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End-of-life vehicle management: a comprehensive review

  • Selman KaragozEmail author
  • Nezir Aydin
  • Vladimir Simic
Open Access
REVIEW
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Abstract

Waste management is gaining very high importance in recent years. As automotive is one of the most critical sectors worldwide, which is rapidly increasing, the management of end-of-life vehicles (ELVs) gains importance day by day. Due to legislation and new regulations, actors like users, producers, and treatment facilities are being conferred new responsibilities in the ELV management process. Besides, the ELV management is of vital importance for environment conservation, circular economy and sustainable development. All of these reasons are making the ELV management such a crucial issue to study. Today, the ELV management is a well-positioned and emergent research area. However, the available review papers are focused only on a small area of the ELV management, such as reverse logistics, recovery infrastructure, disassemblability, etc. Besides, a review of state-of-the-art mathematical models for the ELV management is still missing. This paper aims to provide an extensive content analysis overview of studies on the ELV management. A total of 232 studies published in the period 2000–2019 are collected, categorized, reviewed and analyzed. A critical review of the published literature is provided. Gaps in the literature are identified to clarify and suggest future research directions. This review can provide a source of references, valuable insights, and opportunities for researchers interested in the ELV management and inspire their additional attention.

Keywords

End-of-life vehicle Management Waste Recycling Review 

Introduction

As a result of industrialization, environmental pollution has become one of the most crucial issues of today. According to the Organization for Economic Cooperation and Development (OECD), the total number of registered vehicles in OECD/Europe countries has grown by 4% a year within the period of 2014–2018 [1]. Figure 1 shows worldwide automobile production from 2000 to 2017 (in million vehicles) [2]. As the automotive sector generates about 5% of industrial waste in the entire world [3], recycling of end-of-life vehicles (ELVs) is not only an environmental issue to deal with but also a financial source for the industries.
Fig. 1

Worldwide automobile production from 2000 to 2017 (Statista Portal, 2019)

ELVs are classified as hazardous waste and have the potential for polluting the environment if they are not managed properly [4]. They are the single largest hazardous waste category from households [5]. They represent a category of waste whose processing is especially difficult because of their complex structure and varied composition. As the number of ELVs is estimated to increase to approximately 80 million units per year by 2020 [6], there is strong motivation to effectively manage this fast-growing waste flow.

The ELV management includes the management of all related activities and material, financial, and information flows between and among the ELV network entities; i.e., vehicle users, collection centers, authorized dismantling facilities, shredders, recycling centers, remanufacturing facilities, second-hand markets, industrial landfills sites, etc. It is of vital importance for environment conservation, circular economy and sustainable development. This process is not only profit-oriented. The management of ELVs is significantly dependent on legislation, like Directive 2000/53/EC [7] in the European Union, Law on recycling of ELVs [8] in Japan, Technical policy for the recovery and utilization of automobile products [9] in China, Act on the resource circulation of electrical and electronic equipment and vehicles [10] in Korea, etc. Sound management of ELVs has become the principal sustainability issue in most countries worldwide and therefore requires sophisticated decision-making tools for optimizing its efficiency.

Today, the ELV management is a well-positioned and emergent research area. Recently, some review papers have been published (Table 1). They should be presented here to highlight the need for this research. Table 1 overviews 21 review studies from the literature in the field of ELV management regarding their scope, analyzed period and number of reviewed papers. It shows that the available review papers are focused only on a small area of the ELV management, such as reverse logistics, recovery infrastructure, disassemblability, treatment processes, etc. In addition, a review of state-of-the-art mathematical models for the ELV management is still missing from the available reviews. The last line in Table 1 can present the role of this review paper in covering the identified gap of the literature. It is necessary to have a comprehensive review of the ELV management area to help researchers focus on future directions. Therefore, in this paper, we present a holistic view of the ELV management research area by covering a wide range of published work.
Table 1

Summary of (available) review papers in the field of ELV management

Author(s) and year

Scope

Analyzed period

Number of reviewed papers

Nourreddine (2007) [12]

(Automotive) shredder residue treatment

1991–2004

26

Vermeulen et al. (2011) [16]

1994–2011

~ 150

Zorpas and Inglezakis (2012) [18]

1978–2010

~ 110

Cossu and Lai (2015) [27]

2005–2014

~ 120

De Almeida and Borsato (2019) [31]

1999–2016

76

Kumar and Sutherland (2008) [13]

Vehicle recovery infrastructure

1986–2007

73

Hiratsuka et al. (2014) [24]

 

1995–2012

26

Go et al. (2011) [17]

Disassemblability

1992–2010

38

Mayyas et al. (2012) [19]

Sustainability of the automotive industry

1984–2011

~ 90

Bari et al. (2011) [14]

Automotive waste

2010

103

Kindzierski et al. (2013) [15]

2012

107

Simic (2013) [3]

Environmental engineering issues

2003–2012

93

Lashlem et at. (2013) [20]

Management practices

1995–2012

20

Sakai et al. (2014) [23]

1991–2012

~ 90

Li et al. (2014) [22]

2005–2012

16

Gan and He (2014) [21]

Reverse logistics

2002–2013

38

Cin and Kusakci (2017) [30]

2005–2016

23

Zhang and Chen (2014) [26]

Automotive plastics

1993–2012

63

Buekens and Zhou (2014) [25]

Automotive shredder residue plastics

1977–2012

76

Cucchiella et al. (2016) [28]

Automotive electronics

2000–2014

~ 50

Rosa and Terzi (2016) [29]

2001–2015

35

Our review

Whole area

2000–2019

232

This paper systematically investigates the current research within the area of the ELV management by classifying 232 peer-reviewed published references. Its primary purpose is to provide an extensive content analysis overview of state-of-the-art research published in the period 2000–2019. Studies on the ELV management are classified based on their objectives, methodology, parameter types used in the case, type of supply chains, number, and type of objective functions. Moreover, studies that have used mathematical optimization are analyzed independently based on the type of decision variables, optimization model types, single-multi objectivity, and solution approach. Gaps in the literature are identified to clarify and suggest future research directions.

The remaining part of the paper is organized as follows: Sect. “Review methodology” describes a review methodology. Classification is provided in Sect. “Classification”. Sections “Classification” and “Results of the literature review” present the obtained results of the review and discussion, respectively. The last section presents the paper’s main conclusions and recommendations.

Review methodology

In this study, Content analysis (CA) was inspired to review the literature. CA is a research technique based on interpreting and coding textual material to convert qualitative data into quantitative data [11].

Furthermore, only peer-reviewed publications (i.e., international journals, book chapters, etc.) were reviewed. Search engines were used to explore ACS Publications, ASCE Library, ASME Digital Library, Cambridge Journals, EBSCOhost, EmeraldInsight, Google Scholar, IEEE Xplore, Inderscience, IntegraConnect, IOPScience, J-STAGE, JSTOR, ProQuest, RSCPublishing, SAGE journals, ScienceDirect, SciVerse, SpringerLink, and WILEY databases for literature. Publications were searched with the keyword of “End of life vehicles”. In addition, the references cited in each relevant literature were examined to find out additional sources of information. Finally, rigor in validity is achieved by validation tests using the deductive and inductive approaches simultaneously.

Classification

Being a complex and multidisciplinary subject, ELV management review studies are classified and analyzed based on various types of subjects. For instance, Simic [3] classified the publications related to the ELVs recycling into three major categories: “Vehicle recycling practices world-wide”, “Legislation-oriented research” and “Remanufacturing and materials recycling”. Therefore, major categories were classified according to their approaches; e.g., “Life Cycle Assessment”, “Production planning”, “Material selection”, etc.

In this study, ELVs-related publications are classified into four major categories: (1) literature survey, (2) recycling, production and planning, (3) network design and (4) regulations review. Furthermore, methods of the studies are presented as a sub-category. Figure 2 presents the major classification of the study.
Fig. 2

The major classification of the reviewed publications

In addition, publications including mathematical models were analyzed additionally. Cin and Kusakci [30] clustered reverse logistics of ELVs studies based on network structure, optimization model, objective function, methods to handle uncertainty and solution approach. Different from Cin and Kusakci [30], not only logistics networks of ELVs but also other types of ELVs (e.g., production planning, recycling process planning, location-allocation, etc.) studies with an optimization model are reviewed based on the type of decision variables, optimization model and solution approach. The aim of these classifications is to categorize the studies and make them more visible and summarizer for the researchers.

The major classification of the study

The publications were classified into four major categories: (1) literature survey (LS), (2) recycling, production and planning (RPP), (3) network design (ND) and (4) regulations review.

  1. 1.

    Literature survey (LS) In this sub-category, surveys that are in the scope of this research were investigated.

     
  2. 2.

    Recycling, production and planning (RPP) In this sub-category, studies aiming to analyze and suggest solutions for tactical decisions about recycling processes, material types, product design, and production planning were categorized.

     
  3. 3.

    Network design (ND) Studies that are suggesting approaches to cope with strategical decisions about supply chain issues in the ELV management process were categorized under this sub-section.

     
  4. 4.

    Regulations review (RR) As legislations play an important role in ELVs’ recycling, studies related to regulation analyses were categorized in this sub-category.

     

Methods

The studies reviewed in this paper were classified into 23 categories and 29 sub-categories by the applied methods. Figure 3 presents the summary of used methods in the reviewed studies.
Fig. 3

Classification of methods used in the reviewed studies

Single-multi objectivity

In this section, studies with mathematical modeling approaches were classified into two sections based on the number of their objective functions: (1) single-objective (SO) and (2) multi-objective (MO).

Type of objective function

In addition to the single-multi objectivity section, studies with a mathematical model were classified based on the type of their objective function(s): (1) maximization (Max) and (2) minimization (Min).

Type of parameter

In this section, studies were classified into three sub-categories based on parameter type used in the publication: (1) deterministic (Det.), (2) probabilistic (Prob.) and (3) fuzzy.

Type of supply chain

As transportation of ELVs and its components is one of the most indispensable activities in the ELV management, the reviewed studies were classified into two sub-categories based on supply chain type: (1) open loop (OL), and (2) closed loop (CL).

Type of decision variables

Based on the type of decision variables in the studies with a mathematical model, publications were classified into three sub-categories: (1) location allocation (LA), (2) recycling planning (RP), (3) production planning (PP).

Optimization model

In this section, studies with mathematical models were classified into four sub-categories: (1) linear programming (LP), (2) non-linear programming (NLP), (3) mixed-integer linear programming (MILP), and (4) mixed-integer non-linear programming (MINP).

Solution approach

In this section, studies were classified into three sub-categories based on their solution approaches (1) exact (E), (2) heuristics (H) and (3) meta-heuristics (MH).

Results of the literature review

While the ELV management was in its infancy 20 years ago, today it is a well-recognized and growing research area. The main reason for this is the introduction of Directive 2000/53/EC. More detailed, Directive 2000/53/EC of the European Parliament and of the Council of 18 September 2000 on end-of-life vehicles was introduced in the year 2000 [7]. It fundamentally changed the business philosophy of the vehicle recycling industry. This change started the evolution of the ELV management that has taken place in the last two decades. Since the year 2000, a lot of activity has taken place in the ELV management research area, which has come into focus. Besides, many new sub-areas also have emerged. In view of that, 232 publications in the period of 2000–2019, are collected and classified based on the purpose of the study. This classification generates the main framework of the review. A summary of the overall literature review according to their classification is presented in Table 2.
Table 2

Summary of RPP publications on the ELV management

Year

Author(s)

Method(s) used in the study

  

FC

GP

LCA

LCC

LCI

LP

MBM

MFE

MILP

MM

MOP

NLP

PPP

PR

SD

TCM

2000

Kirkpatrick et al. [32]

  

             

2000

Bellman and Khare [33]

            

   

2000

Hartman et al. [34]

  

             

2000

Hoffmann and Wilson [181]

  

             

2001

Díaz and Fernández [35]

  

             

2001

Mark et al. [36]

   

            

2001

Johnson and Wang [37]

               

2001

Petrov [38]

  

             

2002

Johnson and Wang [39]

       

        

2002

Van Schaik et al. [40]

         

    

 

2003

Boon et al. [41]

 

              

2003

Petrov [42]

  

             

2003

Castro et al. [43]

  

             

2004

Gesing [44]

  

             

2004

Mark and Kamprath [45]

  

             

2004

Van Schaik and Reuter [46]

              

 

2004

Van Schaik et al. [47]

           

    

2004

Kim et al. [48]

      

         

2004

Schmidt et al. [49]

  

             

2004

Pelletiere and Reinert [50]

               

2004

Bandivadekar et al. [51]

       

      

 

2005

Sawyer-Beaulieu and Tam [52]

  

             

2005

Seo et al. [53]

  

             

2005

Choi et al. [54]

        

       

2005

Castro et al. [55]

              

 

2005

Forslind [56]

  

             

2006

Chen [57]

  

             

2006

Ferrao et al. [58]

  

             

2006

Krinke et al. [59]

  

             

2006

Reuter et al. [60]

     

          

2006

Forton et al. [61]

  

             

2006

Finkbeiner et al. [62]

  

             

2006

Mazzanti and Zoboli [63]

              

 

2006

Amaral et al. [64]

              

 

2006

Ferrao and Amaral [65]

               

2006

Pelletiere and Reinert [66]

               

2007

Coates and Rahimifard [67]

         

     

2007

Jeong et al. [68]

  

             

2007

Joung et al. [69]

  

             

2007

Mergias et al. [70]

             

  

2007

Dalmijn and De Jong [71]

  

             

2007

Giannouli et al. [72]

               

2007

Sakai et al. [73]

  

             

2007

Williams et al. [74]

        

       

2007

Alonso et al. [75]

  

            

2007

Frad and Revnic [76]

  

             

2007

Ribeiro et al. [77]

  

             

2007

Fuse et al. [78]

               

2008

Ignatenko et al. [79]

          

     

2008

Qi and Hongcheng [80]

        

       

2008

Sawyer-Beaulieu and Tam [81]

    

           
  

Method(s) used in the study

Year

Author(s)

EPR

FC

GA

ILP

LCA

LCI

LP

MFA

MFE

MILP

MM

MOP

NLP

SD

SW

TCM

WA

2008

Smith and Keoleian [82]

     

           

2008

Fuse and Kashima [83]

 

               

2008

Qu and Williams [84]

           

     

2009

Chondros [85]

         

       

2009

Puri et al. [86]

     

           

2009

Amelia et al. [87]

    

           

2009

Chen and Zhang [88]

                

2009

Kumar and Sutherland [89]

            

    

2009

Fuse et al. [90, 91]

    

            

2009

Zoraga et al. [102]

    

            

2009

Haefliger et al. [182]

    

            

2010

Santini et al. [92]

              

  

2010

Chen et al. [93]

    

            

2010

Go et al. [94]

        

        

2010

Mathieux and Brissaud [95]

 

               

2011

Agbo [96]

 

               

2011

Duranceau and Sawyer-Beaulieu [97]

             

 

 

2011

Hedayati and Subic [98]

    

            

2011

Kibira and Jain [99]

  

       

      

2011

Santini et al. [100]

       

         

2011

Xi et al. [101]

    

            

2011

Che et al. [103]

    

          

 

2011

Nazmi et al. [104]

          

      

2012

Filho [105]

    

   

        

2012

Fiore et al. [106]

    

   

        

2012

Millet et al. [107]

       

  

      

2012

Nakamura et al. [108]

                

2012

Santini et al. [109]

    

  

         

2012

Cheng et al. [110]

    

  

         

2012

Hatayama et al. [111]

       

         

2012

Wang and Chen [112]

              

  

2012

Simic and Dimitrijevic [113, 114]

      

          

2013

Arena et al. [115]

    

            

2013

Simic and Dimitrijevic [116]

      

          

2013

Simic and Dimitrijevic [117]

   

             

2013

Berzi et al. [118]

        

 

      

2013

Tasala Gradin et al. [119]

    

            

2013

Saavedra et al. [120]

    

  

         

2013

Schmid et al. [121]

       

         

2013

Hu and Kurasaka [122]

 

               

2014

Miller et al. [123]

      

         

2014

Ruffino et al. [124]

    

   

        

2014

Sawyer-Beaulieu et al. [125]

    

  

         

2014

Tian and Chen [126]

      

         

2014

Ahmed et al. [127]

    

   

        

2014

Lu et al. [128]

       

         

2014

Yano et al. [129]

       

         

2014

Noguchi et al. [185]

    

            

2015

El Halabi et al. [130]

    

            

Year

Author(s)

Method(s) used in the study

  

AHP

ANN

CBA

DEM

EFA

EA

FAHP

FC

FV

ILP

IOT

LCA

LCI

MFA

SD

SEM

TP

WA

2015

Chen et al. [131]

  

               

2015

Despeisse et al. [132]

           

 

    

2015

Ohno et al. [133]

             

   

2015

Sawyer-Beaulieu and Tam [134]

           

     

2015

Yi and Park [135]

          

       

2015

Simic and Dimitrijevic [136]

         

        

2015

Oguchi and Fuse [137]

       

          

2015

Daniell et al. [186]

           

      

2016

Belboom et al. [138]

           

      

2016

Desnica et al. [139]

                 

2016

Inghels et al. [140]

           

  

   

2016

Junior et al. [141]

           

 

    

2016

Pan and Li [142]

     

       

    

2016

Ahmed et al. [143, 144]

   

  

           

2016

Pourjavad and Mayorga [145, 146]

      

         

 

2016

Raja Mamat et al. [147]

    

          

  

2016

Li et al. [148]

           

      

2016

Tian and Chen [149]

  

   

           

2016

Xia et al. [150]

  

               

2016

Zhou et al. [151]

        

         

2016

Diener and Tillman [152]

             

    

2016

Xu et al. [153]

       

     

    

2016

Yano et al. [154]

       

     

    

2016

Fujimori et al. [188]

           

      

2016

Ericson et al. [189]

           

      

2017

Andersson et al. [155]

       

          

2017

Ene and Öztürk [156]

       

          

2017

Gan and Luo [157]

   

              

2017

Karaeen et al. [158]

           

      

2017

Soo et al. [159]

           

      

2017

Soo et al. [160]

       

          

2017

Nakano and Shibahara [161]

           

      

2017

Endo and Fuse [162]

       

          

2017

Miskolczi et al. [173]

           

      

2018

Khodier et al. [163]

           

      

2018

Zhang and Chen [164, 168]

             

   

2018

Hao et al. [165]

 

     

          
  

Method(s) used in the study

Year

Author(s)

ABC

AHP

DEA

FA

FGDM

LCA

LCC

MBM

MFA

MILP

MM

SD

SW

TP

2018

Mohan and Amit [166]

           

  

2018

Raja Mamat et al. [5]

 

            

2018

Rosa and Terzi [167]

           

  

2018

Wong et al. [169]

     

        

2018

Ortego et al. [170]

          

   

2018

Lin et al. [171]

        

    

2018

Gottesfeld et al. [183]

     

        

2018

Ericson et al. [184]

     

        

2018

Eguchi et al. [187]

     

        

2018

Xu et al. [172]

        

     

2019

Sato et al. [174]

     

        

2019

Arora et al. [175]

            

 

2019

Mohamad-Ali et al. [176]

   

          

2019

Qiao et al. [177]

      

   

   

2019

Wang et al. [178]

  

          

2019

Yang et al. [179]

    

         

2019

Yano et al. [180]

       

     

Literature survey

Table 1 overviews 21 review studies in the literature regarding their research focus, analyzed period and number of reviewed papers. They should be presented here to highlight the need for this research. Nourreddine [12] provided an overview of several automobile shredder residue (ASR) treatment processes. Kumar and Sutherland [13] presented an overview of studies on the vehicle recovery infrastructure. A review of the literature published in the years 2010 and 2012 on topics relating to automotive wastes was presented in Bari et al. [14] and Kindzierski et al. [15], respectively. Vermeulen et al. [16] critically reviewed ELV processing-related issues. Go et al. [17] presented a review of several disassemblability methods, including a spreadsheet-like chart, end-of-life value and time for disassembly. Zorpas and Inglezakis [18] investigated the ASR problem and the options for its processing. Mayyas et al. [19] investigated the sustainability research within the vehicle industry, through a review of the different studies in vehicles’ life cycle, disposal, and end-of-life treatment. Lashlem et al. [20] presented a brief review of ELV management practices worldwide. Simic [3] reviewed the environmental engineering issues of ELV recycling by covering a wide range of peer-reviewed journal papers. Gan and He [21] presented a short review of ELV reverse logistics. Li et al. [22] provided an overview of present ELV management practices in China. Sakai et al. [23] provided a comparative analysis of ELV management practices in several countries. Hiratsuka et al. [24] discussed the background of the establishment of the ELV recycling system in Japan, its features and perspectives. Buekens and Zhou [25] reviewed the most prominent options for recycling plastics from ASR. Zhang and Chen [26] discussed ELV-related regulations in the USA, the EU, Japan, Korea, and China, and analyzed accessible recycling technologies for automotive plastic components. Cossu and Lai [27] presented a general overview of post shredder technologies for the treatment of ASR. Cucchiella et al. [28] provided a mini-review on the automotive electronics recycling topic. Rosa and Terzi [29] compared ELV and WEEE waste streams through a structured literature analysis under several perspectives by evidencing current differences and potential commonalities. Cin and Kusakci [30] presented a brief review of reverse logistics networks for ELVs. De Almeida and Borsato [31] provided a bibliometric literature review to assess the efficiency of the available treatment of end-of-life products.

Recycling, production and planning

Being a strategic and a tactical issue to deal with for companies and governments, there are a significant number of studies focusing on the process and material analyses, product design, production and recycling planning.

Kirkpatrick et al. [32] investigated the environmental impacts of ELV disposal in the UK. Bellman and Khare [33] attempted to analyze financial sources of the ELV management and suggested a few policies about producer responsibility. Hartman et al. [34] presented a project to develop and demonstrate a method and the business potential in re-using components from ELVs. Díaz and Fernández [35] defined future treatment centers for ELV processing. Mark et al. [36] presented a demanufacturing chain under different scenarios to do economic analyses for vehicle instrument panels. Johnson and Wang [37] presented a demanufacturing optimization model to evaluate economics and material destinations within the requirements of the new ELV legislation. Petrov [38] developed a concept for an ELV recycling system for a Russian automotive company.

Johnson and Wang [39] presented an analysis tool that uses demanufacturing optimization to evaluate the economics and material destinations. Van Schaik et al. [40] proposed a dynamic optimization model for recycling aluminum from passenger vehicles. Boon et al. [41] proposed a model to assess the materials streams and process profitability for several clean vehicles via Goal programming. Petrov [42] researched recyclability of all basic LADA family automobiles to meet European ecological requirements. Castro et al. [43] performed the Life cycle impact assessment of the average passenger vehicles of the Netherlands, with emphasis on the current dismantling and recycling practices.

Gesing [44] reviewed current and future recycling technologies with a focus on increasing light material content. Mark and Kamprath [45] summarized various bonding applications and their materials aspect for vehicle lightweighting. Van Schaik and Reuter [46] developed dynamic modeling and simulation approaches to illustrate the influence of various parameters on the recycling rate. Van Schaik et al. [47] proposed a nonlinear optimization model to describe the relationship between particle size reduction and liberation during the shredding and recycling of ELVs. Kim et al. [48] surveyed using some questionnaires processing rates and management status in Korea to aid the establishment of ELV management policies. Schmidt et al. [49] aimed at identifying the environmental impacts and relevance for combinations of recycling/recovery and lightweight vehicle design options over the whole life cycle. Pelletiere and Reinert [50] presented a database on used automobile protection, and employed gravity models of the used automobile trade. Bandivadekar et al. [51] presented a simulation model for material flows and economic exchanges to examine the effect of future changes in vehicle material compositions on the US recycling infrastructure.

Sawyer-Beaulieu and Tam [52] used Life-cycle assessment (LCA) to increase the understanding of and consequently improve the ELV management process in North America. Seo et al. [53] published a study about the ELV management and ASR characterization in Korea. Choi et al. [54] presented a mixed-integer programming model for tactical process planning in the case of traditional US automotive shredders. Castro et al. [55] presented a simulation model that describes the relationships between product design and the liberation level attained by the shredding of passenger seats. Forslind [56] analyzed the consequences of implementing EPR for vehicle recyclers in Sweden.

Chen [57] conducted a study to address the sustainable recycling of Chinese automobile products within the period of 2006–2010. Ferrao et al. [58] assessed the influence of the ELV Directive on the profitability of vehicle dismantlers and shredders. Krinke et al. [59] compared the environmental profiles of two different ELV recycling methods. Reuter et al. [60] explored the limits of ELV recycling. Forton et al. [61] emphasized current issues and drivers at play on the ELV management in the UK to outline their actual effects on present practice. Finkbeiner et al. [62] expressed the use of LCA on Mercedes-Benz S-Class vehicles. Mazzanti and Zoboli [63] addressed the ways specific to economic instruments reflecting the producer responsibility principle in waste and recycling policy. Amaral et al. [64] discussed how far recycling technology innovation can be a major driver for technology shift in the automobile industry. Ferrao and Amaral [65] developed technical cost models to assess the economics of dismantling and shredding activities. Pelletiere and Reinert [66] modeled the used automobile exports of Japan and the USA using two alternative gravity models.

Coates and Rahimifard [67] provided an overview of the stakeholders and their relationships within the UK recovery chain and discussed the development of an ELV costing framework. Jeong et al. [68] focused on the ELV treatment system in Korea using LCA methodology to evaluate its environmental performance and identify potential improvement opportunities. Joung et al. [69] investigated the recycling rate and management status to aid the establishment of a policy for the ELV management in Korea. Mergias et al. [70] used the PROMETHEE method to select the best compromise scheme for the ELV management in Cyprus. Dalmijn and De Jong [71] analyzed the development of the vehicle recycling industry in the EU. Giannouli et al. [72] developed a methodology and technical model for the evaluation of waste produced from road vehicles. Sakai et al. [73] investigated the unintentional formation, decomposition, and emission-control performance of POPs during ASR incineration. Williams et al. [74] proposed a MILP model for making tactical decisions regarding what extent to process and reprocess materials. Alonso et al. [75] published a research project to contribute cost-effective and eco-efficient electrical and electronic systems components in the automotive industry. Frad and Revnic [76] presented a method to assure the achievement of the required eco-efficiency rates, integrated into the software tool for car manufacturing. Ribeiro et al. [77] modified a multi-material car component which is a part of the current automotive brake system, by its original manufacturer. Fuse et al. [78] quantified the outflow of base metals indirectly exported from Japan in the form of ELVs.

Ignatenko et al. [79] extended the optimization model proposed by Reuter et al. [60] to add thermal treatment processes and energy recovery constraints. Qi and Hongcheng [80] proposed a MILP model for designing an ELV recovery network constituted from dismantling centers and processing facilities. Sawyer-Beaulieu and Tam [81] used LCA to analyze ELV dismantling and shredding processes. Smith and Keoleian [82] investigated the energy savings and pollution prevention in the US through remanufacturing a midsized automotive gasoline engine. Fuse and Kashima [83] developed an automobile recycling input–output analysis-based evaluation method to examine the appropriateness of the recycling scheme for ELVs imported from Japan. Qu and Williams [84] formulated automotive reverse production planning and pricing problems in a nonlinear programming model to develop an approximate supply function for hulks.

Chondros [85] reviewed ELV treatment alternatives to ease the creation of an efficient ELV management system in different local conditions. Puri et al. [86] stimulated material alternatives and end-of-life strategies for automotive components. Amelia et al. [87] identified the existing conditions of automotive reuse in Malaysia by conducting interviews in selected local automotive and component manufacturers. Chen and Zhang [88] provided insight into current thinking within China about the ELV management as well as vehicle recovery activities. Kumar and Sutherland [89] focused on certain profit-enhancement strategies that may be employed to ensure the economic sustainability of ELVs. Fuse et al. [90] proposed an estimation method for calculating the number of used passenger cars employed in world trade. Differently, Fuse et al. [91] used the regression analysis to estimate the global flow of base metals (iron, aluminum, copper, lead, and zinc) in the used automobile trade.

Santini et al. [92] studied the impact that pre-shredder treatment could have on achieving 85% recyclability rate in 2015. Chen et al. [93] thoroughly described the principles and characteristics of the vehicle recycling system in Taiwan. Go et al. [94] provided a framework for automotive components to be designed for ease of recovery by optimizing the disassembly sequence. Mathieux and Brissaud [95] presented a new method to elaborate end-of-life product-specific material flow analysis, based on data obtained from statistics as well as from expert elicitation.

Agbo [96] quantified the available salvage value and service materials potential from imported used vehicles in Nigeria. Duranceau and Sawyer-Beaulieu [97] determined and quantified today’s actual ELV disposition rates based on their age and material content. Hedayati and Subic [98] proposed a decision-making support framework for the recovery of ELVs to provide an integrated sustainable treatment option. Kibira and Jain [99] studied the impact of hybrid and electric vehicles on the profitability of the recycling infrastructure. Santini et al. [100] reported a shredder campaign trial developed and performed in Italy at the beginning of 2008. Xi et al. [101] proposed a new method for predicting the residual strength and life of reused components or parts of ELVs. Zoraga et al. [102] calculated energy consumption and carbon dioxide emissions of ELV recycling. Che et al. [103] presented the ELV recycling system of Japan, China and Korea and in developing countries as well. Nazmi et al. [104] suggested an ANN-based tool for predicting the critical stress life of a vehicle door with focusing on the optimal reusability.

Filho [105] analyzed the various constituent vehicle materials and their impact on the environment in Brazil. Fiore et al. [106] presented a characterization and valorization study about ASR in Italy. Millet et al. [107] proposed a method based on an impact module on recycling rate indicators for identifying the worst recycling case. Nakamura et al. [108] presented a novel approach to quantifying quality and dilution losses through hybrid input–output analysis. Santini et al. [109] investigated ASR pre-treatment and pyrolysis to determine whether the ELV recycling target could be achieved by car fluff mechanical separation. Cheng et al. [110] introduced a preliminary approach to examine the operational characteristics of the ELV recycling business in Taiwan. Hatayama et al. [111] discussed how the recycling of aluminum will change until 2050, focusing on the introduction of next-generation vehicles and scrap sorting technology. Wang and Chen [112] analyzed the current ELV recycling system in China and introduced an automotive product recycling technology roadmap. Simic and Dimitrijevic [113] expanded the linear programming modeling framework proposed by Simic and Dimitrijevic [114] to incorporate the vehicle hulk selection problem. Simic and Dimitrijevic [114] presented a tactical production planning problem for vehicle recycling factories in the EU legislative and global business environments.

Arena et al. [115] developed a performance measurement system to help automotive manufacturers to assess their technological options for sustainable mobility. Simic and Dimitrijevic [116] proposed a short-term ASR recycling planning model for the Japanese vehicle recycling industry. Simic and Dimitrijevic [117] developed a risk explicit MINP model for optimal long-term planning in the EU vehicle recycling facilities. Berzi et al. [118] built a process simulation model that could be used for layout planning of ELV dismantling facilities. Tasala Gradin et al. [119] applied the LCA method to compare two waste management scenarios: manual disassembly and shredding. Saavedra et al. [120] presented an exploratory study on the current remanufacturing scenario and its main characteristics within the Brazilian automotive sector. Schmid et al. [121] present the results from the quantitative and qualitative characterization of different material flows resulting from the three experimental campaigns on an industrial site. Hu and Kurasaka [122] developed a projection model for ELV distribution per population at the provincial level in China.

Miller et al. [123] examined the challenges of plastics recycling in the North American automotive industry. Ruffino et al. [124] performed an economic assessment of a hypothetical industrial recovery process of light ASR, obtained by transferring the results gathered at lab scale to full scale. Sawyer-Beaulieu et al. [125] presented strategies and actions for decreasing the lifecycle impact of automobiles. Tian and Chen [126] illustrate the difficulty of handling polymers from a vehicle dashboard. Ahmed et al. [127] examined the current state of the ELV management in Malaysia. Lu et al. [128] identified drivers for new joining solutions in the automotive industry and specifically reviewed the current use of adhesive technology in ELVs. Yano et al. [129] investigated the dynamic substance flow of lead as a representative toxic substance in ELVs and ASR. They applied a population balance model for estimating the number of generated ELVs in Japan between fiscal years 1990–2020.

El Halabi et al. [130] assessed the environmental impact of using a multi-dismantling machine for material separation. Chen et al. [131] applied dynamic modeling and cost–benefit analysis to investigate how policies may affect the recycling of ELVs in China. Despeisse et al. [132] proposed policy, technical and business recommendations to improve reuse, recycling, and recovery rates. Ohno et al. [133] used a waste input–output material flow analysis to investigate the content of alloying elements in ELVs. Sawyer-Beaulieu and Tam [134] discussed the challenges anticipated with the development of ELV management systems. Yi and Park [135] developed a smart dismantling monitoring and smart trolley system for an ELV recycling center. Simic and Dimitrijevic [136] formulated and comprehensively tested a model for optimal long-term planning of vehicle recycling in the Republic of Serbia. The lifespan of a vehicle determines the amount of end-of-life flows. Oguchi and Fuse [137] proposed a straightforward method for estimating the lifespan distribution of passenger cars based on the age profile of in-use cars.

Belboom et al. [138] undertook an environmental evaluation of hybrid vehicles recycling using industrial data from Comet Traitement SA in Belgium. Desnica et al. [139] presented an AHP approach to select equipment for detoxification of ELVs. Inghels et al. [140] assessed the influence of material composition, amount and lifespan of passenger cars on the ELV management in Belgium. Junior et al. [141] addressed vehicle recycling processes and manufacturer responsibility around the globe and the benefits to the economy, society, and environment. Pan and Li [142] employed an improved emergy analysis with traditional and revised emergy indices for evaluation of the efficiency and sustainability of ELV recycling enterprises. Ahmed et al. [143, 144] used DEMATEL and extent analysis method on the fuzzy AHP to rank ELV management alternatives concerning several sustainable criteria. Pourjavad and Mayorga [145] also proposed an integrated fuzzy DM framework to evaluate sustainable ELV strategies. Pourjavad and Mayorga [146] coupled the fuzzy AHP and fuzzy TOPSIS methods to rank seven ELV management strategies. Raja Mamat et al. [147] develop a framework for the ELV management in Malaysia. Li et al. [148] evaluated the environmental impacts of ELV recycling processes in China. Tian and Chen [149] used the fuzzy AHP technique and cost–benefit analysis to compare five manual dismantling scenarios in China. Xia et al. [150] applied cost–benefit analysis to perform the construction and investment analysis of an ELV disassembly plant in China. Zhou et al. [151] developed a multi-criteria model based on the fuzzy VIKOR technique to evaluate ELV recycling service providers from the perspective of sustainability. Diener and Tillman [152] examined the case of an automotive component manufacturer to investigate its ELV management. Xu et al. [153] conducted a scenario analysis to determine the amount of rare earth elements that can be recovered from ELVs in Japan based on a dismantling survey, chemical identification, and substance flow analysis. Yano et al. [154] used a population balance model for estimating the number of end-of-life hybrid electric vehicles generated in Japan during fiscal years 2010–2030. Besides, the amounts of rare earth elements contained in a hybrid transmission and a NiMH battery unit were presented.

Andersson et al. [155] utilized the technological innovation system framework to identify key functions from 1910 to 2010 that enabled ELV iron recycling in Sweden. Ene and Öztürk [156] developed an approach for predicting the number of ELVs that will be generated in the future. Gan and Luo [157] presented a fuzzy-based DEMATEL approach to identify critical factors influencing the recycling rate of ELVs. Karaeen et al. [158] presented a concept for the second life cycle of vehicles. Soo et al. [159] discussed a comparative study on the environmental performance of the current ELV recycling processes between Australia and Belgium. Soo et al. [160] analyzed the joining technologies used in the automotive industry to identify the ELV recyclability. Nakano and Shibahara [161] used the LCA method for quantifying the amounts of greenhouse gases emitted when recycling ELVs by using the traditional shredding approach and the whole recycling approach, in which ELVs are pressed and transferred to an electric furnace or converter. Endo and Fuse [162] explored and reduced the uncertainty in international trade for used automobiles and engines by correcting outliers and missing values.

Khodier et al. [163] focused on challenges around ASR processing and disposal in the UK. Zhang and Chen [164] used the AHP method to compare four ELV dismantling planning scenarios. Hao et al. [165] aimed to better manage the reverse supply chain of the automotive industry in the context of green, circular, and sustainable development. Mohan and Amit [166] proposed a system dynamics model to analyze informal dismantling facilities in India, which operate like a perfectly competitive market. Raja Mamat et al. [5] proposed a performance evaluation tool based on the Analytic Hierarchy Process for implementation, monitoring and continuous improvement of the Malaysian ELV management system. Rosa and Terzi [167] evaluated the current economic performances of the Italian ELV recovery chain using the system dynamics simulation approach. Zhang and Chen [168] constructed an Arena-based simulation tool to analyze four scenarios of an ELV disassembly line in China. Wong et al. [169] proposed a new concept of a processing framework to utilize ELV waste to construction industries via a new trend of circular economy applications in Malaysia. Ortego et al. [170] proposed a downcycling assessment methodology based on the thermodynamic rarity indicator for accounting quantity and quality of the materials lost in the ELV recycling process. Lin et al. [171] used a population balance model for predicting the number of generated ELVs in Kinmen, Taiwan, in the period 1960–2050. They presented material flow and economic analyses of a dismantling business in small islands. Xu et al. [172] performed a scenario analysis to determine the amount of five precious metals that could be returned to material streams from ELVs based on the dismantling survey, chemical identification, and substance flow analysis. Also, a population balance model was utilized for forecasting the number of generated ELVs in Japan in the period 2015–2040.

Miskolczi et al. [173] proposed a study about the modification of zeolite catalysts by metal loading for using ELV plastic waste pyrolysis. Sato et al. [174] proposed an evaluation method to assess benefits with enabling energy consumption and carbon dioxide emission. Arora et al. [175] attempted to use the shared responsibility based framework to explore and develop a business model of the ELV management in India. Mohamad-Ali et al. [176] carried out a survey to identify the issues and factors of the ELV recovery system in Malaysia. Qiao et al. [177] presented a survey that focused on the economic and environmental benefits of electric vehicle recycling in China. Wang et al. [178] analyzed the efficiency of the ELV reverse logistics industry to improve resource utilization efficiency in Shanghai, China. Yang et al. [179] presented a systematic index system in selecting criteria for sustainable ELV management via constructing a group DM approach in a fuzzy environment. Yano et al. [180] conducted a dismantling survey and chemical analysis of six ELVs to estimate the content of valuable and toxic elements/substances.

Used lead-acid battery recycling is a growing hazardous industry. The lead issues from automotive battery recycling are major sources of soil contamination and human health exposure. The management of this hazardous waste from the ELV recycling process was mainly neglected in the previous reviews (Table 1). Hoffmann and Wilson [181] provided a brief characterization of the lead-acid battery recycling industry in the Philippines. Haefliger et al. [182] investigated a mass lead intoxication that occurred as a result of unsafe informal automotive lead-acid battery recycling in Dakar, Senegal. Gottesfeld et al. [183] assessed soil contamination inside and outside recycling plants operating with government approval to recycle used lead-acid batteries in seven African countries. Several studies investigated soil contamination and human health exposure in the battery recycling craft village, Dong Mai, Vietnam [184, 185, 186, 187, 188]. For instance, Ericson et al. [184] evaluated the efficiency of a novel soil lead mitigation project, Noguchi et al. [185], Daniell et al. [186], and Eguchi et al. [187] assessed human lead exposure, while Fujimori et al. [188] studied the lead contamination level in surface soil on roads. Ericson et al. [189] estimated the number of informal lead-acid battery recyclers and the number of exposed people in 90 low- and middle-income countries.

The previous studies, related to recycling processes and analyses of materials, mostly suggested solutions for various local problems. More general and global approaches are highly needed. Moreover, material concepts and perceptions of the vehicles tend to change. Thus, more studies regarding this issue are needed in the future. Furthermore, most of the studies which are considering the managerial perspective are suggesting solutions about economic and/or material issues. There are not enough studies that include social criteria. The participation of the public is an important factor for the ELV management. Owners of ELVs need to be encouraged to withdraw their vehicles from the traffic. For this reason, social acceptance and social awareness are also important problems to deal with for more effective ELV management.

Although there are various types of product design and production planning studies about the ELV management, there are not enough studies comparing the designing and planning systems as before and after. Effects of recycling friendly product design and production planning could be monitored via customer feedbacks, financial analyses, etc.

Due to new ELV regulations, producers’ responsibilities are gaining importance. Manufacturers are expected to make their designs and revise their production plans according to legislation. Herewith, there are several types of approaches studied by the researchers.

Network design

The recycling process of ELVs includes its own supply chain management problem. There are numerous studies in the literature which are suggesting approaches to cope with supply chain issues of the ELV management. Ahn et al. [190] created an optimization tool for solving facility location problems and developed a simulation tool for ELVs of the German automobile industry. Schultmann et al. [191] presented the peculiarities of establishing a closed-loop supply chain (CLSC) for ELVs. Mansour and Zarei [192] developed a multi-period reverse logistics optimization model to locate ELV collection centers and vehicle dismantlers. Cruz-Rivera and Ertel [193] constructed an uncapacitated facility location model to design a collection network for ELVs in Mexico.

Merkisz-Guranowska [194, 195] formulated MILP models to determine the optimum locations of the key participants of the ELV recycling network. Zarei et al. [196] designed a reverse logistics network for the management of the ELV recovery process. Harraz and Galal [197] presented a mixed-integer lexicographic goal programming for designing a sustainable recovery network for ELVs in Egypt. Mahmoudzadeh et al. [198] proposed a capacitated location-allocation model for determining locations of ELV collection points from the perspective of the third-party reverse logistics provider. Vidovic et al. [199] presented a modeling approach that could be used to locate collection points for ELVs.

Merkisz-Guranowska [200, 201] formulated a bi-objective mixed-integer linear programming model aiming at the reorganization and construction of the ELV recycling network in Poland. Farel et al. [202] used a MILP modeling technique to determine the optimal topology and material flow in future ELV glazing recycling network. Gołebiewski et al. [203] proposed a simulation approach that could be used to determine optimum locations for ELV dismantlers. Mahmoudzadeh et al. [204] used a MILP formulation to solve a location-allocation problem of ELVs scrap yards in Iran.

Ene and Öztürk [205] developed a model for managing reverse flows of ELVs within the framework of a multi-period, multi-stage, capacity-constrained network design problem. Simic [206] developed a two-stage interval-stochastic programming model for supporting the management of ELV allocation under uncertainty. Simic [207] proposed a fuzzy risk explicit MINP model for ELV recycling planning in the EU. Subulan et al. [208] formulated a multi-objective, multi-echelon and multi-product mixed-integer linear programming model with fuzzy objectives for optimizing the lead-acid battery CLSC in Turkey.

Alsaadi and Franchetti [209] studied on finding the optimum location for a processing facility for ELVs. Demirel et al. [210] proposed a MILP model for reverse logistics network design including different actors taking part in the ELV recycling system. Simic [211] presented a multi-stage interval-stochastic programming model for planning ELV allocation. Simic [212] proposed an interval-parameter two-stage stochastic full-infinite programming model for ELV allocation management under multiple uncertainties. Simic [4] developed an interval-parameter chance-constraint programming model for uncertainty-based decision-making in the ELV recycling industry under rigorous environmental regulations.

Phuc et al. [213] formulated a fuzzy MILP model for designing a multi-echelon, multi-product reverse logistics network. Özceylan et al. [214] presented a case study from Turkey based on CLSC for ELV treatment. Deng et al. [215] established a simulation–optimization model for the location, path and inventory problem of ELV recycling systems. Lin et al. [216] proposed a MILP model for the facility location-allocation problem of an ELV recovery network. Shankar et al. [217] formulated a MILP model for the CLSC network with a multi-echelon inventory, multi-period planning, and multi-product scenario. Sun et al. [218] developed a mixed-integer bilevel linear programming model to locate distribution centers for collecting ELV parts. The outer and inner optimization tasks were minimizing location costs and transportation costs, respectively. Ma and Li [219] proposed a two-stage stochastic programming model for solving the lead-acid battery CLSC problem with random demands and returns.

Kuşakcı et al. [220] modeled the problem of designing the ELV reverse logistics network for the Istanbul Metropolitan area as a fuzzy mixed-integer linear program. Xiao et al. [221] developed a MILP model for constructing a four-tier reverse logistics network model, which included ELV sources, collection centers, remanufacturing centers, and dismantlers.

In addition, the publications including mathematical models were categorized based on the type of decision variables, optimization model and solution approach. They are summarized in Table 3.
Table 3

Summary of the publications with an optimization model

Year

Author(s)

Type of decision variables

Optimization model

Single-multi objectivity

Type of objective function(s)

Type of parameter(s)

Type of supply chain

Solution approach

  

LA

RP

PP

LP

NLP

MILP

MINP

Single

Multi

Max

Min

Det.

Prob.

Fuzzy

OL

CL

E

H

MH

2002

Van Schaik et al. [40]

 

 

   

 

 

 

 

  

2003

Boon et al. [41]

 

 

   

 

 

  

 

  

2004

Van Schaik et al. [47]

 

  

  

  

  

 

  

2005

Ahn et al. [190]

    

 

  

  

  

 

2005

Choi et al. [54]

 

   

 

 

 

  

 

  

2006

Reuter et al. [60]

 

 

   

 

 

  

 

  

2006

Schultmann et al. [191]

    

 

  

  

  

 

2007

Williams et al. [74]

 

   

 

 

 

  

 

  

2008

Ignatenko et al. [79]

 

   

  

   

  

2008

Mansour and Zarei [192]

    

 

  

   

 

 

2008

Qu and Williams [84]

  

 

  

 

 

  

 

  

2008

Qi and Hongcheng [80]

 

   

 

  

   

  

2009

Cruz-Rivera and Ertel [193]

    

 

  

   

  

2010

Zarei et al. [196]

     

  

   

 

 

2010

Merkisz-Guranowska [194]

    

 

  

  

 

  

2011

Vidovic et al. [199]

    

 

 

 

  

 

  

2011

Merkisz-Guranowska [195]

  

   

  

  

 

  

2011

Mahmoudzadeh et al. [198]

  

   

  

  

 

  

2011

Harraz and Galal [197]

    

  

  

 

  

2012

Merkisz-Guranowska [200]

  

    

  

 

  

2012b

Simic and Dimitrijevic [113]

  

   

 

 

  

 

  

2013a

Farel et al. [202]

    

 

 

 

  

 

  

2013a

Simic and Dimitrijevic [115]

  

   

 

 

  

 

  

2013

Gołębiewski et al. [203]

  

   

  

  

  

 

2013

Merkisz-Guranowska [201]

    

  

  

 

  

2013b

Simic and Dimitrijevic [116]

  

    

  

 

  

2013

Mahmoudzadeh et al. [204]

  

   

  

   

  

2015a

Simic [206]

  

    

 

 

  

2015b

Simic [207]

  

    

 

 

  

2015

Simic and Dimitrijevic [135]

  

   

 

 

  

 

  

2015

Ene and Öztürk [205]

    

 

 

 

  

 

  

2015

Subulan [208]

 

   

  

 

 

  

2016a

Simic [211]

  

   

 

 

 

 

  

2016b

Simic [212]

  

   

 

 

 

 

  

2016c

Simic [4]

    

 

 

 

 

 

  

2016

Demirel et al. [210]

    

 

  

  

 

  

2016

Alsaadi and Franchetti [209]

    

 

  

  

 

  

2017

Phuc et al. [213]

  

   

  

 

 

  

2017

Özceylan et al. [214]

  

   

 

 

   

  

2018

Lin et al. [216]

    

 

  

  

   

2018

Shankar et al. [217]

  

   

 

 

   

  

2018

Sun et al. [218]

  

   

  

  

 

  

2018

Deng et al. [215]

    

 

  

  

 

  

2018

Ma and Li [219]

 

   

 

 

 

  

 

2019

Xiao et al. [221]

  

   

  

  

 

  

2019

Kuşakcı et al. [220]

  

   

  

 

 

  

LA location allocation, RP recycling planning, PP production planning, LP linear programming, NLP non-linear programming, MILP mixed-integer linear programming, MINP mixed-integer non-linear programming, OL open loop, CL closed loop, E exact, H heuristics, MH meta-heuristics

Available investigations that are suggesting approaches to cope with supply chain issues of the ELV management are mostly performed with deterministic data. ELV management systems are complex waste management systems with many uncertain components. Uncertainties also exist with economic and technical parameters, ELV supply, etc. Moreover, most of the real-life applications involve highly complex uncertainty. Therefore, an extension of the available modeling frameworks to address uncertainties can provide a much more realistic representation of ELV management systems.

Regulations review

Several regulation analyses are made in the literature as legislations play an important role in the ELV management. Levizzari [222] addressed the impacts of the ELV Directive on the Italian automotive industry. Kanari et al. [223] analyzed the current situation and future of the ELV management in the EU. Sakkas and Manios [224] identified and evaluated investment strategies for the ELV management in Greece. Smith et al. [225] examined how the abandoned vehicle problem is likely to develop in the future with the introduction of new laws and initiatives.

Chen [226] reviewed the ELV policy, law and administration system in China. Marsh [227] reported a survey about recycling collaborative combats legislation threat. Nakajima and Vanderburg [228] described and analyzed the German ELV take-back system in terms of its impact on the environment and companies involved. Edwards et al. [229] presented a basis for future research by evaluating the potential direction of the recovery industry. Saman and Blount [230] provided a review of current practices in vehicle recycling in Europe, USA, Japan, and Australia together with an overview of legislation, stakeholders and corresponding markets.

Gerrard and Kandlikar [231] presented an evaluation framework based on anticipated changes that could result from the ELV Directive. Smink [232] evaluated the extent to which environmental regulations have been a driving force for change in the car-dismantling trade in Denmark. Manomaivibool [233] explored the impacts of network management on the environmental effects of the programs for the ELV management in the UK and in Sweden from an EPR perspective. Smith and Crotty [234] examined the impact of the ELV Directive on vehicle component manufacturers in the UK using a questionnaire tool.

Konz [235] presented a survey to analyze the ELV Directive. Altay et al. [236] focused on the recycling of metal from ELVs in Turkey and its legislative relations with the Kyoto Protocol. Zhao and Chen [237] gave a brief introduction to ELV regulations in Japan and China. Wang and Chen [238] compared ELV legislation between China, EU, Japan, and Korea to improve the policy implementation on ELV recycling in China. Blume and Walther [239] examined the legislative influence on the German vehicle industry. Farel et al. [240] proposed a model to investigate the potential cost and benefit of the ELV glazing recycling network in France.

Table 4 presents the summary of regulations review publications in the literature.
Table 4

Summary of regulations review publications on the ELV management

Author(s) and year

Research focus

Levizzari (2002) [222]

Italy

Kanari et al. (2003) [223]

Marsh (2005) [227]

The European Union

Gerrard and Kandlikar (2007) [231]

Sakkas and Manios (2003) [224]

Greece

Smith et al. (2004) [225]

England and the United Kingdom

Edwards et al. (2006) [229]

Smith and Crotty (2008) [234]

Chen (2005) [226]

China

Wang and Chen (2013) [238]

Nakajima and Vanderburg (2005) [228]

Germany

Blume and Walther (2013) [239]

 

Saman and Blount (2006) [230]

The European Union, the USA, Japan, and Australia

Smink (2007) [232]

Denmark

Manomaivibool (2008) [233]

The United Kingdom and Sweden

Konz (2009) [235]

The USA

Altay et al. (2011) [236]

Turkey and Kyoto Protocol

Zhao and Chen (2011) [237]

China and Japan

Farel et al. (2013) [240]

France

Most of the studies in the scope of regulative analyses are mainly considering local case studies. However, regulations globally affect many countries in the world simultaneously.

Discussion

The ELV management is such a crucial issue to deal with for the actors like governments, producers, treatment facilities and users. Due to regulations and new legislation, it is becoming even more important both environmentally and economically. Apart from being an operational process, it is also a type of strategic and tactical level decision for decision-makers.

Figure 4 shows the distribution of studies per year between 2000 and 2019. Based on Fig. 4, 61.6% of studies on the ELV management (143 out of 232) were published in the last nine years. Therefore, there is a significant increase in the number of publications in the area of the ELV management after the year 2011. Furthermore, Fig. 1 also presents that the production rate of passenger vehicles has had an upward trend simultaneously.
Fig. 4

Distribution of studies per year across the period 2000–2019

Figure 5 presents the quantity and percentage of studies based on their purpose. According to Fig. 5, the majority is in the scope of “Recycling, production and planning” category. Although the ELV management has a multidisciplinary concept, the lack of hybrid studies can be clearly identified.
Fig. 5

ELV management studies based on their major classification

Figure 6 provides the distribution of the studies based on the applied method. Based on Fig. 6, 32.08% of studies in the scope of “Recycling, production and planning” on the ELV management (51 out of 159) applied the LCA method. It is possible to see that publications are not homogenous based on the method applied. As a multidisciplinary subject, there are many possible issues to deal with while solving ELV management problems. In fact, new combinations in methodology may offer new solutions for real-life cases.
Fig. 6

Applied method

Figure 7 presents the percentage and quantity of the publications with a mathematical optimization model based on the type of parameters used in the analyzed studies. According to Fig. 7, the vast majority of researchers preferred to use deterministic parameters. It is not realistic to study with deterministic parameters for real-life cases. Therefore, new approaches with probabilistic and fuzzy parameters should be in the focus of future contributions.
Fig. 7

Type of parameters

Figure 8 shows the distribution of papers based on the studied type of supply chain network of ELVs and its components. Based on Fig. 8, 76.09% of studies on the ELV management (35 out of 46) are dealing with open-loop supply chain problems. In fact, there is a lack of research suggesting a solution for both open- and closed-loop supply chains.
Fig. 8

Type of supply chain

Figure 9 presents the number and percentage of the studies with a mathematical optimization model based on the type of decision variables. These studies mostly preferred to deal with location-allocation problems (31 out of 46). There are not enough hybrid approaches in this field. Furthermore, studies in the scope of production and recycling planning are very limited.
Fig. 9

Studies with a mathematical optimization model based on the type of decision variables

Figure 10 presents the quantity and percentage of the collected studies based type of optimization model. From Fig. 10, it is evident that studies with a mathematical optimization model are mostly based on linear programming and MILP. Only 3 out of 46 studies developed non-linear optimization models.
Fig. 10

Type of optimization model

Figures 11, 12 present distributions of studies with a mathematical optimization model based on single-multi objectivity and type of objective function, respectively. The lack of multi-objective approaches is more than evident; i.e., 82.61% for single-objective studies and 17.39% for multi-objective studies (Fig. 11). According to Fig. 12, both types of objective functions are considered in just 17.39% of the studies with a mathematical model. It should be mentioned that the majority of the studies with a mathematical model considered cost as its objective function (Fig. 12). There are other objective targets either conflicting or non-conflicting to optimize in the ELV management models.
Fig. 11

Studies with a mathematical optimization model based on single-multi objectivity

Fig. 12

Studies with a mathematical optimization model based on the type of objective function

Figure 13 presents the quantity and percentage of studies with a mathematical model based on the solution approach. It indicates that the vast majority of the approaches offered exact solutions instead of heuristics and meta-heuristics since most of them deal with either small or medium-size cases. Real-life ELV management problems usually need inexact colution approaches for generating reasonable solutions.
Fig. 13

Studies with a mathematical model based on the solution approach

The distribution of studies on the ELV management based on the source of publication is presented in Table 5. The journals with five or more publications are provided in the table. The primary publication outlets for the ELV management research area are: Journal of Cleaner Production (12.07% share), Resources, Conservation and Recycling (10.78% share), Journal of Material Cycles and Waste Management (7.76% share), and Waste Management (7.76% share), jointly publishing 38.4% of the total number of studies on the ELV management printed in the period 2000–2019. Moreover, these four journals published almost 47% of the total identified number of studies in the past five years. On the other hand, the secondary publication outlets for the explored research area are JOM (2.59% share), The International Journal of Life Cycle Assessment (2.59% share), and Waste Management and Research (2.16% share). Finally, reviewing tables in this study confirmed that the ELV management is considered by numerous journals.
Table 5

Distribution of studies on the ELV management based on the source of publication

Journal

Year of publication

Total

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

J. Cleaner Prod.

1

3

2

1

1

6

1

5

4

4

28

Resour. Conserv. Recycl.

2

1

1

1

2

2

4

5

2

2

1

2

25

Waste Manage.

1

1

1

2

1

2

2

4

2

2

18

J. Mater. Cycles Waste Manage.

2

1

1

1

7

3

1

2

18

JOM

1

1

1

1

1

1

6

Int. J. Life Cycle Assess.

1

1

2

1

1

6

Waste Manage. Res.

2

1

1

1

5

Others

4

4

3

3

4

7

9

8

7

6

3

13

5

5

5

8

10

8

11

3

126

Total

4

4

3

5

9

9

13

16

10

11

6

17

13

18

14

14

25

11

19

11

232

Conclusions

This paper presents a comprehensive literature review of the ELV management research area. Totally, 232 studies published in the period 2000–2019 are collected, categorized, reviewed and analyzed. The review has shown that there is a significant increase in the number of studies after the year 2011. Most researchers focused their attention only on the managerial perspective. The vast majority of researchers used only deterministic parameters. Only a few researchers suggested a solution for both open- and closed-loop supply chains. The studies with mathematical models mainly considered location-allocation problems. These studies were mostly formulated as linear programs. Attention to multi-objective problem formulations is low. The studies almost exclusively considered cost or profit as its only objective function. Exact solution methods are mostly provided. However, the vast majority of reviewed studies were illustrated in either small- or medium-size cases. It should be outlined that when solving real-life large-scale problems, this solution approach is significantly limited. It is found that the Journal of Cleaner Production, Resources, Conservation and Recycling, and Waste Management represent primary publication outlets for the investigated research area.

According to the performed review, the following gaps and potential research directions for their improvements are noticed:

  • Social acceptance and social awareness are important problems to deal with for effective ELV management. There are not enough studies that include social criteria.

  • Researches of environmental consequences of introducing or extending the ELV logistics network are missing.

  • Material waste reductions, recyclability of materials and innovative forming processes able to recycle materials have to be considered in more detail.

  • The research on more profitable and ecologically efficient treatment options represents an interesting avenue for further research.

  • Little has been done to document present industry practices in case studies or surveys.

  • Uncertainty is the key factor influencing the ELV management. However, uncertainty analysis is mainly ignored in the available studies. Uncertainty analysis methods incorporated into future modeling frameworks could help to avoid erroneous strategic decisions.

  • Resource scarcity and volatile quantities of ELVs introduce risk in management systems. The available models can hardly provide network designs appealing to risk-averse waste managers. In fact, they can generate less reliable and inferior solutions. Thus, risk measurement methods integration into future optimization frameworks is one of the possible improvements.

This review can provide a source of references, valuable insights, and opportunities for researchers interested in the ELV management and inspire their additional attention.

Notes

Acknowledgements

The authors are grateful for the valuable comments of the Editor-in-Chief and the three anonymous reviewers, which help to improve the manuscript greatly.

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© The Author(s) 2019

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors and Affiliations

  1. 1.School of Computer ScienceUniversity of NottinghamNottinghamUK
  2. 2.Department of Industrial EngineeringYildiz Technical UniversityIstanbulTurkey
  3. 3.Faculty of Transport and Traffic EngineeringUniversity of BelgradeBelgradeSerbia

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