Weldability of Aluminium Alloys for Automotive Applications

Löveborn, David; Larsson, Johnny K.; Persson, K.-A.

doi:10.1016/j.phpro.2017.08.011

“…Aluminium is a crucial metal for defence, aerospace and automotive industries due to its lightweight, high corrosion resistance and heat treatable nature. Welded aluminium parts are widely utilised in many engineering applications, besides wrought and cast aluminium materials [1]. Despite its numerous advantages, there are practical problems in the joining process of aluminium and its alloys due to their thermophysical properties.…”

Section: Introductionmentioning

confidence: 99%

Characterisation of figure-eight shaped oscillation laser welding behaviour of 5083 aluminium alloy

Kabasakaloglu

¹

,

Erdogan

²

2020

Science and Technology of Welding and Joining

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Figure-eight shaped oscillation movement of laser was studied to improve the welding quality of 5-mm-thick 5083 aluminium alloy. The tests were conducted at 3 kW laser power for frequency levels ranging from 25 to 125 Hz and focal point positions as 0, −1 and −2 mm. The quality of welds was characterised by non-destructive testing methods including visual, liquid penetrant and radiographic inspections. In addition, mechanical properties were determined by tensile tests and microstructures were examined by digital video camera and optical microscope. The results showed that welds with lower penetration depth and less porous structure could be obtained at 125 Hz frequency independent of the focal point position when compared to the joints produced without beam oscillation.

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“…In general, pores are disruptive points in the microstructure of welds and thus lead to a decrease in the strength of joints. Therefore, one of the objectives in the design of welding processes is to avoid porosity by adjusting the process boundary conditions [25].…”

Section: Analysis Of Process Poresmentioning

confidence: 99%

A Novel Approach to the Holistic 3D Characterization of Weld Seams—Paving the Way for Deep Learning-Based Process Monitoring

Schmoeller

¹

,

Stadter

²

,

Kick

³

et al. 2021

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In an industrial environment, the quality assurance of weld seams requires extensive efforts. The most commonly used methods for that are expensive and time-consuming destructive tests, since quality assurance procedures are difficult to integrate into production processes. Beyond that, available test methods allow only the assessment of a very limited set of characteristics. They are either suitable for determining selected geometric features or for locating and evaluating internal seam defects. The presented work describes an evaluation methodology based on microfocus X-ray computed tomography scans (µCT scans) which enable the 3D characterization of weld seams, including internal defects such as cracks and pores. A 3D representation of the weld contour, i.e., the complete geometry of the joint area in the component with all quality-relevant geometric criteria, is an unprecedented novelty. Both the dimensions of the weld seam and internal defects can be revealed, quantified with a resolution down to a few micrometers and precisely assigned to the welded component. On the basis of the methodology developed within the framework of this study, the results of the scans performed on the alloy AA 2219 can be transferred to other aluminum alloys. In this way, the data evaluation framework can be used to obtain extensive reference data for the calibration and validation of inline process monitoring systems employing Deep Learning-based data processing in the scope of subsequent work.

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“…Therefore, one of the objectives in the design of welding processes is to avoid porosity by adjusting the process boundary conditions. [24] The 3D characterization method for weld seams presented within this paper allows for the first time to obtain comprehensive information about the relationships between pores and the weld seam geometry. Figure 7 shows on the left the pores recorded for an exemplary weld seam using a µCT scan.…”

Section: Analysis Of Process Poresmentioning

confidence: 99%

A Novel Approach to the Holistic 3D Characterization of Weld Seams – Paving the Way for Deep Learning-Based Process Monitoring

Schmoeller

¹

,

Stadter

²

,

Kick

³

et al. 2021

Preprint

3

0

View full text Add to dashboard Cite

In an industrial environment, the quality assurance of weld seams requires extensive efforts. The most commonly used methods for that are expensive and time-consuming destructive tests, since quality assurance procedures are difficult to integrate into production processes. Beyond that, available test methods allow only the assessment of a very limited set of characteristics. They are either suitable for determining selected geometric features or for locating and evaluating internal seam defects. The presented work describes an evaluation methodology based on microfocus X-ray computed tomography scans (µCT scans) which enable the 3D characterization of weld seams, including internal defects such as cracks and pores. A 3D representation of the weld contour, i.e., the complete geometry of the joint area in the component with all quality-relevant geometric criteria, is an unprecedented novelty. Both the dimensions of the weld seam and internal defects can be revealed, quantified with a resolution down to a few micrometers and precisely assigned to the welded component. On the basis of the methodology developed within the framework of this study, the results of the scans performed on the alloy AA 2219 can be transferred to other aluminum alloys. In this way, the data evaluation framework can be used to obtain extensive reference data for the calibration and validation of inline process monitoring systems employing Deep Learning-based data processing.

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Weldability of Aluminium Alloys for Automotive Applications

Cited by 28 publications

References 3 publications

Characterisation of figure-eight shaped oscillation laser welding behaviour of 5083 aluminium alloy

Characterisation of figure-eight shaped oscillation laser welding behaviour of 5083 aluminium alloy

A Novel Approach to the Holistic 3D Characterization of Weld Seams—Paving the Way for Deep Learning-Based Process Monitoring

A Novel Approach to the Holistic 3D Characterization of Weld Seams – Paving the Way for Deep Learning-Based Process Monitoring

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