Design and fabrication of a semi-automated sorting machine for standard sizes and differentiate the ripe, unripe, overripe, and damaged tomatoes/ Carl C. Cuaresma, Jyle Ehronne S. Ladao, Ron Eleazar C. Masangcay, Juzzel Brylle G. Ogayon, and Jayco C. Omadto.--
Material type:
TextPublication details: Manila: Technological University of the Philippines, 2025.Description: x, 86pages: 29cmContent type: - BTH TJ 145 C83 2025
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Bachelor's Thesis COE
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TUP Manila Library | Thesis Section-2nd floor | BTH TJ 145 C83 2025 (Browse shelf(Opens below)) | c.1. | Not for loan | BTH0006382 |
Bachelor's thesis
College of Engineering.-- Bachelor of science in mechanical engineering: Technological University of the Philippines, 2025.
Includes bibliographic references and index.
This study addresses the challenges in traditional tomato sorting methods by developing a
semi-automated tomato sorting machine capable of classifying tomatoes based on their ripeness.
The project is focused on small to medium-scale farms specially in Plaridel, Lipa City, Batangas,
where farmers currently sort tomatoes manually by ripeness, size, and by identifying damaged or
overripe. The machine is designed to classify tomatoes into two main categories: Accepted (ripe
and unripe) and Rejected (overripe and damaged). It aims to process tomatoes within 1 hour, with
a sorting rate of approximately 100-120 kg per hour. The machine's performance is evaluated based
on safety, user-friendliness, tomato quality preservation, and classification accuracy. To achieve
these goals, the study involved interviews and surveys with local farmers, literature reviews,
calculations, simulations, and extensive experimentation. The final prototype includes essential
components such as a hopper (container), vision box, conveyor, and truncated cone. feeds tomatoes
individually to the conveyor, which operates at 10.02 rpm. The vision box, powered by computer
vision, detects and classifies tomatoes. Finally, the truncated cone, rotating at 20 rpm, effectively
sorts the tomatoes based on classification results. The results confirm that the semi-automated
tomato sorting machine meets the design objectives, maintaining classification accuracy while
preserving tomato quality throughout the 1-hour operation.
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