Academic Awards 2025 booklet

31 Design and Analysis of a sensor-housing, lightblocking suction cup In 2022, an estimated 933 million metric tonnes of fruit were produced worldwide. Yet, 35-55% of fruits and vegetables are lost before it reaches the customer. A large part of this loss occurs during agricultural production. One way to reduce this waste, is by picking optimally mature food. In a collaborative project at TU/e’s Innovation Space, I investigated whether a low-cost, spectral sensor, sensitive to just six distinct wavelengths, could be used to estimate the ripeness of apples non-destructively. My personal thesis revolved around a quantitative analysis of the light blocking capabilities of nine different harvesting suction cups that I designed. We observed trade-off with its stiffness (determining the ease of suction), critical for both experimental consistency and real-world application. By fitting models on suction cups with a constant wall-thickness, I was able to predict the behaviour of more complex suction cups with variable wall-thickness through a slightly adapted application of the Beer-Lambert Law. In addition, I designed an innovative, 3D-printed insert for the suction cup which I placed into the mould and cast into silicone. This made sure that I could attach the other group’s sensor, while maintaining sufficient vacuum for adhering to the apples. Taken together, my results made it possible to combine the team member’s work and to provide a recommendation for the most-suitable suction cup for the application. Figure 1: Representation of how light would protrude a wall with non-constant wall-thickness. At the thicker parts, less light is transmitted (Beer-Lambert Law). Figure 2: Final General Design.