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Injection velocity is one of the key parameters in the injection molding process that has significant effect on part quality, influencing common problems, such as flashing and short shots. Different products require specific molding conditions, including mold and melt temperatures, velocity profiles, and polymers, making the injection velocity dynamics vary significantly and difficult for high precision velocity control. Two predictive controllers were developed to control the screw injection velocity. The first approach uses a position sensor as feedback and a simplified predictive controller to track an injection velocity setpoint profile. The controller was developed and implemented utilizing single‐step change and multistep change open loop tests. The second strategy uses a multimodel dynamic matrix predictive controller to overcome the nonlinear characteristics of the injection velocity dynamics as the mold is being filled. Velocity feedback is provided by high speed processing of the position analog signal. This approach utilizes several open loop injection velocity profiles to generate corresponding dynamic matrices for the controller. As a result, this controller is modified or retuned automatically when setpoint changes in injection velocity occur, as well as when using different polymers and molds. The close loop results for both simulations and real time control have demonstrated that the two predictive controllers provided good setpoint tracking performance for wide ranging position and velocity profiles. POLYM. ENG. SCI., 47:390–399, 2007. © 2007 Society of Plastics Engineers.

Cavity pressure control during filling, packing, and cooling phases is imperative for maintaining product quality in injection molding process. This paper presents the design and implementation of a strategy to control cavity pressure profile during the cooling phase. In order to do this, a controlled variable parameter was defined to be the time constant τ of the pressure profile. This parameter can be used effectively to control the shape of the cavity pressure over the cooling cycle. The coolant flow rate through the mold was used as the manipulated variable. A predictive control system was designed and implemented successfully to allow monitoring and control of τ at several setpoints τ sp resulting in good and effective cavity pressure control.

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In this study, the optimization of recast layer thickness and surface roughness (SR) simultaneously in a Wire-EDM process by using Taguchi method with fuzzy logic has been applied. The Wire-EDM process parameters (arc on time, on time, open voltage, off time and servo voltage) were optimized with considerations of multiple performance characteristics, i.e., recast layer thickness and SR. Based on the Taguchi method, an L18 mixed-orthogonal array table was chosen for the experiments. Fuzzy reasoning of the multiple performance characteristics has been developed based on fuzzy logic, which then converted into a fuzzy reasoning grade or FRG. As a result, the optimization of complicated multiple performance characteristics was transformed into the optimization of single response performance index. Experimental results have shown that machining performance characteristics of Wire-EDM process can be improved effectively through the combination of Taguchi method and fuzzy logic.