Optimization of CFD Simulation of Mixer Machine for Liquid Soap Machine with Capacity of 160 Liters
- DOI
- 10.2991/978-94-6463-386-3_19How to use a DOI?
- Keywords
- CFD; Optimization; Soap; Simulation
- Abstract
Liquid soap plays a very important role in people’s lives, but if the manufacturing process is not done well it will have fatal consequences, such as in the process of making liquid soap in SMEs (Small and Medium Enterprises) many still do it manually or semi-automatically, the target users are small businesses. middle school so that it can develop further. The combination of stirrers in liquid soap machines is an option to increase the capability of the manufacturing process. In this study, CFD analysis compared 3 types of stirrer shapes using Solidworks with a fluid speed of 5 m/s. The simulation results show that in the speed distribution, the highest average occurs in stirrer 2, namely 5,185 m/s. Meanwhile, stirrer 1 gave the highest difference in average pressure distribution, namely 112411.60 Pa. After the CFD simulation was carried out, Topology Optimization was carried out on the stirrer shape using data obtained from the CFD simulation.
- Copyright
- © 2024 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
TY - CONF AU - Fatahul Arifin AU - Yusuf Dewantoro Herlambang AU - Irawan Malik AU - Yahya AU - Eka Satria Martomi AU - Habib Sultan AU - M. Amir Alfayyid PY - 2024 DA - 2024/02/27 TI - Optimization of CFD Simulation of Mixer Machine for Liquid Soap Machine with Capacity of 160 Liters BT - Proceedings of the 7th FIRST 2023 International Conference on Global Innovations (FIRST-ESCSI 2023) PB - Atlantis Press SP - 169 EP - 176 SN - 2352-5401 UR - https://doi.org/10.2991/978-94-6463-386-3_19 DO - 10.2991/978-94-6463-386-3_19 ID - Arifin2024 ER -