Control of flow in resin transfer molding with real-time preform permeability estimation

2002 ◽  
Vol 23 (6) ◽  
pp. 1087-1110 ◽  
Author(s):  
D. R. Nielsen ◽  
R. Pitchumani
Keyword(s):  
Real Time ◽  
Resin Transfer Molding ◽  
Transfer Molding ◽  
Permeability Estimation ◽  
Control Of Flow

Neural Network Based Control of Preform Permeation in Resin Transfer Molding Processes With Real-Time Permeability Estimation

2000 ◽  
Author(s):  
David Nielsen ◽  
Ranga Pitchumani
Keyword(s):  
Neural Network ◽  
Real Time ◽  
Resin Transfer Molding ◽  
Local Pressure ◽  
Transfer Molding ◽  
Model Based ◽  
Rtm Process ◽  
Virtual Sensing ◽  
Intelligent Model ◽  
Injection Pressures

Abstract Variabilities in the preform structure in situ in the mold are an acknowledged challenge to effective permeation control in the Resin Transfer Molding (RTM) process. An intelligent model-based controller is developed which utilizes real-time virtual sensing of the permeability to derive optimal decisions on controlling the injection pressures at the mold inlet ports so as to track a desired flowfront progression during resin permeation. This model-based optimal controller employs a neural network-based predictor that models the flowfront progression, and a simulated annealing-based optimizer that optimizes the injection pressures used during actual control. Preform permeability is virtually sensed in real-time, based on the flowfront velocities and local pressure gradient estimations along the flowfront. Results are presented which illustrate the ability of the controller in accurately steering the flowfront for various fill scenarios and preform geometries.

scholarly journals Embedded Based Real-Time Monitoring in the High-Pressure Resin Transfer Molding Process for CFRP

2019 ◽  
Vol 9 (9) ◽  
pp. 1795 ◽  
Author(s):  
Kim ◽  
Kim ◽  
Hwang ◽  
Kim
Keyword(s):  
High Pressure ◽  
Real Time ◽  
Process Monitoring ◽  
High Speed ◽  
Resin Transfer Molding ◽  
Time Signal ◽  
Process Variables ◽  
Molding Process ◽  
Transfer Molding ◽  
Rtm Process

Carbon Fiber Reinforced Plastics (CFRP) is a material developed for its high strength and light weight in a broad variety of industries including aerospace, automotive, and leisure. Due to the rapid molding cycle time, high-pressure resin transfer molding (HP-RTM) processes are prone to molding defects and susceptible to various process variables such as the resin injection rate, pressure and temperature in the mold, vacuum, end-gap, pressing force, and binder. In recent years, process monitoring technology with various sensors has been applied to stabilize the HP-RTM process and control process variables. The field-programmable gate array (FPGA) based embedded monitoring system proposed in this study enabled high-speed real-time signal processing with multiple sensors, namely pressure, temperature, and linear variable differential transformer (LVDT), and proved feasibility in the field. In the HP-RTM process, the impregnation and curing of the resin were predicted from the cavity pressure and temperature variations during the injection and curing stages. In addition, the thickness of the CFRP specimen was deduced from the change in the end-gap through the detection of the LVDT signal. Therefore, the causes of molding defects were analyzed through process monitoring and the influence of molding defects on the molding quality of CFRP was investigated.

A Robotic System for Real-Time Resin Flow Modification During Vacuum-Assisted Resin Transfer Molding

2006 ◽  
Author(s):  
Scott Kasprzak ◽  
John Nasr ◽  
Michael Fuqua ◽  
Jim Glancey
Keyword(s):  
Real Time ◽  
Vacuum Chamber ◽  
Control Strategies ◽  
Resin Transfer Molding ◽  
Element Model ◽  
Robotic System ◽  
Resin Flow ◽  
Transfer Molding ◽  
Flow Modification ◽  
Molded Part

To complement existing resin flow control strategies currently under development for Vacuum-Assisted Resin Transfer Molding (VARTM), and to provide the ability to react to unexpected changes in resin behavior during injection, a new technique for resin flow manipulation has been investigated. This approach consists of a semi-cylindrical shaped vacuum chamber placed on a mold which, when evacuated, increases the permeability of the region under the chamber by lifting the bag atop the mold. A finite element model has been developed to predict the resin flow within the mold while using the external chamber. Laboratory testing has shown significant modification in resin flow with reduced injection time. Using the external chamber, a robotic system has been prototyped that identifies dry regions forming during injection via computer vision, deploys the vacuum chamber over the mold with a robotic arm, and actuates the chamber in order to modify and correct the resin flow within the mold. Test results using lab-scale molds with large variations in preform permeabilities indicate that the robotic system can correct and/or modify the resin flow within a mold in real time, thus eliminating dry, unimpregnated regions. This computer-based method has the potential to significantly enhance molded part quality and consistency by eliminating resin starved regions within a molded composite part.

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