Evaluation of simple dynamic models and controllers for hydraulic and nozzle pressure in injection molding

Fara, D. Abu; Kamal, Musa R.; Patterson, W I

doi:10.1002/pen.760251109

Cited by 19 publications

(7 citation statements)

References 11 publications

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“…According to the assumption that the gas-injection process can be considered to be a valve-controlled tank charging, Chen and Chao [20] simplified the work of Chao et al [19] that was concerned with the model of the gas pressure dynamics, and proposed a linear transfer function to describe it (1) where denotes the open-loop gain of the process, represents the open-loop time constant, is the desired pressure setting of the regulator valve, and denotes the gas-injection pressure. The parameters in this transfer function can be determined using a system identification technology [21]- [23].…”

Section: Traditional Injection Molding Methodsmentioning

confidence: 99%

Self-Organizing Fuzzy Controller for Gas-Assisted Injection Molding Combination Systems

Lin

Lian

2010

IEEE Trans. Contr. Syst. Technol.

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This study designed and constructed a gas-assisted injection molding system and incorporated it into a traditional injection molding machine. This combined system was referred to as the "gas-assisted injection molding combination system" (GAIMCS). The GAIMCS has complicated and uncertain dynamics, so it is impractical to design model-based controllers for this kind of system. To address this problem, this work developed a model-free selforganizing fuzzy controller (SOFC) to control the GAIMCS and evaluated its control performance. The SOFC has learning ability, which can regulate fuzzy control rules in real time during the control process. The initial fuzzy control rules for the SOFC can be set to zero before the onset of learning. The SOFC achieved better control performance than the fuzzy logic controller or the proportional-integral-derivative controller for high-pressure gas control in the GAIMCS, as confirmed by the experimental results.Index Terms-Fuzzy logic controller, gas-assisted injection molding, self-organizing fuzzy controller.

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Section: Traditional Injection Molding Methodsmentioning

confidence: 99%

Self-Organizing Fuzzy Controller for Gas-Assisted Injection Molding Combination Systems

Lin

Lian

2010

IEEE Trans. Contr. Syst. Technol.

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“…Several research studies have been carried out in this area, especially for the filling phase, by using finite element analysis or other numerical methods (Fara et al, 1985;Hens et al, 1988Hens et al, , 1991aChiu et al, 1991;Gaspervich, 1991;Najmi and Lee, 1991).…”

Section: Modelling Of the Packing Phase Of The Powder Injection Mouldmentioning

confidence: 99%

“…If the geometries of passages and mould are complicated, the change of the total resistance during the process is usually calculated by using a simulation package like C-MOLD. Several research studies have been carried out in this area, especially for the filling phase, by using finite element analysis or other numerical methods (Fara et al, 1985;Hens et al, 1988Hens et al, , 1991aChiu et al, 1991;Gaspervich, 1991;Najmi and Lee, 1991).…”

Section: Modelling Of the Packing Phase Of The Powder Injection Moulding Processmentioning

confidence: 99%

“…As a conclusion, proportional and proportional plus integral control were proposed for injection and packing phases, respectively. Kamal et al (1984) and Fara et al (1985) have investigated the injection moulding dynamics by using a laboratory type, microprocessor-controlled, injection moulding machine. They have carried out two groups of experiments: 1) deterministic tests to determine the behaviours of hydraulic pressure and injection pressure in response to step inputs in servovalve opening, 2) stochastic tests to determine the behaviour of injection pressure in response to pseudo-random binary sequence (PRBS) input signals to the valve.…”

Section: Introductionmentioning

confidence: 99%

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Cavity pressure control of powder injection moulding machines

Yiğit

Ercan

Saritaş³

2004

Transactions of the Institute of Measurement and Control

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In this study, cavity pressure control of a computer controlled powder injection moulding setup driven by an electro-hydraulic servovalve was investigated both theoretically and experimentally. For this purpose, a detailed system model of a powder injection moulding machine was developed and the important parameters that affect the system behaviour were determined by carrying out computer simulations. In light of the simulation results, a closed-loop control system was designed and manufactured. The control system was implemented to a specially designed powder injection moulding setup. Comparisons of the theoretical and experimental results demonstrate that the developed system model describes the dynamic behaviour of the system satisfactorily. The results of experiments show that accurate control of the cavity pressure can be achieved by the proposed control system. A 1 Area of the right-hand side of the hydraulic piston [m 2 ] A 2 Injection piston (screw piston) area [m 2 ] A 3 Area of the left-hand side of the hydraulic piston [m 2 ] A i Cross-sectional area of the ith passage [m 2 ] A c , b Coefficients which describe the feedstock properties b mh Damping coefficent [N.s/m] C ai Circumference of the ith passage [m] C d Discharge coefficent of the servovalve ports C lh Coefficient of leakage around the hydraulic piston [m 3 /s/Pa] C lm Coefficient of leakage around the injection piston [m 3 /s/Pa] d hi Hydraulic diameter of the ith passage at a given time [m] I v Servovalve input current [mA] K v Gain of the servovalve [m/mA] L ei Length of the ith passage at a given time [m] P 2 Injection pressure [Pa] P c Cavity pressure [Pa] P s Supply pressure [Pa] Q m Flow rate into the mould [m 3 /s] R Total resistance [N.s/m 5 ] T mi Feedstock temperature in the ith passage [ C] T 0 Initial temperature of the feedstock [ C] V 1 Oil volume in the right-hand side of the hydraulic cylinder [m 3 ] V 2 Feedstock volume in the injection cylinder [m 3 ] V 3 Oil volume in the left-hand side of the hydraulic cylinder [m 3 ] V fi Volume of the filled part of the ith passage [m 3 ] q h Density of the hydraulic oil [kg/m 3 ] b h Bulk modulus of the hydraulic oil [Pa] b m Bulk modulus of the feedstock [Pa] l i Absolute viscosity of the feedstock flowing through the ith passage [N.s/m 2 ] w Peripheral length of the servovalve ports [m] _ c c i Shear rate in the ith passage [s À1 ] x v Natural frequency of the valve [rad/s] n v Damping coefficient of the second-stage valve x v Servovalve spool position [m]

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“…To solve this issue, system identification is a useful tool commonly used in the modeling polymer injection molding process. 13,14 In principle, the gas-injection process can be treated as a valve-controlled tank charging. The gasinjection pressure dynamics to be controlled can be described by a linear transfer function of the form volume located between the regulator valve and the injection nozzle.…”

Section: Dynamic Model Of Gas-injection Systemmentioning

confidence: 99%

Closed-loop control of gas pressure in the gas-assisted injection molding process

Chen

Chao

1999

Adv. Polym. Technol.

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This paper is concerned with the practical application of closed‐loop control on the gas pressure during the gas‐assisted injection molding process. In principle, the gas‐injection process can be treated as a valve‐controlled tank charging. One of the critical factors for the successful application of the process is the obtaining and maintaining of a desired gas injection pressure within the polymer melt in the mold cavity. Most of the currently available commercial gas‐injection machines operate either in an open‐loop manner or with closed‐loop control, relying upon manual tuning of the associated controllers. This is not only time consuming but also lacking in measurable performance. To improve the controller tuning problem while retaining the currently used controller structure, this study implements a control method which combines system identification and optimal linear quadratic regulator theory into an analytic approach. To demonstrate and verify the proposed method, several experiments were conducted. The results of these experiments show that the approach has excellent potential for designing a control system for regulating gas pressure variation during the gas‐assisted injection molding process. © 1999 John Wiley & Sons, Inc. Adv Polym Techn 18: 137–145, 1999

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Evaluation of simple dynamic models and controllers for hydraulic and nozzle pressure in injection molding

Cited by 19 publications

References 11 publications

Self-Organizing Fuzzy Controller for Gas-Assisted Injection Molding Combination Systems

Self-Organizing Fuzzy Controller for Gas-Assisted Injection Molding Combination Systems

Cavity pressure control of powder injection moulding machines

Closed-loop control of gas pressure in the gas-assisted injection molding process

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