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Construction of evolving models for the environmental evaluation of innovative sub-systems based on a hierarchical agglomerative clustering
Abstract:This paper deals with simplifying the environmental evaluation of an innovative sub-system related to the future complex system that will include it, by using evolving generic models built on a limited number of characteristics. For a complex system range, the evolving approach of the environmental modelling aims to generate a learning dynamics, to avoid the paralysing complexity induced in design by the valuation of many components according to many impact categories. Applied to the automotive sector, dendrograms are made with results of life cycle assessments (LCA) of 17 vehicles for 4 environmental indicators and on 3 life cycle steps. In an iterative process, a limit condition threshold on the resulting relative errors aims to cluster the vehicles. First, several calculation methods of dendrograms are tested. Second, the influence of the limit condition on the models is observed. Lastly, by simulating the vehicle population increase, the modelling capacity to evolve is tested. Five vehicle characteristics are sufficient to identify a model to be equivalent to the future vehicle. While the number of clusters is increased to simplify their identification with the system characteristics, the relative error variability increases too. The generic models are stable when adding LCA's results.
Keywords:life cycle assessment  innovation  complex system  hierarchical agglomerative clustering  evolving models  automotive  continuous improvement system
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