Can you describe a time when you had to analyze complex data to make recommendations for design changes?

In my previous role as a Mechanical Engineering intern, I had the opportunity to work on a project where I had to analyze complex data to make recommendations for design changes. We were designing a new component for a vehicle system, and I was responsible for conducting acoustic simulations to predict the component's behavior in terms of noise and vibration. I used software tools like ANSYS and MATLAB to analyze the data and generate detailed reports. Based on my analysis, I recommended design modifications to improve the component's NVH characteristics. This experience taught me the importance of attention to detail and the ability to interpret complex data to make informed design decisions.

During my internship as a Mechanical Engineering intern, I was part of a team working on developing a new exhaust system for a vehicle. As part of my responsibilities, I had to analyze complex data to make recommendations for design changes. We used acoustic simulation software like LMS Virtual.Lab and MATLAB to create computational models of the exhaust system and predict its acoustic behavior. I conducted extensive simulations under various operating conditions to understand the noise and vibration characteristics of the system. By analyzing the simulation results, I identified areas where design modifications were needed to meet the NVH objectives. I worked closely with the design and engineering teams to implement these changes, resulting in a significant reduction in the overall noise levels of the exhaust system. This experience enhanced my proficiency in acoustic simulation and computational analysis and strengthened my ability to make informed recommendations for design changes based on complex data analysis.

During my internship at a leading automotive company, I was assigned to a project focused on optimizing the cabin noise levels of a new electric vehicle. The project involved analyzing complex data to make recommendations for design changes. To accomplish this, I utilized advanced acoustic simulation software, such as COMSOL and ANSYS, to create high-fidelity computational models of the vehicle's interior and simulate its acoustic behavior. I worked closely with the design and engineering teams to collect data from various sources, such as microphone arrays and accelerometers, to capture the vehicle's noise characteristics under different driving conditions. This data was then processed and analyzed using signal processing techniques and statistical analysis tools. By correlating the data with subjective evaluations from test drivers, I was able to identify specific areas in the vehicle's interior that needed design modifications. I proposed changes to the interior materials, insulation, and damping treatments to improve the overall cabin noise levels. These recommendations were implemented and resulted in a significant reduction in noise, providing a more comfortable and enjoyable driving experience for the customers. This project not only enhanced my skills in acoustic simulation and data analysis but also allowed me to develop strong collaboration and communication abilities by working closely with cross-functional teams.