Engineering Review: Double Pulse Collaborative Arc Welding System – Seoul, South Korea

Field Engineering Report: Implementation of Double Pulse Collaborative Arc Welding in Seoul High-Precision Facilities

1. Introduction and Site Context

The following report details the technical deployment and optimization of a Double Pulse Collaborative Arc Welding System at a Tier 1 electronics and power distribution manufacturing site in Geumcheon-gu, Seoul. The facility’s objective was the transition from manual TIG processes to a sophisticated Automated Welding workflow to handle the increasing volume of high-purity Copper Components welding.

In the Seoul industrial context, floor space is at a premium and the labor market for high-fidelity manual welders is tightening. This necessitates a shift toward systems that can operate alongside human technicians without the massive footprint of traditional robotic light curtains and safety interlocks. The integration of a Collaborative Arc Welding System (CAWS) addresses these spatial constraints while maintaining the high-amperage output required for non-ferrous thermal management.

2. The Synergy: Collaborative Arc Welding System & Automated Welding

The primary technical hurdle in Seoul was bridging the gap between “cobot” flexibility and the rigorous consistency of Automated Welding. Unlike traditional industrial robots that operate on fixed trajectories with rigid logic, the Collaborative Arc Welding System used here utilizes sensitive torque sensors and a “lead-through” programming interface. This allows our on-site welding technicians to hand-guide the torch to complex start-stop points on the copper busbar assemblies.

The synergy between these two technologies manifests in the “Double Pulse” waveform control. While the automated system handles the micro-adjustments of wire feed speed (WFS) and peak current at kilohertz frequencies, the collaborative framework allows the operator to intervene and adjust the torch angle (work/travel angle) in real-time during “test-dry” runs without rewriting thousands of lines of G-code. In the field, we found that this reduced our setup time for new component geometries by 40% compared to traditional automated cells.

Waveform Dynamics in Automated Pulse-on-Pulse

To achieve successful Automated Welding on 10mm oxygen-free copper, we implemented a Double Pulse (DP) logic. The CAWS controller manages two distinct pulse frequencies: a high-frequency pulse to agitate the weld pool and break up surface oxides, and a low-frequency pulse to manage the heat input and create the characteristic “stacked dimes” aesthetic without the need for manual torch oscillation. This frequency interplay is critical; without the automated precision of the power source communicating with the cobot’s motion controller, the copper’s high thermal conductivity would lead to instantaneous “burn-through” or “cold-lapping” at the end of the weld path.

3. Technical Challenges: Copper Components Welding

Copper Components welding is notoriously difficult due to a thermal conductivity rating roughly ten times that of carbon steel. In the Seoul workshop, the ambient humidity and the purity of the copper (C10100) presented significant porosity risks.

Thermal Dissipation and Preheating Strategy

The sheer heat sink effect of large copper busbars means that even at 400 Amps, the start of the weld often lacks fusion. We integrated a localized induction preheating step into the Automated Welding sequence. The Collaborative Arc Welding System was programmed to wait for a thermocouple feedback loop—integrated into the cobot’s I/O—to reach 200°C before initiating the arc.

A “lesson learned” here was the impact of the grounding clamp location. In copper welding, the arc blow is exacerbated by the high currents. We moved to a dual-grounding configuration, which stabilized the arc column and allowed the Double Pulse system to maintain a consistent droplet transfer.

Shielding Gas Optimization

We abandoned standard Argon for a 75% Helium / 25% Argon mix. In the Seoul facility, sourcing high-purity Helium is a cost factor, but for Copper Components welding, the increased ionization potential of Helium is non-negotiable to achieve the required penetration depth. The CAWS was fitted with an automated gas flow regulator that ramps up the Helium mix during the “crater fill” stage to prevent shrinkage pipes, a common failure point in automated copper joints.

4. Collaborative Integration on the Seoul Production Floor

The “Collaborative” aspect of the system is not merely about safety; it is about the workflow between the senior welding engineer and the machine. In our Seoul implementation, the technician handles the fit-up and tacking of the Copper Components, while the Automated Welding system executes the long-seam structural passes.

Safety and Sensor Calibration

The Seoul site utilized a “fenceless” design. We calibrated the force-torque sensors to trigger an immediate E-stop if the torch head encountered a resistance of more than 15 Newtons. This allowed the welding staff to work on the adjacent jig while the robot was active. This “multi-station” approach increased the duty cycle of the power source from 30% (manual) to 85% (automated collaborative).

5. Lessons Learned and Field Observations

After three months of operation in Seoul, several critical takeaways have emerged regarding the intersection of CAWS and Copper metallurgy:

1. Wire Feed Consistency

Copper wire is soft. The Automated Welding feeder must use U-groove rollers with precisely calibrated tension. We found that even slight over-tensioning deformed the wire, leading to micro-stoppages that the Collaborative Arc Welding System interpreted as a collision, triggering false alarms. We switched to a “push-pull” torch system, which synchronized perfectly with the Double Pulse frequency to ensure zero bird-nesting.

2. The “Seoul Humidity” Factor

During the monsoon season, hydrogen-induced porosity in Copper Components welding became a recurring issue. We had to upgrade the gas delivery lines to stainless steel braided hoses to prevent moisture permeation. The automated system’s “start-sequence” was modified to include a 5-second pre-flow of gas to purge the line entirely before the first pulse.

3. Programming for Thermal Expansion

Copper expands significantly when heated. A static program that worked on a cold component would be off by 1.5mm by the time the robot reached the end of a 500mm seam. We implemented a “Touch Sensing” routine where the Collaborative Arc Welding System uses the welding wire itself to sense the edge of the component at three points before every weld. This automated offset adjustment ensures the arc stays on the root regardless of thermal distortion.

6. Metallurgical Result and NDT Findings

Non-Destructive Testing (NDT) via X-ray on the Seoul-produced copper busbars showed a 98% reduction in internal voids compared to the previous manual TIG process. The Double Pulse waveform effectively “stirred” the molten pool, allowing trapped gases to escape before solidification. Furthermore, the heat-affected zone (HAZ) was narrowed by 25%, preserving the structural integrity and electrical conductivity of the C10100 copper.

7. Conclusion

The deployment of the Double Pulse Collaborative Arc Welding System in Seoul demonstrates that “Automated Welding” is no longer confined to high-volume automotive lines. By leveraging the flexibility of collaborative robotics and the specific power electronics of Double Pulse waveforms, we have successfully addressed the unique challenges of Copper Components welding. The key to success was not just the hardware, but the integration of localized environmental variables—thermal expansion, gas purity, and operator-led “lead-through” programming—into a cohesive technical strategy.

Future iterations will focus on integrating AI-driven vision systems to further refine the “collaborative” feedback loop, allowing the system to compensate for imperfect part fit-up without human intervention.

Engineer: Senior Welding Lead, APAC Division
Location: Seoul, South Korea
Status: System Operational / Optimization Phase