Dynamics and control of pressure in the injection molding of thermoplastics

Kamal, Musa R.; Patterson, W I; Conley, Nancy; Fara, D. Abu; Lohfink, G. W.

doi:10.1002/pen.760271809

Cited by 55 publications

(31 citation statements)

References 3 publications

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“…The merits of these machines include superior control accuracy, larger power output, and higher response speed; the system has been widely used in the injection molding machine for precision position control. Kamal et al [40] and Abu Fara [41] have developed cavity pressure models for the cavity pressure history of an injection molding process. A deterministic (step) test was implemented in the injection molding machines with electrohydraulic systems, and pressure sensors were installed at different locations in the mold cavity of a rectangular plate.…”

Section: Cavity Pressurementioning

confidence: 99%

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Correlation between runner pressure and cavity pressure within injection mold

Tsai

Lan

2015

Int J Adv Manuf Technol

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Cavity pressure in the injection molding process is closely related to the quality of the molded products and is used for process monitoring and control to upgrade the quality of molded products. However, the sensor installed inside the cavity makes the molded product of the cavity defective, reducing productivity. In view of this, this study investigates the correlation between melt pressure and cavity pressure in different runner positions and determines the appropriate runner position, where the runner pressure can represent the cavity pressure, in order to increase productivity. First, the Taguchi method is used to obtain the optimal parameter combination of injection molding, and then, the experiment is conducted based on this condition in order to discuss the difference between runner and cavity pressure history profiles. According to the experimental results, the quality of molded products can be monitored and controlled by installing sensors at different runner positions, and the maximum value of the cavity pressure profile varies with the runner position. When the distance between the top of the pressure sensor mounted in the secondary runner and the outside diameter of the runner is greater than the maximum thickness of the molded product, the obtained pressure history profile approximates to that inside the cavity. In other words, the runner pressure can represent the cavity pressure. Mold temperature significantly influences the runner pressure history profile and form accuracy (contour precision) of the lens during the injection molding process, which can be used as a process monitoring and control parameter. In addition, the cavity pressure profile at the cooling stage is closely related to the form accuracy of the lens and is the key to determining process monitoring and control parameter.

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Section: Cavity Pressurementioning

confidence: 99%

“…In comparison to the first-order model, the second-order model has better accuracy; however, the difference is slight. Therefore, the simple first-order plus a time delay model superimposed on a constantly increasing (ramp) pressure component of the form is reasonably expressed, as follows [40,41]:…”

Section: Cavity Pressurementioning

confidence: 99%

Correlation between runner pressure and cavity pressure within injection mold

Tsai

Lan

2015

Int J Adv Manuf Technol

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“…For this reason, it has been often used in past research [9,10]. Through mathematical simulation and experimental study, Woll and Cooper [3,11] used cavity pressure as the basis of a closedloop quality control strategy for the injection molding process.…”

Section: Introductionmentioning

confidence: 99%

Development of an in-process, gap-caused flash monitoring system in injection molding processes

Zhe

Chen

Zhu

2005

Int J Adv Manuf Technol

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This paper describes the development of an in-process, gap-caused flash monitoring (IGFM) system for injectionmolding machines. An accelerometer sensor was integrated in the proposed IGFM system to detect the difference of the vibration signals between flash and non-flash products in the last period of the injection molding filling stage. Through an approach suggested by the statistical process control mechanism, the threshold in the decision-making mechanism of this system was established. That threshold then was used by the IGFM system to determine if flash occurred in the molded products when the machine was running. An experiment was designed and performed by manipulating the variables of gap and nogap. The experimental testing results indicated that this system could successfully monitor injection-molded products' flash status with approximately 94.7% accuracy while the machine was in process.

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“…Kamal et al [6,7] derived the transfer functions for the injection pressure, nozzle pressure, and cavity pressure during the filling phase. Controllers [8,9] were then designed based upon a linearised dynamic model. Paul and Shankar [10,11] proposed a dynamic model for the filling phase by using the state space approach.…”

Section: Introductionmentioning

confidence: 99%

Application of Neural Networks in Injection Moulding Process Control

Huang

Lee

2003

The International Journal of Advanced Manufacturing Technology

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In order to produce precise injection moulding products, a closed-loop controller is employed instead of the open-loop control of a traditional injection moulding machine for monitoring the filling and post-filling phases of the injection processes.Since the injection moulding system has complicated and variable dynamics, the classical control theory is difficult to implement for the precise injection moulding processes. Here, two intelligent neural network control strategies are employed to adjust the injection speed of the filling phase and control the nozzle pressure of the post-filling phase. Since the neural controller has learning ability to track the variation of the injection processes, this control strategy has the advantages of adaptivity and robustness for general purpose application to an injection moulding machine. The experimental results show that this controller has good performance in the actual injection moulding processes.

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Dynamics and control of pressure in the injection molding of thermoplastics

Cited by 55 publications

References 3 publications

Correlation between runner pressure and cavity pressure within injection mold

Correlation between runner pressure and cavity pressure within injection mold

Development of an in-process, gap-caused flash monitoring system in injection molding processes

Application of Neural Networks in Injection Moulding Process Control

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