PSI - Issue 66

S. Skrobacz et al. / Procedia Structural Integrity 66 (2024) 11–25 S. Skrobacz¹², P. Krysi ń ski¹, S. Ma ł ys¹², T. Ł agoda² / Structural Integrity Procedia 00 (2025) 000–000

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prices of utilities and raw materials, compel companies to optimize their processes, increase productivity, and ensure repeatable quality [1]. One of the key processes in the railway industry is welding. As a special process, it is regulated by a series of standards such as DIN EN 15085 [2], the EN 1090 series of standards concerning the execution of steel and aluminum structures, and the international technical standard ISO/TS 22163 [3], which defines the requirements for quality management systems. The transition from manual to robotic welding necessitates meeting several parameters and conducting tests aimed at achieving a precise and high-quality welded joint within an optimal production time [4]. As a result, there is an improvement in the quality and fatigue strength of the door frame intended for use in rail vehicles [5]. Another challenge in production is the material. Modern constructions must have a low mass, which drives the industry to use appropriate materials such as aluminum alloys EN AW 6060, EN AW 6082, and EN AW 6063 [5]. The use of various profile cross-sections, tailored to the product’s function, presents challenges related to welding thin aluminum alloys. The heat input is closely related to the quality of the weld and can cause porosity, cracks, and distortion defects [7]. Aluminum has a low melting temperature, high thermal conductivity, and lower tolerance for surface contamination, which further complicates the welding process [8]. Approaches have been employed to mitigate these issues, such as careful clamping of the workpiece, improved joint preparation for tight fitting, and advanced heat input control [9]. This study outlines the steps taken to investigate the fatigue of prepared samples. A thorough analysis was conducted to demonstrate the hypothesis that automated welding allows for the creation of higher-quality welds with fewer defects, resulting in greater resistance to applied forces compared to welds made by manual methods [10]. Welding is used in many industries as an effective and economical method of joining metal components. However, the nature of the welding process often results in welds having lower fatigue strength than the base material [11]. Therefore, any assessment of the durability of a welded structure must place significant emphasis on the fatigue assessment of weld joints [12].

Nomenclature a: Thickness of the sample (mm) 131 (robot): Refers to the designation of the robotic station within the enterprise b: Width of the sample (mm) Befund: Non-conformity or defect observed during the test Bruchlage: Fracture location of the sample BW: Butt weld

d ₐ : Allowable diameter of defect (mm) d ₘₐₓ : Maximum diameter of defect (mm) End with Gas Porosity; 2011; d ₘₐₓ = 0.1 mm; d ₐ ≤ 0.6mm F ₀ . ₂ : Yield force at 0.2% offset (kN) Fm: Maximum force during the tensile test (kN) h ₐ : Allowable defect height (mm) h ₘₐₓ : Maximum defect height (mm) PA: Flat position S ₀ : Initial cross-sectional area of the sample (mm²) σ₀ . ₂ : Yield strength at 0.2% offset (N/mm²) σᵤ : Ultimate tensile strength (N/mm²)

2. Robotic Welding Station and Its Validation The tested joints are produced on an automated workstation. The welding cell has been selected to accommodate the dimensions of the welded door frames, with the dimensions of the welding cell being 8800x6385 mm as shown in Figure 1.