Enhancing the accuracy of analyzing the cause of defects Case study

Yaskawa Group’s Iruma Solution Factory, which began operations in 2018, manufactures the Σ -7 series servomotors and servo packs, as well as our company’s i3-Mechatronics as a “testing and proven factory” that achieves single-line production and High Variety and Variable quantity production from a minimum of single unit for a total of one thousand varied items.

testing and proven factory testing and proven factory

At the factory, we operate own servomotors and industrial robots, as well as AGVs (automated guided vehicles), etc., and manage production plans and results, collecting, accumulating, and analyzing data on the operating status of production facilities by “visualizing” the operating status of these equipment and devices through Yaskawa Cockpit. This integrated data is centrally monitored in the control center.

monitored in the control center.

For example, if the axis of a manufactured motor does not rotate smoothly, the cause of the malfunction can be identified by analyzing the cause, such as whether it is related to “production process”, “product design”, or procured parts from outside the company”, by comparing the normal value of the data with the error value. By providing feedback to each department on the cause analysis of defects based on the detailed data collection at each site, we succeeded in making about 100 improvement proposals a year from the production department to the product design department.

At this factory, the implementation of i3-Mechatronics has resulted in the identification of the true cause of defects through analysis as well as preventive maintenance efforts. Consequently, manufacturing lead time has been reduced by 1/6 and the number of employees required for assembly has been reduced by 1/3.

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
 
Autonomous distributed manufacturing

Autonomous Distributed Manufacturing

Digital data such as the torque value, vibration value, and temperature of the servomotor is absorbed into the controller, and the robot can think for itself how to move.

Production Production
 

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