University of Twente Student Theses


Sustainability in electromobility purchasing : prioritising raw materials using multi-criteria decision-making

Lansink, T.T.M. (2022) Sustainability in electromobility purchasing : prioritising raw materials using multi-criteria decision-making.

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Abstract:This research is conducted at OEM X in its electromobility purchasing department. This department focuses on purchasing the necessities for developing and delivering OEM X’s electric vehicles. This department aims to increase sustainability in three aspects. The strategy focuses on resources, climate and people and is based on the UN Sustainable Development Goals (SDGs). For instance, the goal is to have decarbonised value delivery in 2040. However, concrete plans for raw materials are not on the current sustainability agenda for two segments within the electromobility purchasing department. There is no overview of what raw materials are used precisely, and it is unknown how the developments in the raw material industry influence the usage of raw materials. Therefore, we map the critical raw materials and relevant developments in the Battery Electric Vehicle (BEV) supply chain, focusing on the motor drive system and electrical distribution and charging segments. Recommendations in the form of an action plan are presented on which raw materials OEM X and its supply chain partners should prioritise. Three sections follow this introduction. First, the highlights of the methodology are presented. Second, the results are discussed, and finally, conclusions and recommendations are formulated. Method: Multiple circular concepts could be applied to a supply chain, as presented by the R-framework (Potting et al., 2017) or Lansink’s Ladder (Kemp & van Lente, 2011). Prevention and product reuse are circular concepts preferred over recycling. On the other hand, raw materials are currently in use, and products cannot be reused indefinitely. Thus, this thesis focuses on recycling as the primary circular concept. Furthermore, there are many reasons to prioritise certain raw materials for recycling over others. These reasons include the maturity of the recycling processes, the geopolitical implications and human rights issues related to the raw materials, environmental concerns or economic dependencies. Moreover, these drivers could be conflicting. Therefore, a multi-criteria decision-making analysis is chosen to execute the prioritisation. The problem consists of nineteen raw materials that are evaluated on twenty-six criteria. Moreover, the perspectives of five different stakeholders are considered. Most of the raw materials are critical in transitioning to a global economy with net-zero emissions and are also used in many booming industries, like the renewable energy industry. The twenty-six criteria are formed following a combination of the criteria already used at OEM X and by executing a literature review following the three Ps: People, Planet, and Profit. The DEMATEL + ANP and PROMETHEE II method has been selected to perform the prioritisation. The pairwise comparison-based method ANP is selected to determine the relative priorities of each criterion since it does not assume independent criteria by modelling the dependencies between criteria. DEMATEL is selected to reduce the number of pairwise comparisons of ANP. Finally, PROMETHEE II is selected since it adheres to the concept of strong sustainability, which means that extremely strong performances in one criterion cannot offset bad performances on other criteria. Moreover, PROMETHEE II can cope with data uncertainty to a certain extent. The use of this hybrid model is validated by comparing the results of this hybrid to less complex and more naïve methods. Generally speaking, multi-criteria decision-making methods are deterministic. However, the electromobility sector is developing rapidly. Therefore, uncertainty about the direction of performances on one of the twenty-six criteria should be considered. These developments are modelled using a novel hybrid of scenario analysis and Monte Carlo simulations. This method allows for the creation of scenarios to substantiate development directions of performances and to translate this direction into probability distributions used as input for Monte Carlo simulation. Furthermore, judgmental uncertainty is another type of uncertainty relevant for multi-criteria decision-making. Therefore, a sensitivity-based Monte Carlo Simulation is executed to analyse the sensitivity of the place of the raw materials in the ranking relative to changes in the priorities.
Item Type:Essay (Master)
Faculty:BMS: Behavioural, Management and Social Sciences
Subject:85 business administration, organizational science
Programme:Industrial Engineering and Management MSc (60029)
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