible and Productive Human-Robot-Collaboration for Disassembly of Lithium-Ion Batteries. In: Sustainable Production, Life Cycle Engineering and Management, Recycling of Lithium-Ion Batteries, S. 99-126 (2018).
[23] Bdiwi, M. u. a.: Autonomous Disassembly of Electric Vehicle Motors Based on Robot Cognition. In: 2016 IEEE International Conference on Robotics and Automation (ICRA), S. 2500–2505 (2016).
[24] Jungbluth, J. u. a.: Demontage von Elektroantrieben mit Assistenzrobotern zum wirtschaftlichen Recycling. In: Tagungsband AALE 2016, S. 10 (2016).
[25] Vongbunyong, S. u. a.: Basic Behaviour Control of the Vision-Based Cognitive Robotic Disassembly Automation. In: Assembly Automation 33 (1), S. 38–56 (2013).
[26] Vongbunyong, S. u. a.: Learning and Revision in Cognitive Robotics Disassembly Automation. In: Robotics and Computer-Integrated Manufacturing 34, S. 79–94 (2015).
[27] Vongbunyong, S. u. a.: A Process Demonstration Platform for Product Disassembly Skills Transfer. In: Procedia CIRP 61, S. 281–286 (2017).
[28] Ries, S. u. a.: Demontageeffektor für Schraubverbindungen mit ungewissem Zustand. In: ZWF Zeitschrift fuer Wirtschaftlichen Fabrikbetrieb 115 (10), S. 711-714 (2020).
[29] Chang, M. u. a.: Interactive AR-Assisted Product Disassembly Sequence Planning (ARDIS). In: International Journal of Production Research 58 (16), S. 4916–4931 (2020).
[30] Chang, M. u. a.: AR-Guided Product Disassembly for Maintenance and Remanufacturing. In: Procedia CIRP 61, S. 299–304 (2017).
[31] Mircheski, I.; Rizov, T.: Improved Nondestructive Disassembly Process Using Augmented Reality and RFID Product/Part Tracking. In: TEM Journal 6 (4), S. 671–676 (2017).
[32] Bentaha, M. L. u. a.: Profit-Oriented Partial Disassembly Line Design: Dealing with Hazardous Parts and Task Processing Times Uncertainty. In: International Journal of Production Research 56 (24), S. 7220–7242 (2018).
[33] Liu, M. u. a.: Robust Disassembly Line Balancing with Ambiguous Task Processing Times. In: International Journal of Production Research 58 (19), S. 5806–5835 (2020).
[34] Meng, W.; Zhang, X.: Optimization of Remanufacturing Disassembly Line Balance Considering Multiple Failures and Material Hazards. In: Sustainability 12 (18), S. 7318 (2020).
[35] Tian, G. u. a.: Disassembly Sequence Planning Considering Fuzzy Component Quality and Varying Operational Cost. In: IEEE Transactions on Automation Science and Engineering 15 (2), S. 748–760 (2018).
[36] Li, S. u. a.: Multi-Objective Disassembly Sequence Optimization Aiming at Quality Uncertainty of End-of-Life Product. In: IOP Conference Series Materials Science and Engineering 631 (3), S. 32015 (2019).
[37] Xia, X. u. a.: 3D-Based Multi-Objective Cooperative Disassembly Sequence Planning Method for Remanufacturing. In: The International Journal of Advanced Manufacturing Technology 106 (4), S. 4611–4622 (2020).
[38] Li, L. u. a.: An Integrated Approach of Reverse Engineering Aided Remanufacturing Process for Worn Components. In: Robotics and Computer-Integrated Manufacturing 48, S. 39–50 (2017).
[39] Zheng, Y. u. a.: A Primitive-Based 3D Reconstruction Method for Remanufacturing. In: The International Journal of Advanced Manufacturing Technology 103 (4), S. 3667–3681 (2019).
[40] Khan, A. u. a.: Vision Guided Robotic Inspection for Parts in Manufacturing and Remanufacturing Industry. In: Journal of Remanufacturing 11 (6), S. 49-70 (2020).
[41] Schlüter, M. u. a.: Vision-Based Identification Service for Remanufacturing Sorting. In: Procedia Manufacturing 21, S. 384–391 (2018).
[42] Siddiqi, M. U. R. u. a.: Low Cost Three-Dimensional Virtual Model Construction for Remanufacturing Industry. In: Journal of Remanufacturing 9 (2), S. 129–139 (2019).
[43] Gibbons, Tom u. a.: A Gaussian Mixture Model for Automated Corrosion Detection in Remanufacturing. In: Advances in Transdisciplinary Engineering 8, S. 63–68 (2018).
[44] Nwankpa, C. u. a.: Achieving Remanufacturing Inspection Using Deep Learning. In: Journal of Remanufacturing 11 (2), S. 89-105 (2020).