Autonomous decentralized manufacturing

If an industrial robot stops unexpectedly on a factory line, the robot in the next step in the production sequence will also be unable to proceed. If this happens, the entire line stop when one robot stops. This is because when the robot is controlled in one direction by a controller such as a programmable logic controller (PLC), the robot can only perform the operations indicated in the order given. In order for robots to work autonomously and cooperatively with other robots, it is necessary for them to have the ability to think and judge for themselves. This type of manufacturing is called “autonomous decentralized manufacturing. “

By absorbing data such as torque value, vibration value, or temperature from the servo motor into the controller, the autonomy aspect of the robot is enhanced, and the robot can determine how to move if any other robot stops moving in the previous order.

Other solutions

  • Production Production
    Production
  • Quality Quality
    Quality
  • Maintenance Maintenance
    Maintenance

Shorter installation time

AI picking

AI Picking

By utilizing the AI technology “Alliom” developed by Yaskawa Group, the installation time to actual operation is drastically shortened, and the accuracy to actual machine can also be improved.

Production Production

Flexible production

High variety and variable quantity production

High Variety and Variable Quantity Production

By using digital data to manage automated production lines, setup can be prepared automatically without manual intervention, enabling high variety and variable quantity production from a minimum of one unit.

Production Production

Accuracy improvement

Accuracy improvement of defect cause analysis Yaskawa case

Accuracy Improvement of Defect Cause Analysis < Yaskawa Case >

By “visualizing” the operation status of equipment/devices with Yaskawa Cockpit, it is possible to identify the root cause by comparing the normal value and abnormal value of the data in the factor analysis for defects in production.

Quality Quality

Quality inspection

Automated product quality assessment with AI

Automated Product Quality Assessment with AI

When the quality inspection process is labor-saving, the use of an image judgement service that utilizes AI technology such as deep learning makes it possible to automatically determine complex No Good patterns with the same level of accuracy as humans.

Quality Quality

Failure prediction

Predictive failure diagnosis of equipment

Predictive Failure Diagnosis of Equipment

To reduce downtime to zero by performing planned maintenance in anticipation of equipment failure due to wear, etc., in response to concerns that production may become impossible due to the sudden shutdown or something else.

Maintenance Maintenance

Recovery support

Investigating the cause of equipment failure

Investigating the Cause of Equipment Failure

By acquiring quality data on when, with which equipment, and how it was processed, it is possible to accurately identify the cause of the problem between which equipment and equipment at the time of failure.

Maintenance Maintenance
Faster Recovery Simulation

Faster Recovery Simulation

The planning technology that Yaskawa developed automatically generates optimal paths, enabling simulation in a few minutes and dramatically reducing engineering time for recovery from sudden stop.

Maintenance Maintenance