Purchasing industrial robots doesn’t guarantee a company now has a high-performing item. Manufacturers need to make sure they incorporate their machines into their production line well & continuously optimize their machines. Taking proactive measures to enhance performance will lead to success. What strategies should you implement?
Explore Solutions to Improve Accuracy
Although people often discuss precision and accuracy interchangeably, there are important differences between them. Precision relates to how closely a robot gets to its target. Some laboratory and welding tasks only tolerate positioning errors of 0.5 mm, for example.
Accuracy refers to how consistently the robot can perform the task. A high repeatability rate is the goal, especially for duties like materials removal or picking.
When improving accuracy is the aim, decision-makers can go about it in several ways. One possibility is to use secondary absolute encoders. They require preliminary calibration and are more expensive than some other options, but the results are often worthwhile.
Another option is to determine the relationship between several measurements:
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Robot base: The machine’s origin point and where any forward kinematics measurements begin.
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The tool center point: The end effector’s frame that interacts with the workpiece, such as a gripper or nozzle.
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Workpiece: The object that the robot interacts with during operation.
Large-volume metrology tools can determine the geometric relationship between those three parameters. Having that information can substantially improve an industrial robot’s accuracy.
Devices outside the robot can use measurement-derived kinematic models to correct the machine’s path depending on how far it strays from the ideal movement.
Alternatively, online correction options refer to data from external measurement systems to exert closed-loop control on the robot’s position. External metrology devices, such as laser trackers, guide the robot and improve its accuracy.
Consider Using Cameras on the Robots
Many company representatives conclude that intelligent vision systems could help them achieve better robot performance. However, moving ahead with that option is not as straightforward as bolting a camera onto a machine.
A good starting point is to iron out how the combination of cameras and industrial robots could improve the success rate of specified tasks. For example, a camera could help a bot find randomly placed components. It can also recognize their orientations and confirm the presence of features, such as whether a part has a bar code or drilled hole.
It’s also crucial to confirm the camera’s field of view and verify that the environmental lighting is bright enough to minimize error rates. Teaching the robot how to link what it sees with a particular task helps the machines improve performance after having cameras installed.
Monitor Robotic Filter Performance
Industrial robots require filters to stop particulate matter from damaging internal components. They keep a machine’s oil and gas lines free from contaminants. They also protect against problems with the machine’s hydraulic lines.
One method is to change filters according to manufacturer recommendations about hours of usage. However, that strategy could mean people switch them out too early or late. If so, they could either spend money unnecessarily or deal with preventable problems due to inadequate maintenance.
Another possibility that could boost performance is to switch to a condition-based monitoring system. For example, a hydraulic robot filter that shows a pressure drop may need to be changed.
Intelligent monitoring could alert people when a filter cannot hold more contaminants before the bypass valve opens. Moreover, when people stay abreast of filter function over time, they’ll be more aware of any performance issues that could warrant a closer investigation. Using big data tools to track the frequency of changes based on usage could illuminate possible issues to explore further.
Have a Technician Diagnose Performance Issues
Statistics indicate that more than 125,000 robots arrived in industrial facilities between 2010 and 2017. Robotics technicians are in demand, and that will likely be the reality for the foreseeable future.
Some factory managers find themselves in positions where their robots were performing well, but that gradually changed. In cases like that, a robotic technician can get to the root of the problem, whether it relates to circuitry, software or something else.
Interventions from technicians are particularly vital when clients enter into performance-based service agreements with providers. The machine-as-a-service (MaaS) model is relatively new, but it appeals to people interested in robotics investments and have some hesitations. That’s because the provider bears the burden of assuring the customer that the equipment will meet minimum performance standards.
Companies in the MaaS space often depend on cloud technology to remotely monitor customers‘ machines. Representatives can then immediately flag problems and dispatch technicians to sites when necessary.
Stay Abreast of Industry Developments
Higher levels of robot performance should also become possible as more companies pool their resources for mutual benefits. One such collaboration between a hardware company and a software brand enabled a commercially available robot to follow humans. That opportunity eliminated the need to solely control the bot with a joystick.
Instead, a person pushes a button to activate a sensor array. That action equips the robot to view the individual as a leader and base its movements on what they do. The human does not need to use specialized apps or engage in dedicated training sessions to make the robot follow them.
Another pairing of companies involves developing operational frameworks and deep learning models to improve preventive maintenance for industrial robots. Many businesses already use Internet of Things (IoT) sensors and big data analytics to identify worrisome trends that could indicate future malfunctions. This work is an extension of that approach, and it’s almost certainly not the only collaboration of its kind.
Remaining knowledgeable about industry advancements isn’t a quick fix for current performance shortcomings. However, it could help an industrial robot user determine whether other people experience the same issues or have similar feature requests. Moreover, communicating with a robotic technology provider about the desire for future performance upgrades could emphasize the need for improvements.
Better Performance for Industrial Robots Is Possible
As these tips show, there’s no single, guaranteed solution for making an industrial robot perform better. A strategy might include calibration, a tweaked maintenance program or accessories to extend functionality.
After determining where suboptimal performance exists and addressing it, it’s time to track metrics. This will help to verify whether the technician’s changes produced the intended results. Similarly, using a big data platform to measure various performance metrics can spotlight performance declines before they affect operations.
