Abstract
Criticality assessments of raw materials are inherently based on multiple criteria, which justifies the use of multi-criteria decision analysis (MCDA) to aid the interpretation of the data by providing a comprehensive evaluation. A structured and transparent selection procedure is firstly introduced in this paper to choose eight supply risk assessment criteria to evaluate the security of supply for thirty-one raw materials used in automotive manufacturing. A synergic combination of MCDA methods is then proposed for the classification of raw materials in risk classes according to the supply risk criteria. Risk classes are recommended following from a robustness analysis based on stochastic and optimisation MCDA methods where risk levels assigned to the raw materials are firstly visualised on a relative frequency basis. The sorting of the raw materials is also refined by narrowing down the best and worst plausible classes when justifiable constraints on criteria weights are accounted for in the modeling. For example, the robustness analysis suggests that rare earth elements and tellurium have a high eventuality of supply chain disruption, closely followed by indium, germanium and boron. Conversely, the results suggest that the risk of supply disruption for iron, copper, zinc and aluminium is mostly medium-low or low. The proposed step-wise decision support approach can be used as a complementary tool to the existing life cycle assessment methods for a more comprehensive assessment of the short-term availability of natural resources.
Highlights
Thirty-one metals and metalloids used in automotive manufacturing were assessed against the supply risk matrix, with each mineral assigned a risk category according to its performance on each supply risk criterion
The European Commission (EC) criticality assessment (EC, 2014) relates to materials that are relevant to the European industry, while this study focuses on metals and metalloids used in automotive manufacturing
The novel approach proposed in this article to assess the supply risk of raw materials is structured upon a conjoint use of multicriteria decision analysis (MCDA) classification methods; in this case, SMAA-TRI and IRIS
Summary
An uninterrupted supply of raw materials, free from disturbances and bottlenecks that may lead to volatility in commodity pricing and markets, is a requirement for sustainable economic development. Erdmann and Graedel (2011) Sectors that rely heavily on raw materials (e.g. construction, manufacturing, and transport) are extremely vulnerable to any physical shortage or increasing prices of these materials. Schneider et al (2014) As such, the need for a systematic quantification and assessment of the risks and impacts related to the increasing depletion of natural resources is currently more important than ever (Rørbech et al, 2014).The methods applied to assessment of the potential consequences associated with resource use frequently come from life cycle assessment (LCA) literature (Rørbech et al, 2014; Klinglmair et al, 2014). Existing LCA models focus exclusively on the mid- to long-term geologic and economic finiteness of resources They ignore other technological, geopolitical, regulatory and social risk factors (e.g. wars, market imbalances, governmental interventions or restrictions to mining due to environmental degradation) that may lead to supply disruptions and increasing commodity prices in the short term (Erdmann and Graedel, 2011; Schneider et al, 2014; Drielsma et al, 2016). Consideration of these additional risk factors in the evaluation of resource depletion impacts has recently emerged as a new research field
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