Topological Optimization of Brake Pedal for Metal Additive Manufacturing: A Case Study

ADMT Journal

دوره 14، شماره 2، شهریور 2021، صفحه 123-130   

نوع مقاله: Original Article

شناسه دیجیتال (DOI): 10.30495/admt.2021.1931105.1285

نویسندگان

Batuhan Izgi¹؛ Meltem Eryildiz^{* 2}؛ Mirigül Altan¹

¹Department of Mechanical Engineering, Yildiz Technical University, Istanbul, Turkey

²Department of Mechanical Engineering, Faculty of Engineering and Architecture, Beykent University, Istanbul, Turkey

چکیده

Additive Manufacturing (AM) has become popular for rapid prototyping and it is presently widely used in different branches of industry because of its advantages such as freedom of design, mass customization, waste minimization and the ability to manufacture complex shape. AM is the process of making 3D object from computer model data by depositing of material layer by layer. Topology optimization is iterative modifying the shape and optimizing material within a given designs space for load, boundary condition thus leading to weight reduction of components. Thus, to form lightweight components which have great advantage where energy consumption is minimal, topology optimization is used. Reducing weight and decreasing the material usage while keeping the product functions are the main challenges. Studies on the integration of the topology optimization and additive manufacturing, specifically mass reduction attract considerable attention. The topology optimization process is employed in this case study, to redesign a lightweight automotive brake pedal to show the potential of topology optimized design for additive manufacturing. As a result of this study 54.07% weight reduction was achieved in the total mass. The thermo- mechanical analysis for additive manufacturing showed that the part without topological optimization 108 MPa of stress and 1,099 mm of displacement were obtained and after optimization they were 196,1 MPa and 1,295 mm, respectively.

کلیدواژه‌ها

Additive Manufacturing؛ Analysis؛ Light Weight؛ Topological Optimization

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