An Experimental Based Approach Using Artificial Intelligence Algorithm for Determining the Surface Roughness by Milling Process

被引：0
|
作者：
Gjelaj, Afrim [1 ]
Berisha, Besart [1 ]
Sitek, Wojciech [2 ]
机构：
[1] Univ Prishtina, Fac Mech Engn, Prishtina, Kosovo
[2] Silesian Tech Univ, Fac Mech Engn, Gliwice, Poland
来源：
INTERNATIONAL TRANSACTION JOURNAL OF ENGINEERING MANAGEMENT & APPLIED SCIENCES & TECHNOLOGIES | 2022年 / 13卷 / 05期
关键词：
Milling; Surface roughness model; Testing of material; Optimization; Artificial intelligence;
D O I：
10.14456/ITJEMAST.2022.86
中图分类号：
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号：
07 ; 0710 ; 09 ;
摘要：
Surface roughness plays an important role in the machining area. This work aims to investigate surface roughness with the use of main machining parameters. Steel C35 is used as workpiece material while performing experimental work with twenty-one experiments, and coolant is taken as constant. The experimental model considers two ways to analyze the surface roughness using Artificial Intelligence. The first is the measurement of surface roughness after machining, and the second is to compare the measurement in a theoretical way. Disciplinary: Mechanical Engineering. (c) 2022 INT TRANS J ENG MANAG SCI TECH.
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页数：11
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