Out-of-Mold Sensor-Based Process Parameter Optimization and Adaptive Process Quality Control for Hot Runner...

Area of Science:

• Manufacturing Engineering
• Polymer Science
• Process Control

Background:

• Injection molding is complex, especially for thin-walled parts requiring high-speed processes.
• Process variability impacts product quality and long-term production stability.
• External factors significantly influence the nonlinear injection molding procedure.

Purpose of the Study:

• To establish appropriate process parameters for stable quality in long-term injection molding production.
• To develop and implement an adaptive process control system for thin-walled parts.
• To minimize product weight variation using sensor data and optimized parameters.

Main Methods:

• Utilized a hot runner mold with a thin wall equipped with nozzle pressure and tie-bar strain sensors.
• Collected data on nozzle peak pressure, peak pressure timing, viscosity index, and clamping force difference.
• Constructed a standardized parameter optimization process including injection speed, V/P switchover, packing, and clamping force.

Main Results:

• Optimized process parameters were applied to adaptive process control experiments.
• The developed control system, operated by a micro-controller unit (MCU), effectively stabilized product weight.
• Achieved a product weight variation of 0.677% and a standard deviation of 0.0178 g.

Conclusions:

• Adaptive process control is effective in stabilizing product weight during high-speed injection molding.
• Sensor integration and parameter optimization are crucial for consistent quality in thin-walled part production.
• The developed MCU-operated control system demonstrates practical application for quality assurance in manufacturing.