Proceedings of the 4th International Conference on Informatics, Technology and Engineering 2023 (InCITE 2023)

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The Application of the Box-Jenkins (BJ) Method for Process Identification of the Batch Milk Cooling System

Authors
Rudy Agustriyanto1, *, P. Setyopratomo1, E. Srihari Mochni1
1Chemical Engineering Department, University of Surabaya, Surabaya, 60293, Indonesia
*Corresponding author. Email: rudy.agustriyanto@staff.ubaya.ac.id
Corresponding Author
Rudy Agustriyanto
Available Online 19 November 2023.
DOI
10.2991/978-94-6463-288-0_6How to use a DOI?
Keywords
Box-Jenkins; Simulation; Dynamic Study; Milk Cooling
Abstract

The Box-Jenkins (BJ) method is a well-known system identification method that has been applied in several fields. Engineers use the Box-Jenkins method for quality control and process optimization in manufacturing. It can identify patterns and trends in production data, leading to improvements in product quality and efficiency. This study presents the application of the BJ method for the identification of a batch milk cooling process. The primary goal of this research is to create a model for the batch milk cooling process, intending to ease the control and enhance the optimization of milk cooling procedures. The data used in this study was collected from a batch milk cooling process over a period of time generated from Simulink. The BJ method was applied to the data to obtain the process transfer function. The model was then used to simulate the batch milk cooling process and tested for different perturbations. The findings indicated that the BJ method effectively represented the batch milk cooling process with high accuracy. The final result obtained from the BJ method is:  0.02361 s + 0.02361  which corresponds to  1 42.3549 s + 1 .

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 4th International Conference on Informatics, Technology and Engineering 2023 (InCITE 2023)
Series
Atlantis Highlights in Engineering
Publication Date
19 November 2023
ISBN
10.2991/978-94-6463-288-0_6
ISSN
2589-4943
DOI
10.2991/978-94-6463-288-0_6How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Rudy Agustriyanto
AU  - P. Setyopratomo
AU  - E. Srihari Mochni
PY  - 2023
DA  - 2023/11/19
TI  - The Application of the Box-Jenkins (BJ) Method for Process Identification of the Batch Milk Cooling System
BT  - Proceedings of the 4th International Conference on Informatics, Technology and Engineering 2023 (InCITE 2023)
PB  - Atlantis Press
SP  - 52
EP  - 61
SN  - 2589-4943
UR  - https://doi.org/10.2991/978-94-6463-288-0_6
DO  - 10.2991/978-94-6463-288-0_6
ID  - Agustriyanto2023
ER  -