Optimization of an algae ball mill grinder using artificial neural network

Arvin H. Fernando; Archie B. Maglaya; Aristotle Tulagan Ubando

doi:10.1109/TENCON.2016.7848762

Optimization of an algae ball mill grinder using artificial neural network

Arvin H. Fernando, Archie B. Maglaya, Aristotle Tulagan Ubando

Department of Aeronautics and Astronautics

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

5 Citations (Scopus)

Abstract

Effects of the various ball mill operational grinding parameters for extracting microalgae were evaluated. This paper presents the use of MATLAB artificial neural network (ANN) for optimizing and improving the micro algae ball mill grinding process configuration set-up particularly on Nannochloropsis sp. The input parameters that was gathered, used and analyse are critical speed, duration, ball material, ball diameter, jar diameter, load percentage and ball-algae ratio. The researcher determines the amount of protein in the sample by using the Bradford Protein Assay Analysis. A total of 42 datasets was used to predict the optimize combination of the dataset. The authors used the MATLAB Programming and trained the neural network. MATLAB is used as an optimization tool to determine the best ball mill grinding configuration for the prototype set-up.

Original language	English
Title of host publication	Proceedings of the 2016 IEEE Region 10 Conference, TENCON 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	3752-3756
Number of pages	5
ISBN (Electronic)	9781509025961
DOIs	https://doi.org/10.1109/TENCON.2016.7848762
Publication status	Published - 2017 Feb 8
Event	2016 IEEE Region 10 Conference, TENCON 2016 - Singapore, Singapore Duration: 2016 Nov 22 → 2016 Nov 25

Publication series

Name	IEEE Region 10 Annual International Conference, Proceedings/TENCON
ISSN (Print)	2159-3442
ISSN (Electronic)	2159-3450

Other

Other	2016 IEEE Region 10 Conference, TENCON 2016
Country/Territory	Singapore
City	Singapore
Period	16-11-22 → 16-11-25

All Science Journal Classification (ASJC) codes

Computer Science Applications
Electrical and Electronic Engineering

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10.1109/TENCON.2016.7848762

Cite this

Fernando, A. H., Maglaya, A. B., & Ubando, A. T. (2017). Optimization of an algae ball mill grinder using artificial neural network. In Proceedings of the 2016 IEEE Region 10 Conference, TENCON 2016 (pp. 3752-3756). Article 7848762 (IEEE Region 10 Annual International Conference, Proceedings/TENCON). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/TENCON.2016.7848762

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title = "Optimization of an algae ball mill grinder using artificial neural network",

abstract = "Effects of the various ball mill operational grinding parameters for extracting microalgae were evaluated. This paper presents the use of MATLAB artificial neural network (ANN) for optimizing and improving the micro algae ball mill grinding process configuration set-up particularly on Nannochloropsis sp. The input parameters that was gathered, used and analyse are critical speed, duration, ball material, ball diameter, jar diameter, load percentage and ball-algae ratio. The researcher determines the amount of protein in the sample by using the Bradford Protein Assay Analysis. A total of 42 datasets was used to predict the optimize combination of the dataset. The authors used the MATLAB Programming and trained the neural network. MATLAB is used as an optimization tool to determine the best ball mill grinding configuration for the prototype set-up.",

author = "Fernando, {Arvin H.} and Maglaya, {Archie B.} and Ubando, {Aristotle Tulagan}",

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language = "English",

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note = "2016 IEEE Region 10 Conference, TENCON 2016 ; Conference date: 22-11-2016 Through 25-11-2016",

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Fernando, AH, Maglaya, AB & Ubando, AT 2017, Optimization of an algae ball mill grinder using artificial neural network. in Proceedings of the 2016 IEEE Region 10 Conference, TENCON 2016., 7848762, IEEE Region 10 Annual International Conference, Proceedings/TENCON, Institute of Electrical and Electronics Engineers Inc., pp. 3752-3756, 2016 IEEE Region 10 Conference, TENCON 2016, Singapore, Singapore, 16-11-22. https://doi.org/10.1109/TENCON.2016.7848762

Optimization of an algae ball mill grinder using artificial neural network. / Fernando, Arvin H.; Maglaya, Archie B.; Ubando, Aristotle Tulagan.
Proceedings of the 2016 IEEE Region 10 Conference, TENCON 2016. Institute of Electrical and Electronics Engineers Inc., 2017. p. 3752-3756 7848762 (IEEE Region 10 Annual International Conference, Proceedings/TENCON).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Optimization of an algae ball mill grinder using artificial neural network

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