How robot users can benefit from artificial intelligence

Oliver Giertz looks at some of the key benefits of artificial intelligence in robots

From voice control to the implementation of 3D vision, the pace of development in robotics is accelerating rapidly. But perhaps the most significant trend right now is the embedding of artificial intelligence into mainstream robotic systems. This is delivering extended capabilities and enabling the full potential of predictive – even prescriptive – maintenance to be realised.

Robot technologies, themselves, continue to evolve, and one of the most promising developments is the application of artificial intelligence (AI). We are already seeing a number of AI functions impacting on robotics. For example, in 3D vision sensing; adjustment time is significantly reduced by AI. Force detection precision is also improved by integrating AI technology with the force sensor.

Perhaps one of the most significant trends in AI with regard to robotics is the implementation of enhanced predictive maintenance technologies. 

A recent Frost & Sullivan report estimated that the cost of unplanned downtime within industrial manufacturing amounted to €45bn, of which 42% was primarily caused by factory equipment failures. There is more than just the cost of lost production itself to be considered.

In addition unplanned outages force a reactionary and costly approach to maintenance, repair and equipment replacement in an effort to get the line up and running as quickly as possible.

This can be addressed by predictive maintenance, which provides the user with an early warning of failing or deteriorating parts. 

Having this information gives service teams the opportunity to perform any maintenance well in advance of any actual failure, reducing unplanned downtime and shortening planned downtime. This is just as relevant to robots as it is to other aspects of the production line: periodic maintenance is required on the robot’s various servo joints to ensure long-term reliable operation.

These predictive maintenance technologies can be enhanced significantly by AI, where machine learning algorithms drive even greater insights into the machine’s operation, not simply comparing current performance with a pre-established baseline, but going further to make decisions on real-time data and past trends.

A good example of AI-based predictive maintenance in practice is Mitsubishi Electric’s MELFA Smart Plus function delivered within its latest robot series. This integrated technology precisely monitors the time each of the main robot components is in motion and derives maintenance schedules according to actual operating conditions. It also offers simulation capabilities to predict the robot lifetime during the design phase of the application and to estimate the annual maintenance costs. This gives engineers the opportunity to modify the robot’s operation to extend the lifecycle.

Mitsubishi Electric’s MELFA RV-8CRL is the latest industrial robot to benefit from the Smart Plus technology. 

The cost-effective, but quality performance robot has been built from the outset to minimise maintenance requirements. It incorporates features such as a beltless coaxial drive mechanism for reduced wear. It also uses the latest servomotors from Mitsubishi Electric which eliminates the need for batteries to back-up the robot’s internal encoder. 

Combining these advanced design features with AI-based predictive maintenance can significantly increase availability by reducing both scheduled and unscheduled downtime.

There is still much more to come from AI-based predictive maintenance, and from the wider application of artificial intelligence to robots. It is a core technology for Mitsubishi Electric, with its process optimisation capabilities offering huge potential to improve productivity and availability on robotic systems, as well as the wider manufacturing environment.

Oliver Giertz is Product Manager EMEA for Servo/Motion and Robotics at Mitsubishi Electric Europe BV.