Issues in end-of-life product recovery and reverse logistics

2001 ◽  
Vol 12 (5) ◽  
pp. 534-547 ◽  
Author(s):  
Neil Ferguson ◽  
Jim Browne
Author(s):  
Seval Ene ◽  
Nursel Öztürk

Increased consciousness on environment and sustainability, leads companies to apply environmentally friendly strategies such as product recovery and product return management. These strategies are generally applied in reverse logistics concept. Implementing reverse logistics successfully becomes complicated for companies due to uncertain parameters of the system like quantity, quality and timing of returns. A forecasting methodology is required to overcome these uncertainties and manage product returns. Accurate forecasting of product return flows provides insights to managers of reverse logistics. This paper proposes a forecasting model based on grey modelling for managing end-of-life products’ return flow. Grey models are capable for handling data sets characterized by uncertainty and small sized. The proposed model is applied to data set of a specific end-of-life product. Attained results show that the proposed forecasting model can be successfully used as a forecasting tool for product returns and a supportive guidance can be provided for future planning. Keywords: End-of-life products, grey modelling, product return flow, product recovery; 


10.5772/9898 ◽  
2010 ◽  
Author(s):  
Rinaldo Michelini ◽  
Roberto Razzoli

2021 ◽  
pp. 0734242X2110452
Author(s):  
Masoud Amirdadi ◽  
Farzad Dehghanian ◽  
Jamal Nahofti Kohneh

The ever-growing stream of waste production has become a critical issue for many metropolitan areas. An effective strategy to address this problem has been the concept of reverse logistics (RL). This paper seeks to develop an appropriate product recovery approach for electronic waste generated in an urban area. Consequently, we have proposed an integrated fuzzy RL model with buyback (BB) offers based on the condition of used-products (UPs) at the time of return. However, this strategy contains a significant challenge, which derives from unpredictability surrounding the return rate of UPs due to its dependency on multiple external factors. Hence, a novel fuzzy probability function is developed to approximate UPs’ chance of return. Besides that, the mathematical RL network’s inherent uncertainty prompted us to employ the fuzzy credibility-based method in the model. Afterward, the model’s objectives are locating and allocating collection centres to customer zones, determining flow between facilities and finding the optimal amount of gathered UPs and BB offers. Finally, we applied the model to a case study concerning product recovery in Mashhad city, Iran, and the results have proven its validity and utility.


2020 ◽  
Vol 142 ◽  
pp. 106339 ◽  
Author(s):  
F. Javier Ramírez ◽  
Juan A. Aledo ◽  
Jose A. Gamez ◽  
Duc T. Pham

Sign in / Sign up

Export Citation Format

Share Document