Evaluation of Waste Electronic Product Trade-in Strategies in Predictive Twin Disassembly Systems in the Era of Blockchain

Özden Tozanlı, Elif Kongar and Surendra M. Gupta
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Özden Tozanlı: Center for Transportation and Logistics, Massachusetts Institute of Technology, Cambridge, MA 02142, USA
Elif Kongar: Departments of Mechanical Engineering and Technology Management, School of Engineering, University of Bridgeport, Bridgeport, CT 06604, USA
Surendra M. Gupta: Department of Mechanical and Industrial Engineering, Northeastern University, Boston, MA 02115, USA

Sustainability, 2020, vol. 12, issue 13, 1-33

Abstract: 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.

Keywords: disassembly; smart remanufacturing; trade-in; digital twins; blockchain; IoT; discrete-event simulation; logistic regression (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

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