NEW ROBOTIC WELDING PROCESS CONTROL TOOLS RAISE OVERALL EQUIPMENT EFFECTIVENESS

As a fabricating and metalworking professional, you are no doubt vigilant and focused on keeping costs under control, directing energy and attention toward quality improvement, pursuing innovation and maintaining a focus on higher productivity.

Overall equipment effectiveness (OEE) is a combined metric that shows how effectively a manufacturing operation is performing. OEE gives the overall performance of a piece of equipment or manufacturing workcenter and is driven by three factors: availability (the percent of scheduled production time that is available), performance rate (the percent of parts produced compared to a standard), and quality (the percent of sellable parts produced compared to parts started).

The goal of OEE analysis is to reduce complex problems into a simple, intuitive presentation of information. This allows for focus to be placed on three categories to reduce or eliminate efficiency losses in manufacturing, including: breakdowns and setup adjustments, startup scrap and production rejects, and causes for reduced speed.

PROCESS CONTROL IS INCREASINGLY A CONTRACT REQUIREMENT

No matter what product you manufacture, there is a good chance that process control and monitoring are also becoming an external requirement to document and manage for your fabricating process. For example, in the automotive industry where high strength steels are used, or in structural steel welding where quenching and tempered steels are used, process control is a contract requirement to insure that qualified welding procedures are applied.

In either of these two industries, procedure qualification and process control are commonly required to document heat input (conventional welding process) or true energy input (advanced welding process). Variation outside of these controlled parameters may adversely affect the mechanical properties, metallurgical structure in the weld and the heat affected zone of the weldments.

Automation coupled with process control provides the means to secure precision and repeatability with tightly controlled procedures and the ability to accurately measure characteristics such as heat input or true energy. The integration of ?intelligence? and productivity measurement tools into automation applications has become easier and more cost effective due to the advancement of vision systems and production monitoring software.

VISION SYSTEMS ERROR-PROOF, ADD INTELLIGENCE TO ROBOTIC WELDING

Vision is an increasingly common component of many automation opportunities. The advancement of new technology has made the integration of vision systems more practical and cost effective. In recent years, the drawbacks of these systems being too sensitive or requiring too much maintenance have been overcome.

Cameras mounted on a robot or to a stationary point in the workcell gather data that is fed back to the welding robot controller. The controller can then see the location and orientation of parts in order to examine and verify part fit up, find features pre-weld, measure the joint position and detect what is going on ahead of the arc. The camera also provides real-time seam tracking and signal changes to user-defined process parameters by using an adaptive parameter control.

The integrated, easy-to-program software calculates the relationship between the camera and the robot, detecting any deviation from the original program.

Pre-weld and post-weld vision in a robot cell has many significant benefits. First, it minimizes tooling complexity and cost by eliminating proximity switches for part detection and clamp verification. Second, it lends itself to error proofing, or the ability of a system to either prevent an error in a process or detect it before further operations can be performed. Error proofing can be performed on every weld in a process or to monitor the critical welds, reduce the potential for scrapped parts, allowing the ability to verify model changes, orientation and part counts in assemblies.

PRODUCTION MONITORING SOFTWARE

Production monitoring software provides access to the metrics to measure availability and performance and monitor limits and tolerances. Robots are increasingly integrating digital technology to network welding equipment to extract a hierarchy of production data to focus on how effectively a manufacturing operation is utilized.

Production monitoring software enables any networked power source to be set up so that weld data can be monitored to establish a productivity benchmark. Basic process control includes the ability to monitor input parameters such as voltage, amperage, wire feed speed and time, along with the ability to verify certain performance requirements, such as gas and water flow.

Weld limits and tolerances can be set and alarms generated when the process limits are exceeded. This prevents the system from continuing to weld with out-of-process parameters. Consumable inventory can be tracked, serial number traceability can be performed and diagnostic troubleshooting can be performed remotely with integrated production monitoring software.

Management personnel, production supervisors and system operators are able to quickly detect problems and take action after reviewing easy-to-understand reports and charts that identify factors contributing to a lack of productivity, scrap and rework ? yielding direct cost savings.

SUMMARY

Integrated vision and production monitoring are two key tools that allow for the extraction and conversion of data to information to make informed decisions allowing for a focus on opportunities for cost savings, quality improvement and higher productivity. If you are welding manually today, consider looking for opportunities and project types where automation can be implemented, and where process control can be introduced to raise your overall equipment effectiveness.

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Geoff Lipnevicius is the operations manager for the automation division at The Lincoln Electric Company, 22800 Saint Clair Avenue, Cleveland, OH 44117-8542, 216-383-8027, Fax: 216-383-8823, www.lincolnelectric.com, [email protected].