Evaluation of Waste Electronic Product Trade-in Strategies in Predictive Twin Disassembly Systems in the Era of Blockchain
Manufacturing and supply chain operations are on the cusp of an era with the emergence of groundbreaking technologies. Among these, the digital twin technology is characterized as a paradigm shift in managing production and supply networks since it facilitates a high degree of surveillance and a com...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Article |
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Multidisciplinary Digital Publishing Institute
2020
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| Online Access: | https://hdl.handle.net/1721.1/126874 |
| _version_ | 1811090759880802304 |
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| author | Tozanli Yilmaz, Ozden Kongar, Elif Gupta, Surendra M. |
| author2 | Massachusetts Institute of Technology. Center for Transportation & Logistics |
| author_facet | Massachusetts Institute of Technology. Center for Transportation & Logistics Tozanli Yilmaz, Ozden Kongar, Elif Gupta, Surendra M. |
| author_sort | Tozanli Yilmaz, Ozden |
| collection | MIT |
| description | Manufacturing and supply chain operations are on the cusp of an era with the emergence of groundbreaking technologies. Among these, the digital twin technology is characterized as a paradigm shift in managing production and supply networks since it facilitates a high degree of surveillance and a communication platform between humans, machines, and parts. Digital twins can play a critical role in facilitating faster decision making in product trade-ins by nearly eliminating the uncertainty in the conditions of returned end-of-life products. This paper demonstrates the potential effects of digital twins in trade-in policymaking through a simulated product-recovery system through blockchain technology. A discrete event simulation model is developed from the manufacturer’s viewpoint to obtain a data-driven trade-in pricing policy in a fully transparent platform. The model maps and mimics the behavior of the product-recovery activities based on predictive indicators. Following this, Taguchi’s Orthogonal Array design is implemented as a design-of-experiment study to test the system’s behavior under varying experimental conditions. A logistics regression model is applied to the simulated data to acquire optimal trade-in acquisition prices for returned end-of-life products based on the insights gained from the system. |
| first_indexed | 2024-09-23T14:51:31Z |
| format | Article |
| id | mit-1721.1/126874 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T14:51:31Z |
| publishDate | 2020 |
| publisher | Multidisciplinary Digital Publishing Institute |
| record_format | dspace |
| spelling | mit-1721.1/1268742022-10-01T22:59:22Z Evaluation of Waste Electronic Product Trade-in Strategies in Predictive Twin Disassembly Systems in the Era of Blockchain Tozanli Yilmaz, Ozden Kongar, Elif Gupta, Surendra M. Massachusetts Institute of Technology. Center for Transportation & Logistics Manufacturing and supply chain operations are on the cusp of an era with the emergence of groundbreaking technologies. Among these, the digital twin technology is characterized as a paradigm shift in managing production and supply networks since it facilitates a high degree of surveillance and a communication platform between humans, machines, and parts. Digital twins can play a critical role in facilitating faster decision making in product trade-ins by nearly eliminating the uncertainty in the conditions of returned end-of-life products. This paper demonstrates the potential effects of digital twins in trade-in policymaking through a simulated product-recovery system through blockchain technology. A discrete event simulation model is developed from the manufacturer’s viewpoint to obtain a data-driven trade-in pricing policy in a fully transparent platform. The model maps and mimics the behavior of the product-recovery activities based on predictive indicators. Following this, Taguchi’s Orthogonal Array design is implemented as a design-of-experiment study to test the system’s behavior under varying experimental conditions. A logistics regression model is applied to the simulated data to acquire optimal trade-in acquisition prices for returned end-of-life products based on the insights gained from the system. 2020-09-01T16:11:16Z 2020-09-01T16:11:16Z 2020-07 2020-06 2020-08-21T13:48:43Z Article http://purl.org/eprint/type/JournalArticle 2071-1050 https://hdl.handle.net/1721.1/126874 Özden Tozanlı et al. "Evaluation of Waste Electronic Product Trade-in Strategies in Predictive Twin Disassembly Systems in the Era of Blockchain." Sustainability 12, 13 (July 2020): 5416 ©2020 Author(s) 10.3390/su12135416 Sustainability Creative Commons Attribution https://creativecommons.org/licenses/by/4.0/ application/pdf Multidisciplinary Digital Publishing Institute Multidisciplinary Digital Publishing Institute |
| spellingShingle | Tozanli Yilmaz, Ozden Kongar, Elif Gupta, Surendra M. Evaluation of Waste Electronic Product Trade-in Strategies in Predictive Twin Disassembly Systems in the Era of Blockchain |
| title | Evaluation of Waste Electronic Product Trade-in Strategies in Predictive Twin Disassembly Systems in the Era of Blockchain |
| title_full | Evaluation of Waste Electronic Product Trade-in Strategies in Predictive Twin Disassembly Systems in the Era of Blockchain |
| title_fullStr | Evaluation of Waste Electronic Product Trade-in Strategies in Predictive Twin Disassembly Systems in the Era of Blockchain |
| title_full_unstemmed | Evaluation of Waste Electronic Product Trade-in Strategies in Predictive Twin Disassembly Systems in the Era of Blockchain |
| title_short | Evaluation of Waste Electronic Product Trade-in Strategies in Predictive Twin Disassembly Systems in the Era of Blockchain |
| title_sort | evaluation of waste electronic product trade in strategies in predictive twin disassembly systems in the era of blockchain |
| url | https://hdl.handle.net/1721.1/126874 |
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