The current study aimed to study some engineering factors affecting the performance of a new automatic sugarcane seed cutting machine based on an RGB color sensor and internet of things technology assisted by sugarcane seed monitoring and a counter-remote system. In the current study, we evaluated the performance of the developed machine using two saw knives with different tooth numbers (80 teeth and 30 teeth), five different cutting times (t1 = 1000 ms, t2 =1500 ms, t3 =2000 ms, t4 =2500 ms, and t5 =3000 ms), and four different sugarcane stalk diameters (d1 = 2.03 cm, d2 = 2.72 cm, d3 = 3.42 cm, and d4 = 3.94 cm). The obtained results showed that the invisible losses and cutting efficiency decreased with the decrease in the diameter of the sugarcane stalks, the increase in the cutting time, and the increase in the number of teeth of the rotary saw knife. While machine productivity took the opposite trend. Where it decreased with increasing cutting time and increasing the diameter of the sugarcane stalks, while the number of teeth of the rotary saw knife had no significant difference.
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Elwakeel et al. (2024) studied this question.
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