Comprehensive Online Control Strategies for Plastic Injection Molding Process

Abstract

This study proposes an effective thermal control for plastic injection molding (polymer: Santoprene 821145 with density of 790 kg/m3, injection pressure: 1400 psi (9,652,660 Pa)) in a laminated die. For this purpose, a comprehensive control strategy is provided to cover various themes. First, a new method for determining the optimal sensor locations as a prerequisite step for modeling and controller design is introduced. Second, system identification through offline and online training with finite element analysis and neural network techniques are used to develop an accurate model by incorporating uncertain dynamics of the laminated die. Third, an additive feedforward control by adding direct adaptive inverse control to selfadaptive PID is developed for temperature control of cavity wall (cavity size: 52.9 أ— 32.07 أ— 16.03 mm). A verification of designed controller's performance demonstrates that the proposed strategy provides accurate online temperature tracking and faster response under thermal dynamics with various cycletimes in the injection mold process.