Systematic evaluation of pulsed laser parameters effect on temperature distribution in dissimilar laser welding: A numerical simulation and artificial neural network

With the proliferation of electric drivetrains, the development and optimization of joining techniques for the fabrication of battery packs became a prime manufacturing topic. Decreasing the electrical resistance and increasing the mechanical strength of the welds at the individual cell level are of great importance not only for productivity and efficiency but also for safety and sustainability purposes. Lasers offer an advanced, highly automatable solution for battery cell joining. Usually, the optimization focuses on the laser parameters or the scanning speed. However, the most widespread battery welding geometry, the so-called lap geometry, allows alternative possibilities for joint property optimization. The novelty of our approach is that we focus on systematic experimental investigation of the effects of dimensional parameters and the layout of the weld pattern. Systematic experiments reveal that the shape and size of the weld area have substantial effect on the properties of the laser welded joint. Our results prove that a rather substantial gain can be achieved in both the electrical and mechanical properties when the weld consists of at least two parallel bead segments. We also show that it is beneficial by both means if the segments have the greatest individual length and placed apart at the maximum feasible distance. The orientation of the straight segments affects the mechanical and electrical behavior differently: strongest welds consist of weld segments oriented in parallel, while the smallest resistance can be achieved using segments oriented perpendicular to the direction of current flow, respectively.

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A review on optimization of autonomous welding parameters for robotics applications

Ali,

El-Betar,

Magdy

2024

Int J Adv Manuf Technol

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In order to withstand the competitive nature of the industrial market and maintain the longevity of products, researchers try to enhance current technologies and create cost-effective solutions. Aside from acquiring new machinery, it also involves successfully managing actual process variables. To get the desired and financially advantageous results, it is necessary to measure, control, and optimize these process variables. The welding process is significantly influenced by its characteristics, which play a major role in assessing the weld quality and reducing the welding time while ensuring the elimination of defects. This study provides a comprehensive overview of the research findings, developments, and remarkable techniques. First, the effective old-trade techniques applied for welding optimization are discussed. Then, the sophisticated methods depending on AI are handled for adaptive welding control, such as ANN in tandem with GA models, ant colony optimization technique, and the NSGA-III algorithm. After that, summarize the relevant research related to building models with supportive vision sensing elements for seam tracking, monitoring the weld pool, and handling feedback control. Finally, the future research difficulties and directions toward real-time intelligent monitoring are highlighted. This review will help aspiring and ambitious researchers gain a comprehensive understanding of welding optimization for robotics applications.

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Systematic evaluation of pulsed laser parameters effect on temperature distribution in dissimilar laser welding: A numerical simulation and artificial neural network

Cited by 12 publications

References 55 publications

Laser Welding of Thin Ferrous Sheets with Ferrous and Non‐Ferrous Sheets

Laser Welding of Thin Ferrous Sheets with Ferrous and Non‐Ferrous Sheets

Improvement of electrical and mechanical properties of laser welded lap joints via dimensional optimization

A review on optimization of autonomous welding parameters for robotics applications

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