An ability to design automotive systems with optimum parameters has become very crucial in the competitive industry. Today, there are many shape optimization algorithms to choose, depending on the nature of the design parameters. Compared with the topology optimization, a topography optimization can be a good alternative. Because of the less number of design variables required for the same optimization model, the topography optimization process is generally faster. In this study, an assembly consisting of several identical sheet metal components is employed for demonstrating the effectiveness of topography optimization, in which various beads are to be derived with appropriate heights and widths, where needed, at the discretion of the algorithm to attempt to render the design variables within the constraints. The identical pieces are arranged around an axis of revolution such that the geometric shape is cyclic symmetric at a constant angular spacing. Despite the geometric symmetry, however, the entire 360-degree assembly has to be modeled in the finite element analysis, to account for the overall lateral stiffness. Thus, during the course of optimization, it is necessary to impose a constraint known as pattern repetition for the evolved shapes of the design such that each component has the identical features for the purpose of simplicity and cost-effectiveness in manufacturing. The responses from the finite element solution in the form of lateral and rotational stiffness as well as maximum stresses are used as the design constraints and objective function. It turns out that the topography algorithm used in this study seems smart enough to figure out a set of design variables to meet some seemingly contradictory constraints.