We are thrilled to introduce the AI technology "Automatic Condition Adjustment During Mass Production", which captured significant attention at the recent Nagoya Plastics Industry Exhibition, held from November 20th to 22nd, 2024. When the target values are set, the AI will automatically adjust the molding conditions, that helps not only to stabilize quality and improve work efficiency, but also minimize material waste caused by molding defects and labor-costs related to molding condition adjustment.
*This technology is currently being introduced for reference purposes only. The release date and availability in different regions are to be determined.
-Although the need for recycling has increased in recent years, keeping the same quality when using recycled materials is difficult because of the thermal history effects.
-Changes of resin rods*¹ or environmental conditions at production site can cause the logging data*² drift phenomenon, which leads to mass disposal of molded products and necessary of molding conditions adjustment by machine operators.
-Changes to molding conditions have previously relied on the experience and intuition of skilled technicians, but the number of skilled technicians is decreasing due to retirement, etc. As a result, conditions are increasingly being set by workers with little experience. It can take a long time to set conditions that yield high-quality products for them, or they may end up setting inappropriate conditions, leading to increase of defects.
*¹Resin rod: A rod-shaped product made from a polymeric resin as a base material.
*² Drift phenomenon: A phenomenon of changes in molding quality over time, which is believed to be caused by factors such as air temperature, cooling water temperature, resin lot variations, etc.
Data on the molding process, such as temperature, pressure, and speed, is collected in real time and sent to a server where it has been analyzing by AI. Once a target value is set, any fluctuations or abnormalities in molding quality are detected based on information from the previous shot, and the subsequent molding conditions are automatically adjusted accordingly. After automatic adjustments, the molding quality data will be continuously monitored, and further adjustments will be made as needed.
Molding data Example: Peak filling pressure is set to 113MPa.
The VP switching position is automatically adjusted within the range of ±0.5.
The molding quality is automatically regulated to consistently approach the target value, thereby preventing the drift phenomenon*². In addition, by shifting the average value through post-shot correction, it is possible to determine which condition settings should be changed, resolving the mean shift problem*³ and stabilizing quality while reducing the occurrence of defective products.
*³Mean shift problem: The occurrence where the average value of a data distribution changes over time or due to environmental variations.
LCL (Lower Control Limit): The lower limit at which a process is considered to be operating normally.
USL (Upper Specification Limit): The upper limit of the acceptable quality of a product.
Automatic adjustments reduce the effort required to move around a large factory and minimize the need to enter and exit clean rooms, thereby improving work efficiency.
Reducing defects and improving work efficiency minimize overall production costs, including material and labor costs.
If any abnormality in molding quality is detected, adjustments are made immediately, enabling early resolution of the issue.
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If automatic adjustments can be utilized during mass production, it will be possible to reduce material costs, reduce the environmental impact by using recycled materials, and reduce labor costs.
This technology can be observed at the Technology Center of the Chiba Factory. If you are interested, please contact our sales representative or use our online inquiry form.