Development of shredding and mixing machine for organic compost/
Bolima, Jaymark B.
Development of shredding and mixing machine for organic compost/ Jaymark B. Bolima, John Louise M. Espadilla, Dwight S. Onagan, Rennie A. Veras, and Vincent J. Young - 166pages: Illustrations 28cm. CD-ROM (4 3/4in.)
Thesis (undergraduate) --
College of Industrial Technology:
Includes bibliography
LGUs and barangays lack of tools, composting areas, and unwarranted amount of biodegradable waste produced by communities are such problems that they are facing for a very long time. The study, Development of Shredding and Mixing Machine for Organic Compost, aims to improve the methods of the existing composting machine and reduce the laborious work of making compost, which will help barangay staff and City Environment and Natural Resources (CENRO) officers to have additional tools to reduce waste within their jurisdiction. It has the features of mixing manually and automatically, shredding, and dispensing compost. The machine is equipped with Siemens LOGO! that acts as the brain of the machine, that controls the switches and motors. The machine is also equipped with two (2) 1 HP Electric Motors and a Gearbox that acts as the transmission system and gives the essential workload needed for mixing compost and shredding biodegradable waste. Test results revealed that the machine is able to mix up to three (3) kg worth of mixture and can dispense compost efficiently with the highest efficacy of 96.57%. The system was evaluated by 30 evaluators composed of Electrical Engineering and Mechanical Engineering Technology professors, professionals, farmers, CENRO officers, barangay staff, and agriculture and electrical engineering students using the TUP standard evaluation instrument. It was rated with an overall mean of 4.23 with a descriptive rating of "Very Good". This means that the machine is useful to the barangay and LGU in terms of reducing the time and laborious work of making compost. -- Author's abstract
Compost
Agriculture--data processing
Artificial intelligence --Agricultural applications
BTH S 494.5 / B65 2020
Development of shredding and mixing machine for organic compost/ Jaymark B. Bolima, John Louise M. Espadilla, Dwight S. Onagan, Rennie A. Veras, and Vincent J. Young - 166pages: Illustrations 28cm. CD-ROM (4 3/4in.)
Thesis (undergraduate) --
College of Industrial Technology:
Includes bibliography
LGUs and barangays lack of tools, composting areas, and unwarranted amount of biodegradable waste produced by communities are such problems that they are facing for a very long time. The study, Development of Shredding and Mixing Machine for Organic Compost, aims to improve the methods of the existing composting machine and reduce the laborious work of making compost, which will help barangay staff and City Environment and Natural Resources (CENRO) officers to have additional tools to reduce waste within their jurisdiction. It has the features of mixing manually and automatically, shredding, and dispensing compost. The machine is equipped with Siemens LOGO! that acts as the brain of the machine, that controls the switches and motors. The machine is also equipped with two (2) 1 HP Electric Motors and a Gearbox that acts as the transmission system and gives the essential workload needed for mixing compost and shredding biodegradable waste. Test results revealed that the machine is able to mix up to three (3) kg worth of mixture and can dispense compost efficiently with the highest efficacy of 96.57%. The system was evaluated by 30 evaluators composed of Electrical Engineering and Mechanical Engineering Technology professors, professionals, farmers, CENRO officers, barangay staff, and agriculture and electrical engineering students using the TUP standard evaluation instrument. It was rated with an overall mean of 4.23 with a descriptive rating of "Very Good". This means that the machine is useful to the barangay and LGU in terms of reducing the time and laborious work of making compost. -- Author's abstract
Compost
Agriculture--data processing
Artificial intelligence --Agricultural applications
BTH S 494.5 / B65 2020