OverView
AI predicts signs of trouble.
System details
The system collects data such as temperature, pressure, and camera images from the molding line, and the AI constantly checks for signs of impending defects.
When the warning signs intensify, notifications are sent to on-site terminals and chat rooms, and suggestions for "what to do next," such as adjusting speed and temperature or performing mold maintenance, are made.
assignment
Conditions are unstable immediately after launch or when switching product lines, and it's easy to overlook warning signs by relying solely on experience.
Scattered data delays root cause identification, and fixed thresholds fail to account for seasonal and material variations, leading to over-testing.
Implementation effects
By being able to adjust the speed and temperature during the initial stages, it is possible to reduce the occurrence of discharge defects and rework.
Furthermore, stable yield rates during the initial setup phase can be expected to reduce waste costs and overtime hours.
