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To achieve these goals, manufacturers are investing heavily in digitally controlled automated assembly systems. These systems offer two advantages: high-volume manufacturing of high-quality vehicles and detailed control of every key process. These systems capture and track a broad range of production data.
High-speed, midfrequency, direct-current resistance welding is one such system. Robotic resistance welders can rapidly weld hundreds of parts per hour cost-effectively. However, to ensure the quality of each weld, engineers must periodically conduct destructive and ultrasonic testing of assemblies.
Now, a new technology—adaptive control—has the potential to revolutionize the quality, flexibility and productivity of high-speed resistance welding, and it could obviate the need for follow-up testing of welded assemblies.
Adaptive control of resistance welding control uses unique hardware and software to precisely adjust welding parameters, in real time, so every weld is performed within the tightest quality tolerances.
Ultrasonic inspection of a welded joint is a manual process that involves taking a sample part from the assembly line and subjecting it to a standalone inspection. Based on the results of the test, engineers can then adjust current, time and other welding parameters.
The problem is, ultrasonic inspection is time-consuming and not all that repeatable. The part only represents the quality of that particular welding process during a given production run. The sample doesn’t necessarily indicate what’s happening with every part. Moreover, the results can vary based on the tester’s opinion of what represents a good weld.
By comparison, adaptive control integrates the inspection of each weld with the real-time control of how each weld is performed. This saves time, improves quality, and ensures that every weld is inspected and documented by the control system. Integration also maintains high levels of welding throughput.
An adaptive control welding system, such as the PSQ 6000 made by Bosch Rexroth, monitors current, voltage and resistance parameters once per millisecond during automated welding. These parameters are constantly compared in real time against a previously established master resistance curve that controls the quality of the process.
This master resistance curve is generated through a mathematical calculation of previously captured and stored current, voltage and resistance curves of known good welds. The PSQ 6000 automatically raises and lowers welding current and weld time, in real time, to keep the actual parameter values as close as possible to those of the master curve—with the anticipated result that each weld will have equivalent quality.
The adaptive control system measures the current and voltage at the electrode. Mathematical algorithms calculate resistance curves and energy balance. Data from the weld—such as the process stability factor, weld quality factor and explosion—are stored and made available for monitoring and trend analysis. The current is then adjusted to compensate for minute differences as welding proceeds. In special circumstances, sheet combinations with different thicknesses and coatings can be welded by a single program for special process applications, such as manual welding.
This kind of control enhances welding flexibility, so manufacturers can be more responsive to fast-changing market needs. The automated platform can store and operate multiple welding schedules, and allows manufacturers to quickly change welding schedules for different components and body types.
Welding Process Repeatability
Manufacturers seek weld reliability, which helps them consistently meet their production and quality requirements. Unfortunately, every welding process is subject to variations. For resistance welding, these include part fit up and thickness, misaligned electrodes, coating material composition or thickness, sealers, weld force, shunting and machine tooling degradation.
Welding gun tip wear is another factor that can affect weld reliability. Most manufacturers control tip wear through regular weld testing. Unfortunately, dozens or even hundreds of components might be welded before periodic testing uncovers a problem with worn electrode tips.
In contrast, adaptive control of resistance welding automatically compensates for output changes as gun tips wear. Equally important, adaptive control provides an information framework to assure manufacturers that weld reliability is actually being achieved.
Because 100 percent of the welds are inspected in real time, the platform captures a record of each weld and any variations the controller made to ensure that the weld was within the established parameters. In terms of process control, this is a significant improvement over projecting weld quality from results obtained by manual product sampling.
Many automated resistance welding operations have multiple robots performing hundreds of welds per minute. Without real-time control, the robots deliver a constant flow of power to the guns, which, in certain instances and with certain materials, is more than necessary to complete the weld.
The excess sparks pose an increased risk of explosion and worker injury, which lead to lost worker productivity and increased healthcare costs. Operations without real-time control also require enclosures and other expensive protective devices and procedures.
Adaptive control receives real-time feedback of conditions on a component’s surface and adjusts the current flow to just the right level to complete the weld without generating explosion. Some studies have shown that adaptive control also reduces overall energy consumption by welding tools.
Besides increasing worker safety and operational quality, adaptive control reduces the dirt and contamination associated with explosions in the welding workspace. A cleaner work environment lessens the need for maintenance and the likelihood of particulates interfering with sensitive electronic connections, sensors and other production line equipment.
The true value of any automation technology is measured in how it helps a manufacturer generate savings through improved productivity and lower manufacturing costs. While there are costs associated with adding adaptive control to a resistance welding platform, adaptive control can lower the total cost of a welding system in several ways:
Significant reduction of testing costs, including labor, time, documentation, expense per part tested, and scrapped and testing materials.
Elimination of weld quality spills and quarantine requirements.
Less rework of components, recalls, rebates and legal liability due to increased weld reliability.
Lower production cost per part due to increased throughput from 100 percent weld inspection.
Reduction of explosion-related costs due to a safer and cleaner workspace with less contaminants and better quality welds.
To better illustrate the cost-saving potential of adaptive control, consider the following example. A resistance welding line with 14 robots performs 150 spot-welds per part and generates about 800 parts per day in three shifts. Even after factoring in the cost of the control’s components and programming, an automotive manufacturer could expect to reduce the cost of testing and quality control for resistance welding by more than 30 percent over six years.
Equally important, this amount does not include savings associated with improved parts quality. Plus, automotive manufacturers can efficiently integrate and retrofit adaptive control into their existing resistance welding platforms.