ANALISIS PENGARUH KONDISI PEMOTONGAN TERHADAP UMUR PAHAT PADA PROSES FREIS MENGGUNAKAN METODE ANN (ARTIFICIAL NEURAL NETWORKS)

RAMADHANY, FEBRIYANDI and Mohruni, Amrifan Saladin (2016) ANALISIS PENGARUH KONDISI PEMOTONGAN TERHADAP UMUR PAHAT PADA PROSES FREIS MENGGUNAKAN METODE ANN (ARTIFICIAL NEURAL NETWORKS). Undergraduate thesis, Sriwijaya University.

	Text RAMA_21201_03121405008_0011096407_01_front_ref.pdf - Accepted Version Available under License Creative Commons Public Domain Dedication. Download (369kB)
	Text RAMA_21201_03121405008_0011096407_02.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (421kB) | Request a copy
	Text RAMA_21201_03121405008_0011096407_03.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (601kB) | Request a copy
	Text RAMA_21201_03121405008_0011096407_04.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (406kB) | Request a copy
	Text RAMA_21201_03121405008_0011096407_05.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (48kB) | Request a copy
	Text RAMA_21201_03121405008_0011096407_06_ref.pdf - Bibliography Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (13kB) | Request a copy
	Text RAMA_21201_03121405008_0011096407_07_lamp.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (1MB) | Request a copy

Abstract

The development of increasingly advanced technology requires an industry improve product quality with time efficiency and high accuracy. A tool life is an important data in planning a machining process. In this research, it using a tool endmill with material HSS milling process that gets to analyze the machining conditions, namely cutting speed, feeding speed, and depth feeds the tool life and obtain optimum conditions of the tool life by using artificial neural network. To get the value of tool life and tool wear (VB) on the milling machine then performed 18 times the test with three variable cutting speed, feeding, and depth of cut with Artificial Neural Network (ANN) Method. The test data obtainet by cutting speed is very influence on tool life whereas, feeding and deep of cut the less influential because of little value. Then the test result data were analyzed using artificial neural network method with 3-3-1 , analysis was done by software MATLAB error analysis found with an average percentage of 3.25 %

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Milling Machine, cutting speed, feeding, depth of cut, Artificial Neural Network.
Subjects:	T Technology > TJ Mechanical engineering and machinery
Divisions:	03-Faculty of Engineering > 21201-Mechanical Engineering (S1)
Depositing User:	Prof Amrifan Saladin Mohruni
Date Deposited:	18 Jul 2019 15:33
Last Modified:	18 Jul 2019 15:58
URI:	http://repository.unsri.ac.id/id/eprint/414

Actions (login required)

View Item