Image of ANALISIS KEKASARAN PERMUKAAN PADA PEMESINAN FREIS MENGGUNAKAN CAIRAN PEMOTONGAN NANOFLUIDA MINYAK NABATI DAN OPTIMASINYA DENGAN MACHINE LEARNING
Bookmark Share

Skripsi

ANALISIS KEKASARAN PERMUKAAN PADA PEMESINAN FREIS MENGGUNAKAN CAIRAN PEMOTONGAN NANOFLUIDA MINYAK NABATI DAN OPTIMASINYA DENGAN MACHINE LEARNING

This study aims to analyze the influence of machining parameters on surface roughness and to optimize the milling process using a machine learning approach. The machining process was conducted on AISI 1045 steel using the down milling method with a Minimum Quantity Lubrication (MQL) system based on coconut oil combined with Fe₃O₄ nanoparticles as a nano-cutting fluid. The machining parameters investigated include cutting speed (Vc), feed per tooth (fz), and axial depth of cut (a), while the surface roughness parameter analyzed is surface roughness arithmetic (Ra). The experimental data consist of 30 data points, which were divided into 27 training data and 3 testing data. Data processing and model development were performed using the Python programming language on the Google Colab platform. The machine learning methods applied in this study are K-Nearest Neighbors (KNN) Regression and Bayesian Ridge Regression, with model performance evaluated using Mean Absolute Percentage Error (MAPE) and Mean Square Error (MSE). The results indicate that KNN Regression achieved a MAPE value of 16.68% and an MSE value of 0.0138, while Bayesian Ridge Regression produced a MAPE value of 19.51% and an MSE value of 0.0169 on the testing data. Furthermore, the optimal machining parameter combination was obtained at a cutting speed of 40.82 m/min, a feed per tooth of 0.028 mm/tooth, and an axial depth of cut of 0.5 mm

Availability
#
Central Library (Reference) T1915902025
T191590
Available but not for loan - Not for Loan
Detail Information
Series Title
-
Call Number
T1915902025
Publisher
Indralaya : Prodi Teknik Mesin, Fakultas Teknik Universitas Sriwijaya.,
Collation
xxix, 107 hlm.; ilus.; 29 cm
Language
Indonesia
ISBN/ISSN
-
Classification
621.910 7
Content Type
Text
Media Type
unmediated
Carrier Type
-
Edition
-
Subject(s)
Prodi Teknik Mesin, Teknik Pemesinan (Milling)
Specific Detail Info
-
Statement of Responsibility
Other version/related
File Attachment
Comments
You must be logged in to post a comment