Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal Jurnal Poros Teknik Mesin Unsrat
Ones Tatogo
Sam Ratulangi University
Automotive Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
PREDIKSI KEBUTUHAN ENERGI LISTRIK PEMESINAN BERDASARKAN VARIASI CAMPURAN MEDIA PENDINGIN PADA MESIB BUBUT KENT USA RML-1640T Ones Tatogo; Romels Cresano A Lumintang; Tertius Ulaan; I Nyoman Gede; Jefferson Mende; Irvan Rondonuwu
Jurnal Poros Teknik Mesin UNSRAT Vol. 15 No. 1 (2026): Jurnal Poros Teknik Mesin Unsrat
Publisher : Fakultas Teknik Jurusan Teknik Mesin Universitas Sam Ratulangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35793/jptmu.v15i1.68656

Abstract

Cutting fluids have special uses in the machining process in addition to extending tool life, cutting fluids are also able to reduce cutting forces and smooth the surface of the machined product. There are several factors that affect cutting power in the lathe process, including cutting conditions, workpiece material and the use of coolant. From several factors that affect the cutting power, this research tries to analyze the use of several cutting mixtures to predict the electrical energy requirements on turnning in the Mechanical Engineering Laboratory of Sam Ratulangi University (Unsrat). The purpose of this research is to predict the machining electrical energy requirement based on machining variation of cutting mixture on KENT USA RML-1640T lathe. This research is experimental research, namely by conducting tests on a turnning by varying the mixture of cutting media as an independent variable to obtain machining electrical energy as the dependent variable. The results of the analysis obtained from this study show that the actual machining electrical energy is lowest in the 1:10 cutting media mixture, because it has less water volume. From the prediction results, the appropriate equation is obtained, namely the quadratic regression equation y ̂ = (203.689175)+ (0.010712)x-(0.000002) x^2, because the coefficient of determination reaches 77.1% accuracy close to the actual data. Keywords: Cutting Media, Electrical Energy, Turnning Machine
Co-Authors I Nyoman Gede Irvan Rondonuwu Jefferson Mende Romels Cresano A Lumintang Tertius Ulaan