2 Case Studies of Successful Automation Using Collaborative Robots

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By David

It costs you money to keep your equipment idle but collaborative robots are constantly on the task, even if the machine tending roles are difficult to fill and keep. Machine tending applications like press braking and dial tables benefit from collaborative automation because they can function consistently and reliably around the clock. You’ll keep your shop functioning and be able to promote experienced machinists to higher-paying roles.

Modern robots are now at the centre of collaborative welding solutions, which are less expensive than typical automated systems and may need installation in normal welding work cells. Move your finest welders to more fantastic product lines by automating repetitive or small unappealing goods for welders.

Matsunami Glass

Matsunami Glass Ltd. makes Glass for microscopic, medicinal, and electronic applications. Due to space constraints and the necessity for specialized development that needed outsourcing, the company discovered that deploying traditional industrial robots to ease human shortages was challenging.

After learning about Universal Robots’ industrial collaboration robots, the company developed robot applications in-house, including loading oversized glass discs into devices for cutting as part of their glass design process.

The 15 cobots helped achieve a significant increase in production output with no new staffing. Still, they also improved employees’ technical skills, helping to build robotic systems without dealing with external resources.

The Objective

The company advocates for the automation of human-assisted work processes to preserve competitiveness and handle future labour shortfalls. Previously, the enterprise automated its activities with traditional industrial robots. Still, due to the factory’s limited area, it was required to assist the change-over anytime the company needed to employ the industrial robot for a different task.

The Solution

initially drawn to the Universal Robot cobot’s capacity to operate with people without using safety fences. That means they won’t have to worry about the extra cost and hassle of contacting a system vendor to adjust the configuration.

The robot was first added to the thick glass feeding phase of the process by Matsunami Glass. The robot’s ease of operation and the setup went quickly, describing how dealer Inaba Denki brought him to their facility for robot training.

After the orientation program, the supplier appeared on-site to assist with the complete execution. Glass has placed alternately on the front and backside of the machine, depending on the circumstances. They were able to faithfully imitate the human technique of turning and flipping big sheets of Glass because the UR robotic has a 360° joint mobility for each axis.

Inside the act of bringing flat glassware into the cutting machine, cobots are also active. The robot removes packed sheets of glassware using a self-made sucking hand and air blowers. Before the robot’s installation, inserting thousands of sheets of Glass was manually done, which occasionally caused shoulder and wrist problems for the workers. Cobots use helped the company avoid this job stress and increased work efficiency by installing the robot.

There are presently 15 cobots in use. The company’s production output has expanded by 1.5 times in the last decade, but the workforce has remained constant. The company’s staff now believe that the cobots are competent in smoother motions and can accomplish what people do.

Their employees have traditionally handled tiresome activities. But they now see the value in being capable of delivering stable products to their consumers by delegating simple tasks to cobots and empowering people to control quality and procedures, such as inventory and raw material procurement.

AIM Processing

AIM Processing is now handling Universal Robots (UR) collaborative robots. The Colorado infusion moulder needed a modular automation system that was flexible in moving between work stations. The solution was a portable device such as UR5e collaborative robot coupled with Flexx References. This feature allows the cobots to be reconfigured in minutes, resulting in a fourfold boost in productivity and a payback time of fewer than 15 weeks.

The Problem

AIM Processing manufactures approximately 1300 distinct parts for over 100 customers. Each day is unique at the company since very few manufacturing lines have run for a long time due to staffing shortages. T automation was the only answer prompting the management to discover ways to boost the output while controlling costs.

How Cobots Benefits AIM Processing

  • Increased production by fourfold

Since its first deployment, AIM Processing has deployed the UR5e in over a dozen different applications, including tending injection moulding machines, stacking trays, and picking components off conveyors. The first objective was automating the choosing and placement of the trays for the cartesian palletizer. Formerly, this was a 90-second task that had a worker waiting for a few seconds to shift the trays.

The apparent labour savings were not the only advantage of automating this operation but also a constant workflow increasing capacity and productivity.

  • 15-week return on investment

Part of the unpredictability of operating a range of different components for varying durations makes it challenging to calculate payback. Still, the first implementation, as the says the AIM Processing proprietor found out, was that after the fifth run, they paid for the cobot translating into an ROI within 15 weeks.

  • UR cobots are plug-and-play.

All components the company uses to customize robots have been approved by the UR+ programs to work with the cobots. The UR+ features are straightforward to install. The software, known as a URCap, comes on a USB drive that you connect straight into the cobot’s teach pendant, taking care of all the technical complexities of getting the cobot arm to communicate with the peripherals. The URCaps currently allow AIM Processor to program the visual cameras and grippers on the Flexx Reference and Robotiq cobots directly through the teach pendant interface.

Conclusion

The cobot deployment’s success factors go beyond the apparent labour reductions. Many additional subtle advantages have surfaced. You have to deal with the robot’s setup and redeployment, but you also have to deal with workers accidentally bumping against the robot. It wrecks everything up if it’s even slightly out of place. Compared to the few hours the adjustment may otherwise take, employing the Flexx Reference enables the user to reteach that posture that may lead all those other aspects out of place in just a few minutes.