Journal ArticleDOI
Online control of the injection molding process based on process variables
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TLDR
In this paper, a pvT-based process control for the injection molding process is presented, where the quality determining process variable cavity pressure can be determined directly and a desired course of cavity pressure in the injection and holding pressure phases can be realized.Abstract:
The conventional control of the injection molding process is based on machine variables, which cannot sufficiently characterize the course of the process. Hence, a system that controls the injection molding process based on process variables has been developed at the Institute of Plastics Processing at RWTH Aachen University during the last years. It controls the quality determining process variable cavity pressure directly and realizes a desired course of cavity pressure in the injection and holding pressure phases. The cavity pressure course in the holding pressure phase is controlled online on the basis of pvT behavior of the processed plastic material. Thus, an optimal course of the process in the pvT diagram can be guaranteed and the quality constancy of the molded parts can be clearly increased. Using the pvT-based process control, the effect of varying mold and melt temperatures on the molded part weight can be decreased by about 90% compared with the conventional process control. © 2009 Wiley Periodicals, Inc. Adv Polym Techn 28:65–76, 2009; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/adv.20153read more
Citations
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Journal ArticleDOI
Monitoring and dynamic control of quality stability for injection molding process
TL;DR: In this paper, a quality prediction model based on polymer melt properties is established to monitor product weight variation online, and a pressure integral based on the prediction model is proposed as an effective process variable to predict product weight variations.
Journal ArticleDOI
A Novel Process Control Methodology Based on the PVT Behavior of Polymer for Injection Molding
Jian Wang,Qianchao Mao +1 more
TL;DR: In this article, a process control methodology for injection molding is presented based on the PVT (pressure volume temperature) behavior of polymer, which can be used to accommodate the product weight change due to variation of the melt or mold temperature.
Journal ArticleDOI
Online quality monitoring of molten resin in injection molding
TL;DR: In this paper, the authors proposed a method for evaluating the melt quality of the molten resin by means of three pressure sensors installed at the nozzle, runner and mold cavity, respectively.
Book ChapterDOI
PVT Properties of Polymers for Injection Molding
TL;DR: In this paper, the authors show the typical PVT diagrams of an amorphous and semi-crystalline polymers and show that the specific volume increases with the temperature increasing.
Book ChapterDOI
The Micro Injection Moulding Process for Polymeric Components Manufacturing
TL;DR: Examples of technologies to be investigated either individually or in combination are technologies for director rapid manufacturing, energy assisted technologies, microreplication technologies, qualification and inspection methods, functional characterisation methods and integration of "easy and fast" on-line control systems.
References
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MonographDOI
Parallel Distributed Processing: Explorations in the Microstructure of Cognition: Foundations
Journal ArticleDOI
Generalized predictive control—Part I. The basic algorithm
TL;DR: A novel method—generalized predictive control or GPC—is developed which is shown by simulation studies to be superior to accepted techniques such as generalized minimum-variance and pole-placement and to be a contender for general self-tuning applications.
Journal ArticleDOI
Cavity pressure dynamics and self-tuning control for filling and packing phases of thermoplastics injection molding
TL;DR: In this paper, a self-tuning control system was designed and tested for a wide range of conditions and the transition from filling to packing was best detected by the change in the derivative of cavity pressure.
Journal ArticleDOI
Profiling of injection velocity for uniform mold filling
Xi Chen,Furong Gao +1 more
TL;DR: Based on a neural network model developed for estimating the melt flow length from online measurable variables, Wang et al. as discussed by the authors transformed the profiling problem into an optimization to minimize the difference between the predicted Melt flow length and a given ramp.
Journal ArticleDOI
Automation of online quality control in injection moulding
TL;DR: In this article, an empirical mathematical model of the molding properties allows their calculation on the basis of the data acquired at the end of each production cycle and the data obtained with the new neural algorithm show better results ahtn all algorithms applied so far.
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