Integrated CO2e assessment and decision support model for supplier selections
Creators: name: Schiessl, Andreas
Publisher: name: Karlsruher Institut für Technologie (KIT)
Year: 2021
Subjects: LCA
CO2e
Carbon footprint
Iron-and steel industry
Aluminum industry
Product assessment
Credit system
Decision making
Supplier selection
Automotive industry

description: The fast growing stakeholder interest in sustainability leads to an increased attention both on the ecological and social perspective of industrial companies and its products. While in the past the focus predominantly laid on the environmental impact of the product use phase, it recently shifted towards the manufacturing phase. Hence, both, focal companies and supply chain members are obliged to create and apply new strategies to reduce greenhouse gas emissions (GHG). From a purchasing perspective, the selection of more environmentally efficient suppliers is a possibility to significantly reduce CO$_{2}$e emissions. Therefore, transparency is required in form of site-specific and comparable data on suppliers’ environmental performance. This data is lacking and the detailed environmental performance criteria has not been integrated in supplier selection decisions yet. In this dissertation a model is developed and applied to close the transparency gap and to integrate CO$_{2}$e as an additional supplier selection criteria in decision-making. For this purpose, a multi-criteria decision analysis approach is developed to derivate criteria weights and a supplier ranking based on expert opinion and quantitative supplier performance data. As decision making based on expert consultation is associated with a certain level of subjectivity, a sensitivity analysis is performed to evaluate the robustness of the model and the results. By means of ‘what-if’ scenario simulations, the dynamic behavior of the model is further investigated to examine how decisions may change when CO$_{2}$e is formulated and considered as a new criteria. In addition, a systematic and modular Life Cycle Assessment (LCA) based approach is developed to enable an efficient evaluation and comparability of the sustainability performance of raw material suppliers on a production site level, based on publically available data. The model combines a bottom-up calculation of technical process flows with top-down reported site-specific CO$_{2}$ emissions, and explicitly considers technical restrictions and trading of inter-mediate products. The developed site-specific performance model is applied in two case studies for primary steel production sites in Europe and primary aluminum sites in Germany. The results, which were validated with industry experts, differ by 58 % for the comparison between the most and least efficient production site for steel and by 9 % for the examined aluminum production sites and show an opportunity to reduce GHG emissions by selecting more environmentally efficient suppliers. The combined, integrated CO$_{2}$e assessment and decision support model is subsequently applied on an automotive case study for the selection of the most adequate supplier for a powertrain part from an environmental and economic efficiency perspective. The results show that in some cases the integration of the CO$_{2}$e performance can have a significant impact on the ranking of the most preferable supplier, despite an initially investigated low importance of the new CO$_{2}$e decision criteria.