An injection molding study. Part I: Melt and barrel temperature dynamics

Abstract

The dynamics of the key variables in the plastication phase of injection molding were studied using a microcomputer controlled laboratory scale injection molding machine. Interfaces for the measurement and manipulation of suitable variables were developed. An approximate theoretical analysis provided a preliminary understanding of the effect of a step input in heating power on melt and barrel temperatures. Deterministic and stochastic models were derived from experimental data for the melt and the front and rear zone barrel temperatures with heater power manipulation. Experiments were performed for evaluating the effects of back pressure manipulation, heating zone interaction, and process disturbances on the melt and barrel temperatures. Experiments showed that it is desirable to directly control the melt temperature rather than the barrel temperatures.

CFD-based predictive control of melt temperature in plastic injection molding

“…Kamel et al [2] demonstrated interaction between zone melt temperatures. This indicated conductive heat flow between the barrel and nozzle heating zones as well as heat transfer through the barrel casing.…”

“…The models derived for melt temperature control simulations neglected these interactions and were therefore single input single output (SISO). The resulting temperature oscillations during closed loop control with SISO [2][3][4][5] can result in thermal deterioration in the polymer and longer operator setup times on the IMM.…”

“…The heating zone at the rear of the chamber near the hopper, serves to pre-heat the plastic, while the center heating zone ensures the polymer is fully plasticized, and the front zone is controlled to keep the material at the desired melt temperature required for injection [1]. Several researchers [2][3][4] have investigated the use of conventional three-term PID controllers, including Dahlin and Smith predictor control schemes for controlling melt temperature. Deterministic and stochastic models were found by manipulating the heater power applied to the heater zones independently and recording their response.…”

“…The formulation of advanced controllers such as ones derived from the predictive control methodology [5][6][7][8][9][10], as well as conventional approaches [2][3][4], all depend on open-loop testing for model identification. The development of multi-input-multi-output (MIMO) predictive control for melt temperature was conducted by Dubay et al [11,12], incorporating the interactions between the barrel zone temperatures.…”

A generic controller for part surface temperature on a plastic injection molding machine

“…3−6 Control techniques commonly used for melt temperature control are either basic on-off control or proportional, integral and derivative (PID) based methods. 3 However, these control strategies can be unsuitable due to a lack of robustness and adaptability, which are necessary for controlling nonlinear and coupled processes. 7 Dubay 6 implemented a predictive method for controlling melt temperature, resulting in good control performance having zero overshoot.…”