Estimating the cost efficiency of the microalgae drying process using the conventional oven and the infrared technology

Growing demand for energy has called for the search of alternative sources of fuel, one of which is the biofuel harvested from dried microalgae. However, current drying technology for microalgae is inefficient because it requires large time and energy input, prompting students from the Mechanical En...

Full description

Saved in:
Bibliographic Details
Main Authors: Bea, Kara Colleen D., Chua, Wilbur Osmar T., Inofre, Paula Louise A., Ordoñez, Sophia Maria Antoinette P.
Format: text
Language:English
Published: Animo Repository 2014
Subjects:
Online Access:https://animorepository.dlsu.edu.ph/etd_bachelors/18683
https://animorepository.dlsu.edu.ph/context/etd_bachelors/article/19196/viewcontent/Ordona_et.al__1_.pdf
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: De La Salle University
Language: English
Description
Summary:Growing demand for energy has called for the search of alternative sources of fuel, one of which is the biofuel harvested from dried microalgae. However, current drying technology for microalgae is inefficient because it requires large time and energy input, prompting students from the Mechanical Engineering department of De La Salle University to look into different drying technologies. To support their analyses, we compared two available drying technologies the conventional oven and the infrared device to determine which technology is more cost efficient in terms of input and economies of scale. With data from each technology's experimental study, we estimated a translog cost function using seemingly unrelated regression. Results show that while the infrared technology is more cost efficient in terms of labor input, the conventional oven is more efficient in energy use and is more capable of economies of scale. Nevertheless, both technologies show potential in further minimizing cost. We recommend future researchers to improve data collection and gathering to include more variation in input levels for more comprehensive results.