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Statistical Decision in the Automotive Material Selection

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Abstract

The objective of the research is the ranking of materials applied to an example from the automotive industry (material candidates for the car body construction). The variety of properties/attributes imposes different evaluations for metrical/ordinal scales and the necessary statistical calculus. Heterogeneity of the characteristics imposes the separation of the attributes into mainly two classes: functional (mechanical, physical, etc.), usually with metric scale and technological and environmental attributes with frequently ordinal scale. The paper analyses a practical case of the material for the car body by Multi Criteria Decision Making (MCDM) procedures like primary ranking and preference index value applied to mechanical, technological and ecological, respective all attributes, etc. All these methods are principally based on the variance, viewed as a risk measure. The final comparison has as result the most valuable materials: Titanium sheet, Glass Reinforced Plastics (GRP) and Carbon Fiber Composite.

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Correspondence to Cristian Andreescu .

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Andreescu, C., Paris, A.S., Dragomirescu, C., Târcolea, C. (2016). Statistical Decision in the Automotive Material Selection. In: Andreescu, C., Clenci, A. (eds) Proceedings of the European Automotive Congress EAEC-ESFA 2015. Springer, Cham. https://doi.org/10.1007/978-3-319-27276-4_17

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  • DOI: https://doi.org/10.1007/978-3-319-27276-4_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27275-7

  • Online ISBN: 978-3-319-27276-4

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