Christoph Helbig
University of Augsburg
Fourth year PhD student at the University of Augsburg, Germany. MSc in Physics. Works in the interdisciplinary research group 'Resource Lab' of the University of Augsburg. Research areas are material flow analysis, life cycle systainability assessment, raw material criticality assessment and dissipative losses, mostly on metals and minerals. Member of the Student Board of Representatives of the ISIE.
Raw material criticality assessment includes a broad research field, which developed immensely over the last decade, as presented in several review articles. Focus areas are mainly supply risk and vulnerability to supply... [ view full abstract ]
Raw material criticality assessment includes a broad research field, which developed immensely over the last decade, as presented in several review articles. Focus areas are mainly supply risk and vulnerability to supply restrictions, sometimes extended by environmental and rarely by social considerations. However, considering social aspects as an essential part of raw material criticality assessments could be of high benefit, especially when the assessment is intended for decision support in the industry. As companies can directly implement social aspects when purchasing raw materials or selecting raw materials for designing new products, inclusion of social raw material assessments could improve the social performance sustainably. With regard to the commonly called Dodd-Frank Act and the future European pendant, increasing socially oriented political regulations for the usage of raw materials can be expected. As many companies rely on numerous raw materials and maybe miss expertise in raw material assessments, especially regarding social aspects, helping them with an extensive and comprehensive decision support system (DSS) would be advantageous and essential.
Therefore, we develop an individual and quantitative social assessment dimension, based on both an extensive literature review and the methodology of raw material criticality assessment, and prototypically implement it into a decision support system. As impact, knowledge, application and understanding of social life cycle assessment (SLCA) has grown immensely within the last several years, results from the research field of SLCA are adapted for the social assessment dimension. As frequently highlighted in literature, all participants along a product’s supply chain have to be considered to fully assess its social lifecycle, which is hardly feasible for companies. In reference to criticality assessments and parts of the SLCA literature we therefore carry out a raw material production hotspot analysis as a first insight. A combination of both top-down and bottom-up approach is carried out to construct the assessment dimension and identify relevant impact indicators, followed by an analytic hierarchy process (AHP) analysis for indicator weighting determination.
We then apply our assessment model, which consists of three criteria containing 18 indicators in total, on 35 different raw materials and for the years from 1994 till 2015. Here, different behavior in social criticality development among the focused raw materials can be identified, as increase, stagnation and decrease is observable. Sensitivity analysis identifies the significance of individual indicator weighting, for instance that the AHP-determined indicator weighting results in a higher spread between socially most and least critical raw materials, compared to equal weighting. Additionally, the relevance of some included indicators is discussable from both a mathematical and an ethical point of view, as the impact of these indicators on the final criticality score is rather low. With a case study we tested the prototypical implementation of the social criticality assessment into a DSS.
Considering social aspects in raw material production is of high importance and has to be transferred to industry and into DSSs, independently of the methodology used. In this connection the work we present could be of great benefit.
• Advances in methods (e.g., life cycle assessment, social impact assessment, resilience a , • Decision support methods and tools