In the constantly changing field of engineering and design, achieving solutions that are both resilient and optimized is crucial. This thesis introduces a robust design methodology (RDM) that integrates statistical concepts and Finite Element Analysis (FEA) to enhance the product reliability and durability. Altair Hyperstudy is used for design exploration, and it examines how changes in geometry and material properties influence the IKEA Wall-Mounting shelving unit. The objective is to efficiently parameterize geometric shapes, compare different Design of Experiments (DOE) methodologies, identify key input variables impacting outputs, and generate a response surface model based on training data. The parameterization of geometric shapes is achieved using the morphing tool in Altair Hypermesh, while the design exploration is conducted using Full factorial, Fractional factorial V, IV and III approaches with selected resolutions. A space-filling modified extensive lattice sequence design (MELS) is employed to examine the entire design space, providing input for the development of the response surface methodology (RSM). Finally, the RSM is developed for all design variables and the quality of fit is assessed. The methodology described is used to explore the design space and determine which parameters influence the system’s output response, ensuring these parameters are considered during the design phase.