Development of waste coconut oil refining machine/ Kristian B. Lescano, John Lucky S. Palafox, Kayce Ann E. Reyes, Concepcion Ian S. Sibayan, and John Daniel R. Solibaga .--
Material type:
TextPublication details: Manila: Technological University of the Philippines, 2019.Description: x, 98pages: 29cmContent type: - BTH TK 146 L47 2019
| Item type | Current library | Shelving location | Call number | Copy number | Status | Date due | Barcode |
|---|---|---|---|---|---|---|---|
Bachelor's Thesis CIT
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TUP Manila Library | Thesis Section-2nd floor | BTH TK 146 L47 2019 (Browse shelf(Opens below)) | c.1 | Not for loan | BTH0005641 |
Bachelor's thesis
College of Industrial Technology .-- Bachelor of Technology major in Electrical Engineering Technology: Technological University of the Philippines, 2019
Includes bibliographic references and index.
Quezon province is the largest producer of coconut products in the Philippines. However,
waste water coming from coconut factories is harmful for the environment. Instead of
letting the waste coconut water contaminate the rivers of Quezon, the locals think of a
solution on how to treat the wastewater by processing it as a refined coconut oil. The study
aims to develop a Waste Coconut Oil Refining Machine that will minimize the losses along
the production and that will attain a higher quality of the product. It has a platform that
rotates at 180 degrees. An Arduino microcontroller unit is used to control both the mixing
and pressing process of the machine. It has 25 pitch angle impeller revolving at 500rpm for
the mixing and boiling process. The project was tested in terms of time production test,
capacity test and quality test. The time production test shows that the machine can process
a 4L of oil within 30mins. It has a capacity of 10L yielding an output of 4L. The quality of
the oil was tested by the DOST and obtained a higher viscosity index having a 0.3%
difference and decreased the water and sediment content by up to 0.17%. It is Evaluated
by 30 respondents and obtained an average mean of 4.79 with a descriptive rating of
“Excellent”. However, the study is limited for research purposes only but it can be enlarged
to fit the mass production.
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