294
M. A. A. A. Razak et al.
Keywords Self-supported friction stir welding · Aluminum plate AA5083 · Root
deformation · Analysis of variance
27.1 Introduction
The process of friction stir welding (FSW) utilizes frictional heat generated between
the tool and the work piece to soften and joining two metal parts together. The rotation
of the pin produces enough heat to soften the material. The rotation and translation
of the tools produce the mixing of materials [1]. Manufacturers have the problem
to carry out friction stir welding due to a lack of information on suitable welding
parameters and settings. Suitable parameters will produce good welding results. The
parameters needed in FSW are the welding speed, rotational speed, axial force, and
tool geometry [2]. To carry out this FSW process, all the suitable parameters need
to be set properly [3].
The non-consumable tool was fabricated using the high carbon high chromium
H-13 steel to weld the aluminum plate [4]. Five different tool pin profiles were
fabricated, namely cylindrical, tapered cylindrical, triangular, square and hexagonal
were used in the experiment to choose the most efficient welding tools to perform the
welding process [5]. If insufficient heat generated, the FSW tool stuck in the material
while doing the welding process and the welding process cannot be continued. A
wormhole can appear due to a lack of heat to cause proper material flow [6].
ANOVA is a short term for analysis of variance, and it is known as a general
linear model (GLM) that is widely used for creating any factorial designs for any
experiment. Factors of one or more that contribute to the experiment are categorized
in factorial design [7]. ANOVA is mainly focusing on the F-tests of main effects and
interaction of the desired experiment. This ANOVA is used to analyze and support
the experimental work by using model comparison and model selection accordingly
[8].
In engineering and science field, the signal to noise ratio (SNR) is commonly
applied to measure by comparing the level of background noise with the level of
signal. This method is implemented to interpret the experimental result from the
factors of all levels [9]. Usually the greater the SNR, the stronger the signal or
information in the signal relative to the noise or distortion. The application of SNR
is the efficient approach that is commonly used for data interpretation. SNR can be
computed in time or frequency domain [10].
27.2 Experimental Setup
The Taguchi method was applied to analyze the process parameters that need to be
used for this experiment. The Taguchi method is implemented by using the design of
experiment based on orthogonal arrays to analyze certain variables in certain number
M. A. A. A. Razak et al.
Keywords Self-supported friction stir welding · Aluminum plate AA5083 · Root
deformation · Analysis of variance
27.1 Introduction
The process of friction stir welding (FSW) utilizes frictional heat generated between
the tool and the work piece to soften and joining two metal parts together. The rotation
of the pin produces enough heat to soften the material. The rotation and translation
of the tools produce the mixing of materials [1]. Manufacturers have the problem
to carry out friction stir welding due to a lack of information on suitable welding
parameters and settings. Suitable parameters will produce good welding results. The
parameters needed in FSW are the welding speed, rotational speed, axial force, and
tool geometry [2]. To carry out this FSW process, all the suitable parameters need
to be set properly [3].
The non-consumable tool was fabricated using the high carbon high chromium
H-13 steel to weld the aluminum plate [4]. Five different tool pin profiles were
fabricated, namely cylindrical, tapered cylindrical, triangular, square and hexagonal
were used in the experiment to choose the most efficient welding tools to perform the
welding process [5]. If insufficient heat generated, the FSW tool stuck in the material
while doing the welding process and the welding process cannot be continued. A
wormhole can appear due to a lack of heat to cause proper material flow [6].
ANOVA is a short term for analysis of variance, and it is known as a general
linear model (GLM) that is widely used for creating any factorial designs for any
experiment. Factors of one or more that contribute to the experiment are categorized
in factorial design [7]. ANOVA is mainly focusing on the F-tests of main effects and
interaction of the desired experiment. This ANOVA is used to analyze and support
the experimental work by using model comparison and model selection accordingly
[8].
In engineering and science field, the signal to noise ratio (SNR) is commonly
applied to measure by comparing the level of background noise with the level of
signal. This method is implemented to interpret the experimental result from the
factors of all levels [9]. Usually the greater the SNR, the stronger the signal or
information in the signal relative to the noise or distortion. The application of SNR
is the efficient approach that is commonly used for data interpretation. SNR can be
computed in time or frequency domain [10].
27.2 Experimental Setup
The Taguchi method was applied to analyze the process parameters that need to be
used for this experiment. The Taguchi method is implemented by using the design of
experiment based on orthogonal arrays to analyze certain variables in certain number