Friction Self-Piercing Riveting (F-SPR) of AA6061-T6 to AZ31B

2013 ◽  
Author(s):  
YongBing Li ◽  
ZeYu Wei ◽  
YaTing Li ◽  
ZhaoZhao Wang ◽  
Xiaobo Zhu
Keyword(s):  
Magnesium Alloys ◽  
Spot Welding ◽  
High Speed ◽  
Dissimilar Materials ◽  
Friction Stir Spot Welding ◽  
Friction Stir ◽  
Riveting Process ◽  
Solid State Joining ◽  
Joining Process ◽  
Vehicle Bodies

Implementation of lightweight low-ductility materials such as aluminum alloys, magnesium alloys and composite materials has become urgently needed for automotive manufacturers to improve the competitiveness of their products. However, the hybrid use of these materials poses big challenges to joining processes. Self-piercing riveting (SPR) is currently the most popular technique for joining dissimilar materials and has been widely used in joining all-aluminum and multi-material vehicle bodies. However, in riveting magnesium alloys, cracks always occur for its low ductility. In this paper, a hybrid joining process named friction self-piercing riveting (F-SPR), which combines mechanical joining mechanism of SPR with solid-state joining mechanism of friction stir spot welding (FSSW) by making rivet rotating at high speed in riveting process, was proposed aiming at joining the low ductility materials. 1-mm-thick AA6061-T6 and 2-mm-thick AZ31B were used to validate the effectiveness of the F-SPR process. The results showed that the F-SPR process could significantly improve the rivetability of magnesium alloys, and greatly increase the joint strength, comparing with traditional SPR process.

Friction Self-Piercing Riveting of Aluminum Alloy AA6061-T6 to Magnesium Alloy AZ31B

2013 ◽  
Vol 135 (6) ◽  
Author(s):  
YongBing Li ◽  
ZeYu Wei ◽  
ZhaoZhao Wang ◽  
YaTing Li
Keyword(s):  
Magnesium Alloys ◽  
Spot Welding ◽  
High Speed ◽  
Dissimilar Materials ◽  
Friction Stir ◽  
Magnesium Alloy Az31b ◽  
Riveting Process ◽  
Solid State Joining ◽  
Joining Process ◽  
Vehicle Bodies

Implementation of lightweight low-ductility materials such as aluminum alloys, magnesium alloys and composite materials has become urgently needed for automotive manufacturers to improve the competitiveness of their products. However, hybrid use of these materials poses big challenges to traditional joining process. Self-piercing riveting (SPR) is currently the most popular technique for joining dissimilar materials and has been widely used in joining all-aluminum and multimaterial vehicle bodies. However, in riveting magnesium alloys, cracks always occur for its low ductility. In this paper, a hybrid joining process named friction self-piercing riveting (F-SPR), which combines mechanical joining mechanism of SPR with solid-state joining mechanism of friction stir spot welding (FSSW) by making rivet rotating at high speed in riveting process, was proposed aiming at joining the low-ductility materials. The effectiveness of the F-SPR process was validated via riveting 1 mm thick AA6061-T6 and 2 mm thick AZ31B. The results showed that the F-SPR process could significantly improve the rivetability of magnesium alloys, and greatly increase the joint strength, comparing with the traditional SPR process.

Numerically modelled study of the plunge stage in friction stir spot welding using multi-tiered mesh partitions

2021 ◽  
Author(s):  
Arindom Baruah ◽  
Jayaprakash Murugesan ◽  
Hemant Borkar
Keyword(s):  
Spot Welding ◽  
Material Model ◽  
Friction Stir Spot Welding ◽  
Frictional Heat ◽  
Complex Behaviour ◽  
Friction Stir ◽  
Spot Joining ◽  
Solid State Joining ◽  
Joining Process ◽  
Significant Attention

Abstract Friction stir spot welding is a solid-state joining process that has attracted significant attention particularly in the field of joining of lightweight, low melting alloys. These materials include alloys of Aluminium and Magnesium amongst many others which are of great importance to the aerospace and the automobile industries. The friction stir spot welding is a complex thermo-mechanical multiphysics phenomenon and is currently a field of intense research. The motivation of the current study is to understand this complex behaviour of the joining process by simulating it in the ABAQUS CAE environment. In the friction stir spot joining technique, the plunge stage is identified as the critical stage of operation as it involves a highly transient and dynamic zone for material and temperature flows. The plunge stage was studied in detail using the finite element based model. The plasticity of the material was simulated by the Johnson-Cook material model while the frictional heat generation was captured by applying a penalty-based frictional contact between the rotating tool and the workpiece contact surfaces. Considering the reasonable assumptions made, the results obtained by the numerical simulation model were found to agree with the past experimental and numerically modelled studies.

Effects of High Speed Tool Rotation in Micro Friction Stir Spot Welding of Aluminum A1100

2014 ◽  
Vol 493 ◽  
pp. 739-742 ◽  
Author(s):  
Ario Sunar Baskoro ◽  
Suwarsono ◽  
Gandjar Kiswanto ◽  
Winarto
Keyword(s):  
Shear Strength ◽  
Spot Welding ◽  
High Speed ◽  
Tool Material ◽  
Friction Stir Spot Welding ◽  
Welding Parameters ◽  
Friction Stir ◽  
Tool Shoulder ◽  
Welding Processes ◽  
Tool Rotation

Technology of Friction Stir Welding (FSW) is a relatively new technique for joining metal. In some cases on Aluminum joining, FSW gives better results compared with the arc welding processes, including the quality of welds and less distortion. The purpose of this study is to analyze the parameters effect of high speed tool rotation onmicro Friction Stir Spot Welding(μFSSW) to theshear strengthof welds. In this case, Aluminum material A1100, with thickness of 0.4 mm was used. Tool material of HSS material was shaped with micro grinding process. The spindle speed was fixed at 30000 rpm. Tool shoulder diameter was 3 mm, and a length of pin was 0.7 mm. The parameter variations used in this study were the variable of pin diameter (1.5 mm, 2.0 mm, and 2.5 mm), a variable ofplunge speed(2 mm/min, 4 mm/min, 6 mm/min), and the variable ofdwell time(2 seconds, 4 seconds, 6 seconds). Where the variation of these parameters will affect to the mechanical properties of welds (as response) was theshear strength.Response Surface Methods(RSM) was used to analyze μFSSW parameters with theshear strengthof welds. From the result of experiment and analysis, it is shown that the important welding parameters in high speed μFSSW process are pin diameter and plunge speed.

scholarly journals Friction Stir Spot Welding of Aluminum and Copper: A Review

Materials ◽  
2019 ◽  
Vol 13 (1) ◽  
pp. 156 ◽  
Author(s):  
Mingshen Li ◽  
Chaoqun Zhang ◽  
Dayong Wang ◽  
Li Zhou ◽  
Daniel Wellmann ◽  
...  
Keyword(s):  
Material Flow ◽  
Spot Welding ◽  
Dissimilar Materials ◽  
Industrial Applications ◽  
Friction Stir Spot Welding ◽  
Research Progress ◽  
Current Status ◽  
Friction Stir ◽  
Dissimilar Metal ◽  
Metal Materials

Aluminum (Al) and copper (Cu) have been widely used in many industrial fields thanks to their good plasticity, high thermal conductivity and excellent electrical conductivity. An effective joining of dissimilar Al and Cu materials can make full use of the special characteristics of these two metals. Friction stir spot welding (FSSW), as an efficient solid-state welding method suitable for joining of dissimilar metal materials, has great prospects in future industrial applications. In this paper, the FSSW studies on Al-Cu dissimilar materials are reviewed. The research progress and current status of Al-Cu FSSW are reviewed with respect to tool features, macroscopic characteristics of welded joints, microstructures, defects in welds and mechanical properties of joints. In addition, some suggestions on further study are put forward in order to promote the development and progress of Al-Cu FSSW studies in several respects: material flow, thermal history, addition of intermediate layer, auxiliary methods and functionalization of Al-Cu FSSW joint.

scholarly journals Evaluation of mechanical property predictions of refill Friction Stir Spot Welding joints via machine learning regression analyses on DoE data

2021 ◽  
Author(s):  
Frederic E. Bock ◽  
Tino Paulsen ◽  
Nikola Brkovic ◽  
Lennart Rieckmann ◽  
Dennis Kroeger ◽  
...  
Keyword(s):  
Machine Learning ◽  
Mechanical Property ◽  
Process Parameters ◽  
Spot Welding ◽  
Friction Stir Spot Welding ◽  
Regression Analyses ◽  
Friction Stir ◽  
Joint Properties ◽  
Process Property ◽  
Solid State Joining

The high-potential of lightweight components consisting of similar or dissimilar materials can be exploited by Solid-State Joining techniques. Whereas defects such as pores and hot cracking are often an issue in fusion-based joining processes, via solid-state joining processes they can be avoided to enable high-quality welds. To define an optimal process window for obtaining anticipated joint properties, numerous time and cost consuming experiments are usually required. Building a predictive model based on regression analysis enables the identification and quantification of process-property relationships. On the one hand, mechanical property and performance predictions based on specific process parameters are needed, on the other hand, inverse determination of required process parameters for reaching desired properties or performances are demanded. If these relations are obtained, optimized process parameter sets can be identified while vast numbers of required experiments can be reduced, as underlying physical mechanisms are utilized. In this study, different regression analysis algorithms, such as linear regression, decision trees and random forests, are applied to the refill Friction Stir Spot Welding process for establishing correlations between process parameters and joint properties. Experimental data sets used for training and testing are based on a Box-Behnken Design of Experiments (DoE) and additional test experiments, respectively. The machine-learning based regression analyses are benchmarked against linear regression and DoE statistics. The results illustrate a decryption of relationships along the process-property chain and its deployment to predict mechanical properties governed by process parameters.

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