Cavity temperature control in plastic injection molding

Dubay, Rickey; Pramujati, Bambang; Hernandez, J. M.

doi:10.1109/icma.2005.1626673

Cited by 6 publications

(9 citation statements)

References 9 publications

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“…Input conditions of FEA for NARX modeling. From the figure, it can be seen that for data gathering, each flow rate (input) with a given cycle-time keeps constant until a corresponding steady state of temperature at the node (output) is reached over many cycles [3]. Additional data sets for modeling at the same node (Mo 484) were generated by using the same flow rate ranges (0, 1, 3, 4, 5, 6, 8gpm) with each different cycle-time (i.e., 61, 71, 81sec).…”

Section: Mo676 Mo771mentioning

confidence: 99%

“…A PI [3] and PID algorithms [1] were applied to manage the cavity temperature on a plastic injection moulding and highpressure die-casting, respectively. To improve limitation of a PID control in presence of uncertain or nonlinear dynamics, several studies have been undertaken.…”

Section: Introductionmentioning

confidence: 99%

“…Hot polymer injected into the mould cavity is cooled to the demoulding temperature by heat transfer to coolant (water) through the conformal cooling channel in close proximity to the cavity. Since the dominant heat transfer mechanism for the injection moulding process is the convection by the coolant [3,12], the flow rate and temperature of the coolant are chosen as the controllable process parameter to control the temperature distribution of the die. FE simulations for thermal dynamic analysis of the die are carried out based on this model.…”

Section: Introductionmentioning

confidence: 99%

“…However, the rapid change of the temperature during the cycle makes it difficult to use this temperature profile as a set-point and thus alternative variable is required as an output. Instead, cycle average temperature [3,4,15] defined in Eq. (2) serves as an output.…”

Section: -Introduction Of Narxmentioning

confidence: 99%

See 3 more Smart Citations

Thermal management in laminated die system

Seo

Khajepour

Huissoon

2014

Int. J. Control Autom. Syst.

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Abstract:The thermal control of a die is crucial for the development of high efficiency injection moulds. For an effective thermal management, this research provides a strategy to identify a thermal dynamic model and to design a controller. The neural network techniques and finite element analysis enable modeling to deal with various cycle-times for moulding process and uncertain dynamics of a die. Based on the system identification which is experimentally validated using a real system, controllers are designed using fuzzy-logic and self-tuning PID methods with backpropagation and radial basis function neural networks to tune control parameters. Through a comparative study, each controller's performance is verified in terms of response time and tracking accuracy under different moulding processes with multiple cycle-times.

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Section: Mo676 Mo771mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: -Introduction Of Narxmentioning

confidence: 99%

See 2 more Smart Citations

Thermal management in laminated die system

Seo

Khajepour

Huissoon

2014

Int. J. Control Autom. Syst.

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“…Dubay et al [3] applied a PI controller to control coolant flow rate and manage the cavity temperature on a plastic injection molding machine for achieving an effective cooling system. In the study by Bishenden and Bhola [1], a proportional integral differ ential (PID) algorithm maintains the die cavity temperature within a preset range during the casting process, improving production through improved response time.…”

Section: Introductionmentioning

confidence: 99%

Comprehensive Online Control Strategies for Plastic Injection Molding Process

Seo

Khajepour

Huissoon

2014

Journal of Manufacturing Science and Engineering

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This study proposes an effective thermal control for plastic injection molding (polymer: Santoprene 8211-45 with density of790kg/m3, injection pressure: 1400psi (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 o f the laminated die. Third, an additive feedforward control by adding direct adaptive inverse control to self-adaptive PID is developed for temperature control of cav ity wall (cavity size: 52.9 x 32.07 x 16.03 mm). A verification of designed controller's performance demonstrates that the proposed strategy provides accurate online tempera ture tracking and faster response under thermal dynamics with various cycle-times in the injection mold process.

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Temperature control of injection molding. Part I: Modeling and identification

Diduch

Dubay

2004

Polymer Engineering & Sci

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This paper develops a mathematical model for the dynamics of a plastic injection molding machine (IMM) that may be used for the design of a temperature-control system. The research in this paper is novel in comparison to others since the derived models explicitly include the effects of zone interaction and backpressure, and do not lump these into an arbitrary disturbance signal. A series of experiments were conducted on a 150-tonne IMM to identify the parameters of the proposed model using measurements of zone temperatures, percentage heater input, backpressure and screw speed. The identified model was validated using a series of blind tests that compared the model output with the measured barrel temperatures of the IMM.

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Cavity temperature control in plastic injection molding

Cited by 6 publications

References 9 publications

Thermal management in laminated die system

Thermal management in laminated die system

Comprehensive Online Control Strategies for Plastic Injection Molding Process

Temperature control of injection molding. Part I: Modeling and identification

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