A comprehensive geometrical, metallurgical, and mechanical characteristic dynamic model of laser beam welding process

The welding industry is facing increasing demands for improved productivity, efficiency, and quality, particularly in the laser beam welding process. As advanced materials with complex compositions are used to achieve specific functional properties, there is a growing need for a comprehensive and precise understanding of how these materials can be effectively and efficiently joined. In this paper, we present an innovative and comprehensive model that can accurately predict the geometrical, metallurgical, and mechanical characteristics of the laser beam welding process. The model consists of two main subsystems: the thermal dynamic model and the characteristic model. The thermal dynamic model captures essential parameters such as melt pool dimension, maximum temperature, and cooling rates throughout the welding process. This enables the prediction of geometrical characteristics of the weld, particularly in terms of melt pool dimension. The characteristic model encompasses sections dedicated to geometrical, metallurgical, and mechanical characteristics. By analyzing the cooling rate, the model can diagnose important metallurgical characteristics, including primary dendrite arm spacing (PDAS) and secondary dendrite arm spacing (SDAS). Based on the PDAS and SDAS, the model predicts the mechanical strength during the welding process. The results of our study demonstrate the exceptional accuracy of model 2, which incorporates both primary and secondary dendritic arm distances. The model achieved impressively low error rates of only 0.8298% and 0.8300% for PDAS and SDAS, respectively. These findings highlight the model’s reliability and effectiveness in predicting the mechanical strength of welded joints during the laser beam welding process. This comprehensive model offers valuable insights and predictive capabilities that are crucial for optimizing the welding process and achieving superior productivity, efficiency, and quality. By accurately predicting the geometrical, metallurgical, and mechanical characteristics, it enables engineers and researchers to make informed decisions, enhance process control, and ensure the successful integration of advanced materials in laser beam welding applications.