Hello Tesla

Thank you for taking the time to look at my application! I truly believe I have the perfect skill set to be an amazing Actuator Mechanical Design Engineering Intern before starting graduate school this Fall and I want to prove it to you on this webpage. I know you may have limited time so I will keep this brief with a bulleted list of why I would be a perfect fit:

  1. I know how to build brushless DC motors from scratch!

    I am working on a personal project where a friend and I are 3D printing a BLDC motor with a partially complete stator to make our motor uniquely lightweight, yet functional. I have surveyed what is available and know what materials are best for the rotor and the stator. I’ve read textbooks covering the governing differential equations of BLDC motors, which I’ve used to model torque simulations with pyFEMM and find optimal stator-rotor combinations. I also understand intuitively the core components of motor design such as back irons, Halbach arrays, winding factor, slot-pole ratios, and more!

  2. I can automate hardware tests and collect/analyze vast amounts of data

    When I worked at Amazon Robotics, I ran automated conveyor tests to find what parameters would lead to the fastest tote delivery time, within a consistent range of stopping positions. I coordinated with vendors, wrote PLC programs, and calibrated my test setup to measure tote positions accurately for days on end. I wrote Python scripts to parse through the position data, find the most relevant points, and report the effective stopping positions. I then applied linear regression and ANOVA statistical analyses to identify the significant differences between parameter sets and concisely reported my findings to the company. Because of my work, conveyors are optimized for tote delivery and people use my findings and automated test setup to assess more conveyor parameters and further enhance company productivity.

  3. I have used FEA and ANSYS simulations to justify system-wide decisions

    When working at Desktop Metal, I used FEA to justify the strength of my aluminum retrofit parts to bring system-wide functionality back to the company’s production line of metal 3D printers. I also used the same approach when justifying the strength of my arm clamp assemblies for a lightweight indoor research drone I built from scratch for Northeastern’s drone research club (NUAV). Additionally, I used ANSYS fluent to find optimal nosecone shapes for our senior capstone project - an autonomous invasive-plant-detecting catamaran. I’ve also used MATLAB to simulate differential/partial differential equations using RK2, implicit/explicit, and Crank-Nicholson methods, as part of my Intro to Computational Fluid Dynamics class.

Projects Mentioned

In short, I am an up-and-coming M.S. in Robotics student who loves building automated test setups, collecting data, and finding the most optimal electromechanical designs. I have excellent CAD skills, having worked with SolidWorks for the past 7 years. I know how to design small parts for manufacturability, assembly, and function, all while specifying part dimensions and tolerances with GD&T. Additionally, I have completed motor tests, developed strong test flows, automated data collection, processing, & analysis with Python, used FEA models to simulate motors, and have written clear and concise reports that people easily understand and use to enhance company-wide productivity. That’s not to mention my time leading Northeastern University’s drone research club, working across multi-disciplinary teams, and understanding/implementing system-wide goals.

I check off all the boxes, and if you were to accept me as an intern, you will have an engineer with a relentless drive to uncover the most optimal actuator designs that will make TeslaBot harder, better, faster, stronger.

I look forward to hearing back soon and talking to you about my projects.

Kindest Regards,

Daniel T. Simpson