In modern industrial manufacturing, the adoption of robot technology has revolutionized welding processes, enabling higher precision, consistency, and efficiency. As a researcher focused on advancing welding automation, I have conducted an in-depth study on the factors affecting single-sided welding with double-sided formation in horizontal welding positions using robot technology. This investigation aims to optimize the root pass welding for 8 mm thick Q345E steel plates with HV-groove butt joints, employing robotic pulse welding. The integration of robot technology allows for precise control over welding parameters, which is critical for achieving high-quality welds in challenging positions like horizontal welding. Through systematic experiments, I analyzed the effects of welding current, arc length, and assembly gap on weld formation, providing insights that can enhance the performance of welded joints in applications such as rail vehicle components. The use of robot technology not only improves productivity but also ensures repeatability, making it indispensable in industries requiring stringent quality standards.
The foundation of this research lies in leveraging robot technology to address the complexities of horizontal welding, where issues like lack of fusion, incomplete penetration, and poor weld appearance are common. By employing a robotic system, I could maintain stable welding conditions and systematically vary parameters to observe their impact. The robot technology used here includes an ABB-IRB2600-XT welding robot with a Fronius TPS4000 power source, which offers digital pulse welding capabilities. This setup enables precise adjustments to welding current, arc length, and other variables, facilitating a detailed analysis of how these factors influence the root pass formation. The goal is to establish optimal parameters that ensure consistent double-sided formation, thereby reducing defects and improving overall weld integrity in automated environments.
To conduct the experiments, I used Q345E steel plates with dimensions of 200 mm × 100 mm × 8 mm, which comply with GB/T 1591-2008 standards. The chemical composition and mechanical properties of the base material are summarized in the tables below. The welding wire was G3Si1 with a diameter of 1.0 mm, and the shielding gas was a mixture of 84% argon and 16% carbon dioxide, flowing at 18 L/min. The robot technology allowed for leftward welding in the horizontal position without arc oscillation, using a single V-groove of 45° on the upper plate and no blunt edge. The joint configuration and weld cross-section parameters, such as backside reinforcement (a), backside width (B1), front width (B2), lower leg (Z1), and upper leg (Z2), were carefully measured to evaluate weld quality.
| C | Si | Mn | P | S | Als | Nb | Fe |
|---|---|---|---|---|---|---|---|
| 0.04 | 0.07 | 1.09 | 0.014 | 0.010 | 0.036 | 0.01 | Bal. |
| Yield Strength (MPa) | Tensile Strength (MPa) | Elongation (%) |
|---|---|---|
| 528 | 429 | 33.5 |
The experimental procedure involved pre-weld cleaning to remove contaminants, precise gap control using magnetic fixtures, and evaluation based on backside penetration, reinforcement, width, and front-side appearance. The welding parameters were varied as per the following table, focusing on welding current, arc length, and assembly gap. The heat input, a critical factor in welding, can be expressed using the formula: $$ Q = \eta \cdot I \cdot U / v $$ where Q is the heat input (J/mm), I is the welding current (A), U is the arc voltage (V), v is the welding speed (mm/s), and η is the arc efficiency (assumed as 0.8 for this process). This formula helps in understanding the energy distribution during welding, which is essential for analyzing weld formation in robot technology applications.
| Factor | Welding Current (A) | Arc Voltage (V) | Arc Length (mm) | Assembly Gap (mm) | Welding Speed (mm/s) | Power Type/Polarity | Wire Extension (mm) |
|---|---|---|---|---|---|---|---|
| Welding Current | 100 | 20.0 | 0 | 1 | 4 | DC EP/+ | 15 |
| Welding Current | 120 | 20.8 | 0 | 1 | 4 | DC EP/+ | 15 |
| Welding Current | 140 | 21.1 | 0 | 1 | 4 | DC EP/+ | 15 |
| Welding Current | 160 | 21.4 | 0 | 1 | 4 | DC EP/+ | 15 |
| Arc Length | 120 | 20.8 | -2 | 1 | 4 | DC EP/+ | 15 |
| Arc Length | 120 | 20.8 | 0 | 1 | 4 | DC EP/+ | 15 |
| Arc Length | 120 | 20.8 | +2 | 1 | 4 | DC EP/+ | 15 |
| Arc Length | 120 | 20.8 | +4 | 1 | 4 | DC EP/+ | 15 |
| Assembly Gap | 120 | 20.8 | 0 | 0.5 | 4 | DC EP/+ | 15 |
| Assembly Gap | 120 | 20.8 | 0 | 1 | 4 | DC EP/+ | 15 |
| Assembly Gap | 120 | 20.8 | 0 | 1.5 | 4 | DC EP/+ | 15 |
| Assembly Gap | 120 | 20.8 | 0 | 2 | 4 | DC EP/+ | 15 |
In the analysis of welding current effects, I observed that varying the current significantly influenced the weld geometry. The table below summarizes the weld dimensions for different welding currents. As the current increased from 100 A to 160 A, the backside reinforcement initially rose and then decreased, while the backside width showed a similar trend. This can be modeled using a polynomial relationship: $$ a = k_1 \cdot I^2 + k_2 \cdot I + k_3 $$ where a is the backside reinforcement, I is the welding current, and k1, k2, k3 are constants derived from experimental data. For instance, at 120 A, the backside reinforcement peaked at 0.48 mm, but further increases led to a reduction due to elevated heat input concentrating on the front side. The use of robot technology enabled precise current control, highlighting its role in optimizing energy distribution for desired weld profiles.
| Welding Current (A) | Arc Voltage (V) | Backside Reinforcement a (mm) | Backside Width B1 (mm) | Front Width B2 (mm) | Lower Leg Z1 (mm) | Upper Leg Z2 (mm) |
|---|---|---|---|---|---|---|
| 100 | 20.0 | 0.25 | 2.80 | 5.42 | 6.90 | 4.0 |
| 120 | 20.8 | 0.48 | 3.20 | 6.96 | 7.64 | 4.0 |
| 140 | 21.1 | 0.20 | 3.68 | 7.50 | 7.84 | 5.28 |
| 160 | 21.4 | 0.15 | 1.18 | 9.56 | 8.44 | 6.9 |
When examining arc length variations, I found that shorter arc lengths resulted in better backside formation and reduced defects like undercut. The data for different arc lengths is presented in the table below. The arc length, which fine-tunes the arc voltage, affected the arc diameter and heat input. A shorter arc (e.g., -2 mm) concentrated energy on the root, increasing backside width to 4.24 mm, while longer arcs spread energy, leading to undercut on the upper plate. This relationship can be described by: $$ B1 = c_1 \cdot L + c_2 $$ where B1 is the backside width, L is the arc length, and c1, c2 are constants. Robot technology facilitated accurate arc length adjustments, demonstrating its importance in maintaining arc stability and controlling metal transfer in horizontal welding.
| Arc Length (mm) | Backside Reinforcement a (mm) | Backside Width B1 (mm) | Front Width B2 (mm) | Lower Leg Z1 (mm) | Upper Leg Z2 (mm) |
|---|---|---|---|---|---|
| -2 | 0.28 | 4.24 | 6.7 | 7.38 | 4.66 |
| 0 | 0.48 | 2.8 | 6.96 | 7.64 | 4.0 |
| +2 | 0.6 | 3.0 | 7.04 | 7.26 | 4.12 |
| +4 | 0.7 | 2.84 | 7.2 | 7.28 | 5.0 |
The assembly gap had a profound impact on backside formation, as smaller gaps hindered metal flow to the backside, causing defects. The table below shows weld dimensions for different gaps. As the gap increased from 0.5 mm to 2 mm, the backside reinforcement and width improved, but the upper leg decreased due to gravity effects. This can be expressed as: $$ a = m_1 \cdot G + m_2 $$ where a is the backside reinforcement, G is the assembly gap, and m1, m2 are constants. For example, at a 2 mm gap, backside reinforcement reached 0.82 mm, but excessive gaps risked burn-through. Robot technology ensured consistent gap control, underscoring its value in achieving uniform weld quality across variable conditions.
| Assembly Gap (mm) | Backside Reinforcement a (mm) | Backside Width B1 (mm) | Front Width B2 (mm) | Lower Leg Z1 (mm) | Upper Leg Z2 (mm) |
|---|---|---|---|---|---|
| 0.5 | 0.36 | 2.66 | 6.48 | 7.46 | 4.44 |
| 1 | 0.48 | 2.8 | 6.96 | 7.64 | 4.0 |
| 1.5 | 0.6 | 3.92 | 7.06 | 7.46 | 4.52 |
| 2 | 0.82 | 4.6 | 6.72 | 7.52 | 3.78 |
In conclusion, this study highlights the critical factors influencing single-sided welding with double-sided formation in robot horizontal welding. Welding current primarily affects backside reinforcement and width, with an optimal range around 120 A to 140 A for balanced formation. Arc length fine-tunes the weld appearance, where shorter arcs minimize defects. Assembly gap directly impacts backside quality, and moderate gaps of 1-1.5 mm are recommended to avoid issues. The integration of robot technology enables precise parameter control, ensuring consistent results and enhancing the reliability of automated welding processes. Future work could explore real-time monitoring using advanced robot technology to further optimize weld quality in dynamic industrial environments.
Throughout this research, the application of robot technology has proven essential for achieving high-quality welds in challenging positions. By systematically analyzing parameters, I have demonstrated how robot technology can be leveraged to overcome common welding defects, providing a foundation for improved automation in sectors like transportation and construction. The formulas and tables presented here offer practical guidance for engineers, emphasizing the role of robot technology in advancing welding innovation. As industries continue to adopt automation, the insights from this study will contribute to more efficient and reliable welding solutions, driven by the capabilities of modern robot technology.