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Monitoring of the surface roughness by using acoustic emission analysis during end milling process [electronic resource] / Intan Yasmin Ismail

By:

Intan Yasmin Ismail

Material type:

Computer filePublication details: Kuantan, Pahang : UMP, 2016Description: 1 computer disc : digital data ; 12 cmISBN:

THE0005084(Local)

Subject(s):

Dissertation note: Project Paper (Bachelor of Engineering in Mechatronis Engineering (Hons.)) -- Universiti Malaysia Pahang – 2016 Abstract: Surface roughness of Aluminium Alloy 6061 has been investigated under different cutting condition by using Aoustic Emission (AE) sensor in milling operation. The experiment has shown that AE components are effectively respond to the change of occurrences in milling process.Three controllable factors are used as machining parameter. They are cutting speed, feed rate and depth of cut. The workpiece is clamped tightly on the workbench of milling machine and the AE sensor (PK15i) is mounted on top at the end of workpiece. The tool material used is 20mm 4 flute high speed steel cutting tool. All data collected from the AE sensor are displayed in AEWin and analysed in MATLAB software. Fast Fourier Transform (FFT) method is used to convert time domain into frequency domain signal and hence the rms, amplitude and frequency could be calculated. The surface roughness of the workpiece is measured by using Surfcom 130A. The results indicated that the most of the cutting parameter that influenced the surface roughness is feed rate, followed by cutting speed, and finally depth of cut.

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Title notes ( 5 )

Holdings
Item type	Current library	Call number	Copy number	Status	Date due	Barcode
Final Year Report	UMPLIB PEKAN	FKP .I58 2016 r Bc. \| CD 10413 (Browse shelf(Opens below))	1	Not for loan		0000115928

Faculty of Manufacturing Engineering

Theses Gred B

Project Paper (Bachelor of Engineering in Mechatronis Engineering (Hons.)) -- Universiti Malaysia Pahang – 2016

Surface roughness of Aluminium Alloy 6061 has been investigated under different cutting condition by using Aoustic Emission (AE) sensor in milling operation. The experiment has shown that AE components are effectively respond to the change of occurrences in milling process.Three controllable factors are used as machining parameter. They are cutting speed, feed rate and depth of cut. The workpiece is clamped tightly on the workbench of milling machine and the AE sensor (PK15i) is mounted on top at the end of workpiece. The tool material used is 20mm 4 flute high speed steel cutting tool. All data collected from the AE sensor are displayed in AEWin and analysed in MATLAB software. Fast Fourier Transform (FFT) method is used to convert time domain into frequency domain signal and hence the rms, amplitude and frequency could be calculated. The surface roughness of the workpiece is measured by using Surfcom 130A. The results indicated that the most of the cutting parameter that influenced the surface roughness is feed rate, followed by cutting speed, and finally depth of cut.

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