Optimizing Lightweight Material Selection in Automotive Engineering: A Hybrid Methodology Incorporating Ashby’s Method and VIKOR Analysis

The automotive industry is responsible for about 20% of greenhouse gas emissions in Europe, and it is under notable pressure to meet the reduction targets set by the European Union for the next decades. In this context, lightweighting is a very effective design strategy for which materials selection plays a key role. One of the main challenges of lightweighting is selecting materials with enhanced structural properties but a reduced weight in comparison with traditional solutions. The spectrum of available materials is very large, and the choice needs to be carefully evaluated based on multiple factors, such as mechanical behavior, raw materials cost, the availability of manufacturing processes, and environmental impact. This article presents an innovative methodology for materials selection in the lightweight automotive field based on the Ashby approach for mechanical performance coefficients as an initial filtering criterion. Following this preliminary screening, this study adopts the VIKOR (Vise Kriterijumska Optimizacija I Kompromisno Resenje) MCDA (Multi-Criteria Decision Analysis) technique to rank feasible design solutions based on case study boundary conditions. The evaluation criterion of different design options encompasses crucial factors, such as mechanical properties, cost considerations, and environmental impact measures. The method is finally validated by the application of a redesign case study, a motor bracket of an electric commercial car.

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Publication Details

Journal
Machines
Published
2025-01-16
DOI
https://doi.org/10.3390/machines13010063
Citations
8
Primary Topic
Material Selection and Properties
Type
article
Field-Weighted Citation Impact
4.14
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article

Optimizing Lightweight Material Selection in Automotive Engineering: A Hybrid Methodology Incorporating Ashby’s Method and VIKOR Analysis

Gabriele Arcidiacono, Paolo Citti, Francesco Del Pero, Edoardo Risaliti
8 citations
Machines
Material Selection and Properties
4.14
article

Optimizing Lightweight Material Selection in Automotive Engineering: A Hybrid Methodology Incorporating Ashby’s Method and VIKOR Analysis

Gabriele Arcidiacono, Paolo Citti, Francesco Del Pero, Edoardo Risaliti
article en
8 citations

Abstract

The automotive industry is responsible for about 20% of greenhouse gas emissions in Europe, and it is under notable pressure to meet the reduction targets set by the European Union for the next decades. In this context, lightweighting is a very effective design strategy for which materials selection plays a key role. One of the main challenges of lightweighting is selecting materials with enhanced structural properties but a reduced weight in comparison with traditional solutions. The spectrum of available materials is very large, and the choice needs to be carefully evaluated based on multiple factors, such as mechanical behavior, raw materials cost, the availability of manufacturing processes, and environmental impact. This article presents an innovative methodology for materials selection in the lightweight automotive field based on the Ashby approach for mechanical performance coefficients as an initial filtering criterion. Following this preliminary screening, this study adopts the VIKOR (Vise Kriterijumska Optimizacija I Kompromisno Resenje) MCDA (Multi-Criteria Decision Analysis) technique to rank feasible design solutions based on case study boundary conditions. The evaluation criterion of different design options encompasses crucial factors, such as mechanical properties, cost considerations, and environmental impact measures. The method is finally validated by the application of a redesign case study, a motor bracket of an electric commercial car.

MachinesVol. 13(1)
Marconi University (IT)
Openalex Percentile: Top 6%
Material Selection and Properties
4.14
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Optimizing Lightweight Material Selection in Automotive Engineering: A Hybrid Methodology Incorporating Ashby’s Method and VIKOR Analysis — Gabriele Arcidiacono, Paolo Citti, et al. · Machines (2025) | TGRS Research Map | TGRS