Implementation of Particle Swarm Optimization (PSO) Method in Minimum Quantity Lubrication (MQL) Optimization to Obtain Optimal Machining in CNC Milling Machine

Yogi Muldani Hendrawan, Faza Husnan Anshori, Andri Pratama, Pandoe, Herman Budi Harja, Akil Priyamanggala Danadibrata

2022

Abstract

One of the machining processes used is the milling process with CNC milling machines equipped with cutting fluid to reduce the impact of the cutting process. One of the techniques of cutting fluid is to use MQL (Minimum Quantity Lubricant) as an application of ISO 140001 in reducing coolant waste in the environment which has the advantage of being more economical in reducing friction between the tool and the workpiece, thereby reducing the temperature rate in the cutting tool. The CNC tool machine of Politeknik Manufaktur Bandung is equipped with MQL (Minimum Quantity Lubricant) with Arduino control which has no parameters for optimum coolant discharge during the machining process. In this study, the Particle Swarm Optimization (PSO) method was used, which is one of the optimization methods for making decisions used in the manufacturing process by looking for a minimum value. There sulting from the milling process becomes a response in the process on CNC milling machines to obtain the characteristics of an effective discharged lubricant discharge. Some parameters such as cutting depth and feeding speed for aluminum and steel materials St37 were identified as experimental data for response. The data was searched for equations with regression, so in this study a polynomial regression model was chosen that could describe the data value better than linear regression. Polynomial equations are calculated with the Particle Swarm Optimization (PSO) algorithm to find the optimum flowrate. So that the minimum discharge obtained on aluminum material for a feeding depth of less than 0.85 mm is 25ml/h, and more than 0.85mm is 85ml/h. while for St.37 material the feeding depth of less than 0.35 mm is 25ml/h, and more than 0.35mm is 85ml/h.

Paper Citation

in Harvard Style

Hendrawan Y., Anshori F., Pratama A., Harja H., Pandoe. and Danadibrata A. (2022). Implementation of Particle Swarm Optimization (PSO) Method in Minimum Quantity Lubrication (MQL) Optimization to Obtain Optimal Machining in CNC Milling Machine. In Proceedings of the 5th International Conference on Applied Science and Technology on Engineering Science - Volume 1: iCAST-ES; ISBN 978-989-758-619-4, SciTePress, pages 821-827. DOI: 10.5220/0011891500003575

in Bibtex Style

@conference{icast-es22,
author={Yogi Muldani Hendrawan and Faza Husnan Anshori and Andri Pratama and Herman Budi Harja and Pandoe and Akil Priyamanggala Danadibrata},
title={Implementation of Particle Swarm Optimization (PSO) Method in Minimum Quantity Lubrication (MQL) Optimization to Obtain Optimal Machining in CNC Milling Machine},
booktitle={Proceedings of the 5th International Conference on Applied Science and Technology on Engineering Science - Volume 1: iCAST-ES},
year={2022},
pages={821-827},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011891500003575},
isbn={978-989-758-619-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 5th International Conference on Applied Science and Technology on Engineering Science - Volume 1: iCAST-ES
TI - Implementation of Particle Swarm Optimization (PSO) Method in Minimum Quantity Lubrication (MQL) Optimization to Obtain Optimal Machining in CNC Milling Machine
SN - 978-989-758-619-4
AU - Hendrawan Y.
AU - Anshori F.
AU - Pratama A.
AU - Harja H.
AU - Pandoe.
AU - Danadibrata A.
PY - 2022
SP - 821
EP - 827
DO - 10.5220/0011891500003575
PB - SciTePress