Look: Up in the Sky! Over the Field! It’s a Farm Drone!
The drone segment is among the fastest growing in the aerospace industry. Although initially focused on military applications, the segment is now rapidly expanding into the commercial realm. According to Statista, the sector’s 2015 value was already $127 billion and growing. In this increasingly competitive market, the company that comes up with the best drone designs wins, and the battle is on for performance (endurance, payload, cameras/sensors/antennas) and safety (reliability, robustness, bug-free control code). Because drone producers need to keep development costs as low as possible, while innovating faster in an arena full of inexperienced players, it shouldn’t be a surprise that simulation is playing a major role. One important new application is pesticide spraying. In India, for example, the scarcity of water, the slow speed of manual spraying and the risks from pesticide exposure to farmers’ health are enormous challenges. Many innovative companies are using drones to come up with new methods of pesticide spraying that not only solve these problems, but also offer added advantages like selective farming. This technique saves water and pesticide quantities by precise spraying on a selected area. To foster innovation, Tata Sons Group Technology and Innovation Office organizes an annual student design and engineering contest, the Tata Pioneer’s Makerthon. For the 2017 unmanned aerial vehicle (UAV challenge), I was given an opportunity to be on the prototype judging panel. The objective of the competition was to build an autonomous drone capable of lifting a payload of 10 kg or more. The drone had to have a vertical and horizontal terrain-following accuracy of 10 cm and 0.5 m, respectively. For a team to win, it had to satisfy these requirements and do so at the lowest cost. The winning design would then be used in precision agriculture. One of the most exciting parts of the competition was the sheer enthusiasm shown by the students in their efforts to fly the drones. The teams used many types of simulation to create their prototypes. In the ideation phase, the students came up with their initial concepts, and selected the batteries, motors, propellers and to accommodate the required lifting capacity. This phase is especially important because the design decisions made will determine the overall cost. In the subsequent design phase, the teams used static structural analysis to optimize the drones’ frame. They also made use of dynamic analysis to ensure that the vibrations were within the specified range. The teams used systems simulation for tuning the proportional-integral-derivative (PID) controller. One of the teams proposed using an additive manufacturing technique to manufacture the frame. Others used topology optimization simulation to reduce material resources, which not only lowers the overall cost, but also increases the payload carrying capacity. All learned firsthand how simulation can significantly reduce the time to market throughout the product lifecycle — from ideation to manufacturing. If you are curious to see how simulation tames the complexity of drone design, have a look at this video demonstration.