Multi-Objective Optimization of the Stamping of Titanium Bipolar Plates for Fuel Cell
محورهای موضوعی : metal formingVahid Modanloo 1 , Vali Alimirzaloo 2 , Majid Elyasi 3
1 - Department of Mechanical Engineering,
Urmia University, Iran
2 - Department of Mechanical Engineering,
Urmia University, Iran
3 - Department of Mechanical Engineering,
Babol Noshirvani University of Technology, Iran
کلید واژه: Ranking, TOPSIS, VIKOR, Weighting, Titanium Bipolar Plates,
چکیده مقاله :
High demands of quality development in the industry especially automotive, necessitates multi-objective optimization of the manufacturing processes. Fuel cells are one of the most important sources of renewable energies that Bipolar Plates (BPPs) are their main components. Metallic BPPs are known as a suitable replacement of the graphite plates due to their lower weight and cost. Accordingly, this study employs Multi-Criteria Decision Making (MCDM) methods to determine the best forming condition in the stamping of titanium BPP. In the first step, the process is analyzed using the Finite Element (FE) simulation. Afterward, validation of the FE model is confirmed by performing the experiments using titanium ultra-thin sheet with a thickness of 0.1 mm. Subsequently, a set of tests with 15 experiments are assumed to be as alternatives. In addition, filling ratio, thinning ratio and forming load are considered as different criteria. In order to select the optimum condition considering three mentioned responses simultaneously, TOPSIS and VIKOR methods are applied. In addition, a weighting procedure combining AHP and Entropy approaches is used. Based on the weighting results, the highest and lowest weights were obtained for filling ratio (0.5398) and forming load (0.1632), respectively. Likewise, a Spearman’s rank equal to 0.9357 was obtained that demonstrates high compatibility between TOPSIS and VIKOR methods. Overall, the best (optimum) forming condition has obtained an experiment with a clearance of 0.2 mm, the speed of 3.5 mm/s, and friction coefficient as 0.2.
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