Development of a material selection decision support system for an automotive application

This study presents the development of a material selection decision support system for an automotive rooftop tent. The system uses five parameters of material cost, formability, corrosion resistance, tensile strength and hardness to optimize material choice from a list of aluminium alloy options. This was done before production via the deep drawing process can commence. The parameters were quantified using the average market prices for each alloy, product requirements obtained from the case study and the performance data that was obtained from the uniaxial tensile and hardness tests. These inputs were combined with the developed material selection framework and then programmed into a web-based decision support system for automated, data-driven material selection. The output presents the recommendation for the optimum material that balances cost-effectiveness and performance. The decision support system was successfully used to select the optimum alloy for the rooftop tent. Results show that AA1050 is the optimum material, providing weight reduction at the minimum achievable cost without compromising the product requirements for the rooftop tent. The decision support system is also scalable, and this allows it to be used with larger datasets for different products and processes in the future.