Thermal Modeling of Tool-Work Interface during Friction Stir Welding Process

Chikh, Amina; Serier, Mohamed; Al-Sabur, Raheem; Siddiquee, Arshad Noor; Gangil, Namrata

doi:10.3103/s1067821222060049

Cited by 11 publications

(2 citation statements)

References 18 publications

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“…The above equations were used to analyze the FSSW process and predict the quality of the weld. The heat generation equation is used to calculate the amount of heat generated during the process, which is important for determining the temperature of the materials [ 24 ]. The heat transfer equation was used to predict the temperature distribution in the materials.…”

Section: Methodsmentioning

confidence: 99%

Numerical and Experimental Analyses of Developed Friction Stir Spot Welding (DFSSW) Based on Systematic Design Process Approach

Abd Al-Sahb,

Hussein,

Mohammed

et al. 2024

The Scientific World Journal

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This research paper presents a developed technique for Friction Stir Spot Welding (FSSW) to join similar aluminum sheets (6061), and then this technique was analyzed critically based on numerical simulation and experimental work. The objective of this Developed Friction Stir Spot Welding (DFSSW) is to avoid or at least reduce the keyhole defects by optimizing the design parameters of the process. The coupling problem (thermomechanical) was solved numerically using the finite element method to find the variations of temperatures and stress distributions in addition to the applied forces by the tool. Different parameters were considered in the numerical analysis, such as rotational speed and plunge depth. The experimental results proved the success of the developed technique by comparing the available results of tensile shear force with the results of other researchers that applied the traditional FSSW. It was obtained the highest tensile shear force (2388 N) under the optimal working and design conditions, when the rotational speed, plunging depth, height, and diameter of the sliced disc were 2100 rpm, 0.3 mm, 3.5 mm, and 12 mm, respectively. It was found that both the diameter and height of the sliced disc are significant parameters that ensure the success of this new technique when selecting the suitable values for these parameters. Otherwise, selecting unsuitable values of these parameters leads to appearing defects (e.g., flash) or the sample will fail under a low level of tensile shear force. The other essential advantage outcome point of this new technique was reducing the defect of the keyhole significantly compared with the results of typical Friction Stir Spot Welding. According to the results of the promising developed welding procedure that can be automated, it can be used widely in the industrial sectors.

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Section: Methodsmentioning

confidence: 99%

Numerical and Experimental Analyses of Developed Friction Stir Spot Welding (DFSSW) Based on Systematic Design Process Approach

Abd Al-Sahb,

Hussein,

Mohammed

et al. 2024

The Scientific World Journal

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show abstract

“…A tool with a round, flat shoulder and a smaller probe extending from its centre is used in FSW [1]. FSW as a solid-state manufacturing process shows the good ability to fabricate high strength joints in comparison with conventional fusion welding techniques Figure 1 and Figure 2 below show the friction stir welding process and its four stages [2,3]. The behaviour of material flow in FSW has been the subject of numerous studies.…”

Section: Introductionmentioning

confidence: 99%

Enhancing Friction Stir Welding: Quality Machine Learning Based Friction Stir Welding Tool Condition Monitoring

2024

Int. Res. J. multidiscip. Technovation

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Ensuring the quality and optimizing the tool in Friction Stir Welding (FSW) process is quite complex and the solution relies on implementing Condition Monitoring. The major impact of this process yields good quality welds and cuts down the non-operational timing and cost. Condition Monitoring is the key to find a solution to the challenging problem of ensuring quality and optimizing the tool in the FSW process. The creation of a graphical user interface (GUI) and the development and comparison of several models, including Decision Tree (DT), Random Forest (RF), Light Gradient Boosted Machine (LGBM), and Extreme Gradient Boosting (XGBoost), are the main objectives of this study. By offering an uniform interface for tracking and evaluating tool condition data, GUI can make it easier for operators and the maintenance crew to collaborate. Vibration analysis is the first step in tool condition monitoring. Al5083 and AZ31B are used as the workpiece and H13 as the tool in this investigation. The signals are obtained from the experimental setup via DAQ, and LabView processes them. A Python script converts the raw signals into statistical data. Following that, the data was loaded into ML models and optimized using Optuna. TKinter has been used to create the GUI. For prediction, the best models were included in the GUI. By the deployed models, LGBM generates 96% for 1000 rpm, 96.55% for 1200 rpm, and 95.90% for 1400 rpm for Al5083 93.22% for 1000 rpm, 99.29% for 1200 rpm, and 91.50% for 1000 rpm for AZ31B. For real-time prediction, these models are thus connected to a graphical user interface. In each case, the LGBM classifier topped the others. This work served as an initial basis for the creation of a semi-onboard diagnostic approach that requires minimal human input.

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Optimization of friction stir processing to improve the mechanical properties of bone fixation plate inputs made of ZK60 magnesium alloy

Thanikodi,

Giri,

Ramesh

et al. 2024

Int J Adv Manuf Technol

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Thermal Modeling of Tool-Work Interface during Friction Stir Welding Process

Cited by 11 publications

References 18 publications

Numerical and Experimental Analyses of Developed Friction Stir Spot Welding (DFSSW) Based on Systematic Design Process Approach

Numerical and Experimental Analyses of Developed Friction Stir Spot Welding (DFSSW) Based on Systematic Design Process Approach

Enhancing Friction Stir Welding: Quality Machine Learning Based Friction Stir Welding Tool Condition Monitoring

Optimization of friction stir processing to improve the mechanical properties of bone fixation plate inputs made of ZK60 magnesium alloy

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