Caren Dripke, head of robotics development at Lorch Schweißtechnik GmbH, does not hesitate when describing AI-enabled welding with cobots.
“It’s like having an apprentice, but it isn’t their very first day on the job,” she says. “Rather, they’ve seen a couple things. And you only need to point out the general description of the job and they can figure the rest out by themselves.”
With all the hype around AI these days, it is easy to lose sight of the fact that it is already being used across multiple industrial applications. This includes automated welding where cobots with AI capabilities are increasingly being deployed to improve ergonomics for skilled welders and drive efficiency.
AI comes in different flavors and is intended for different purposes. Some systems guide the user through the programming process, for example, while others provide seam tracking and path planning capabilities. A common thread running through all AI welding tools is that they virtually eliminate programming as a barrier to automation adoption.
Production bottlenecks
Robot programming is a major bottleneck in welding automation projects, especially for small to medium-size businesses, says David Pietrocola, co-founder and CEO at Cohesive Robotics. Cohesive’s Argus OS allows welding cobots to perform common weld joints and tack welds with automatic vision-based detection out of the box.
“Some manufacturers don’t have a manufacturing engineer on staff, let alone an automation engineer,” Pietrocola says. “The no programming aspect, the AI, the vision – these smarter systems are helping to sidestep those bottlenecks and helping companies bring in robotic technology quicker.”
A welding cobot with Cohesive’s 3-D camera mounted on its arm takes millions of data points from different positions as the robot moves and the Argus OS processes them using AI running on a dedicated, embedded GPU.
“It understands where the parts are,” Pietrocola says. “It knows what it’s looking for and using that information, it’s able to program the robot to go where it needs to go.”
Real-world lessons
Hirebotics’ AI-powered Beacon software provides suggestions designed to guide end users of all experience levels through the automated welding setup process.
“It’s like having a copilot,” says Zach Boyd, chief technology officer at Hirebotics. “For first-time users of automation, it really helps to get them over that initial hurdle. The welders are still in control, but certain things are simplified so they can focus on more of the craft while the cobot focuses on the more monotonous tasks.”
Leveraging AI to optimize parameters, such as voltage, wire feed speed and travel speed, the system uses contextual data to suggest settings tailored to the specific application and material.
The suggestions Beacon provides are not drawn from a limited list of predetermined weld settings and recipes, but from hundreds of real-world deployments of welding cobots that have been analyzed by AI. Moreover, if end users encounter a problem, they can take a picture of the welding cell and Beacon will use AI to suggest fixes.
Lorch’s Dripke says where complex traditional programming requires users to think through multiple waypoints and input many details, with AI-powered tools like Lorch’s SeamPilot, the complexity is removed.
“You don’t have to provide many input parameters,” she says. “You don’t have to set up all the torch angles or provide every single waypoint. Rather, you just say, ‘Here are the parameters, here’s the seam, please weld this.’ SeamPilot takes care of all the geometrical paths. That’s a huge time saver because waypoints usually take the most programming time, so you can easily weld right away.”
Automatic adjustments
Meanwhile, Vectis Automation has developed a range of embedded AI features designed to lower barriers to welding automation deployments. These features are able to reference points trained by the cobot operator, automatically adjusting the travel and work angles to match production standards and auto-detecting corner transitions to enable optimized welds on complex geometries.
Instead of having to precisely place the torch and manually teach all points, these AI features perform the calculations for the operator. Additional features, such as intelligent multi-pass welding, automatic seam tracking and smart path generation for plasma cutting, are also available.
Finding a welder with years of experience who knows, for example, best practices for using a certain work angle and a travel angle for a specific weld is a real challenge for metal shops.
“AI weld path optimization makes it possible for a new welder to quickly jump in and meet these standards,” says Josh Pawley, vice president of business development and founding partner at Vectis Automation. “It eases some of the ‘tribal knowledge’ barrier that welders naturally gain over the course of a long career. We’ve seen dozens of times where the knowledge of an experienced welder in the shop is essentially passed on to the next generation via the cobot tool.”
In terms of high-mix, low-volume production runs, programming traditional welding robots takes considerable time, which can be another barrier to overcome. Depending on the size of the job lot and how long it takes to set up the robot, it may not seem worthwhile automating the welding process at all. AI-powered technologies, however, drastically reduce setup times, enabling job shops to confidently deploy automation even on small jobs.
“When your robot is easy to program,” Dripke says, “it tips the scale toward small lot sizes being easily automated. SeamPilot figures out many things on its own so operators don’t have to. This easy programming enables high productivity even on small lot jobs that previously would’ve been too time-consuming to set up for automated welding.”
The human element
AI can handle a lot of welding tasks, but keeping a human in the loop makes for even more effective solutions.
“The human is the most important resource in welding,” Dripke says. “It’s important to have somebody who understands different materials, welding parameters and job requirements. You also need a human to check the weld quality after the fact. Automating welding as a whole process isn’t easily done, especially with the weld details, so relying on the experience of welders is the way to go.”
Boiled down, it can’t or shouldn’t be a case of ‘either-or’ when it comes to humans and cobot welders. In fact, skilled welders who can also operate welding automation are highly prized and very well paid.
“When you find a skilled welder, that’s great,” Dripke says. “If you find somebody that can program robots, that’s great, too. But, if you find somebody that has skills in welding and can program a robot, you have most likely found somewhat of a unicorn.”
But with major industrial economies worldwide suffering a dramatic shortage of skilled welders, AI systems that fully automate deployment and welding processes are probably inevitable.
“The United States is short hundreds of thousands of welders,” Cohesive’s Pietrocola says. “It’s a similar story in Europe and China. We see our technology as a way to supercharge an existing welding workforce to increase production. And with an aging welding workforce, systems like ours enable workers to actually work longer if they choose because they aren’t the ones who are necessarily welding all day, every day.”
Hirebotics’ Boyd says in some future cases, fully automated welding driven by AI may well be the norm, but cobot-based welding is still about human-robot collaboration.
“There’s a lot of hype about AI and what it can do,” he says, “but at this point, humans are still better at some tasks; it’s very much still a collaboration between a human and a machine. And beyond the hype, there are really practical examples, like Beacon, of being able to embed AI into software that helps customers get started quicker without it being overly intrusive.”
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