Forecasting the Number of End-of-Life Vehicles: State of the Art Report

Xia, Hanbing; Han, Jiarui; Milisavljevic-Syed, Jelena

doi:10.1017/pds.2022.119

Cited by 4 publications

(3 citation statements)

References 35 publications

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“…Several researchers have investigated the socioeconomic factors that influence the quantity of recycled ELVs [5,[37][38][39][40][41]. 15 socioeconomic factors were selected that affect the quantity of recycled ELVs [37][38][39][40][41].…”

Section: Emprical Study 41 Data Descriptionmentioning

confidence: 99%

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Predicting the Quantity of Recycled End-of-Life Products Using a Hybrid SVR-Based Model

Xia,

Han,

Milisavljevic-Syed

2023

Volume 5: 28th Design for Manufacturing and the Life Cycle Conference (DFMLC)

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End-of-life product recycling is crucial for achieving sustainability in circular supply chains and improving resource utilization. Forecasting the quantity of recycled end-of-life products is essential for planning and managing reverse supply chain operations. Decision-makers and practitioners can benefit from this information when designing reverse logistics networks, managing tactical disposal, planning capacity, and operational production. To address the challenge of small sample data with multiple factors influencing the recycling number, and to deal with the randomness and nonlinearity of the recycling quantity, a hybrid predictive model has been developed in this research. The model is based on k-nearest neighbor mega-trend diffusion (KNNMTD), particle swarm optimization (PSO), and support vector regression (SVR) using the data from the field of end-of-life vehicles as a case study. Unlike existing literature, this research incorporates the data augmentation method to build an SVR-based model for end-of-life product recycling. The study shows that developing the predictive model using artificial virtual samples supported by the KNNMTD method is feasible, the PSO algorithm effectively brings strong approximation ability to the SVR-based model, and the KNNMTD-PSO-SVR model perform well in predicting the recycled end-of-life products quantity. These research findings could be considered a fundamental component of the smart system for circular supply chains, which will enable the smart platform to achieve supply chain sustainability through resource allocation and regional industry deployment.

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Section: Emprical Study 41 Data Descriptionmentioning

confidence: 99%

“…Return quantity is the most significant uncertainty in RSC, making quantity prediction crucial when designing RSC. This information helps industrial engineers make decisions on designing reverse logistics networks, managing tactical disposal, planning capacity, and operational production [5].…”

Section: Introductionmentioning

confidence: 99%

Predicting the Quantity of Recycled End-of-Life Products Using a Hybrid SVR-Based Model

Xia,

Han,

Milisavljevic-Syed

2023

Volume 5: 28th Design for Manufacturing and the Life Cycle Conference (DFMLC)

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“…The whereabouts of the permanently decommissioned vehicles in Germany in 2019 are shown graphically in Figure 1. Due to the high export rate of decommissioned cars a large proportion of the materials used within the cars are lost to the local economy [14,15]. Moreover, increasing material criticality issues in industrial enterprises lead to the need for circular solutions [16,17].…”

Section: Introductionmentioning

confidence: 99%

Designing Component Interfaces for the Circular Economy—A Case Study for Product-As-A-Service Business Models in the Automotive Industry

et al. 2022

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The resource-intensive automotive industry offers great potential to avoid waste through new circular business models. However, these new business models require technical innovations that enable the rapid dismantling of add-on parts. In this paper, we design new mechanical interfaces that enable fast and non-destructive dismantling while still fulfilling all technical requirements and develop a general model for the evaluation of disassembly capability. For this purpose, the current dismantling options of add-on parts are first examined and evaluated concerning defined KPIs using the example of the front bumper. Based on the analysis, the requirements as well as various solution principles for the new interface concept can be derived. The necessity of removing neighboring components is identified as the main challenge for rapid dismantling. Two different concepts for the interfaces were developed by inserting an intermediate level as a connecting part between the front bumper and the front module. We prove that by redesigning and reconstructing the interfaces the number of process steps required to remove the front bumper could be reduced by roughly 60% compared to current interface solutions. The developed methodology should be applied to other components of a vehicle to create a greater positive environmental, economic and societal impact.

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Waste from Industry and Commercial Activity

Chandrappa,

Das

2024

Solid Waste Management

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Forecasting the Number of End-of-Life Vehicles: State of the Art Report

Cited by 4 publications

References 35 publications

Predicting the Quantity of Recycled End-of-Life Products Using a Hybrid SVR-Based Model

Predicting the Quantity of Recycled End-of-Life Products Using a Hybrid SVR-Based Model

Designing Component Interfaces for the Circular Economy—A Case Study for Product-As-A-Service Business Models in the Automotive Industry

Waste from Industry and Commercial Activity

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