Paper number 853
|USE OF SENSORS AND SIMULATIONS TO MOVE TOWARDS AUTOMATION OF THE RESIN TRANSFER MOLDING PROCESS|
Suresh G. Advani, E. Murat Sozer, Simon Bickerton, Hubert C. Stadtfeld, and Karl V. Steiner
Department of Mechanical Engineering and Center for Composite Materials
University of Delaware, Newark, DE 19716, U.S.A.
|Summary||Resin Transfer Molding (RTM) has the potential to manufacture high-quality, geometrically complex composite parts. Inherent variability in the process can cause problems if moderately complex parts are to be produced on a very consistent basis. On-line control of mold filling provides an opportunity to manipulate the process by changing the inlet gate pressure or flow rate and/or by adding or deleting new injection locations, based upon feed back from relevant sensor data. This methodology will bring RTM a step closer towards process automation and lead to cost avoidance by reducing prototype development cost, rejection rate, and trial and error manufacturing practice. For active control of mold filling to be effective, the resin injection system employed should be versatile. This paper explores the feasibility of such intelligent resin injection systems, and presents results obtained by using an injection system with three individually controllable lines which provides continuous feed back control of either injection flow rate or injection pressure. Several flow visualization studies are presented, the goal being to demonstrate the advantages of RTM filling with active control. Reductions can be made in size of dry spots and in void content, time to fill, and also in the amount of resin wasted. Numerical simulation of the mold filling process is a valuable tool for the design of mold filling strategies. Simulations are used to identify the parameters to be sensed and those to be actuated. The main parameters to be sensed are pressure and the arrival of the resin. The actuators that can be invoked are location of the injection gates, vents, inlet pressure and flow rates at the injection location. Strategic controllers that describe the decision process based on sensor feedback are developed using the simulations. The sensor signal travels to a LabView controller which in turn implements the decisions on a lab-scale RTM mold by invoking the actuators which will switch gates/vents or change pressure/flow rates. An experimental case study is conducted to demonstrate the methodology.
||Keywords|| resin transfer molding, mold filling simulation, permeability, flow sensors, model based control, on-line control, automation, composites, decision-tree.
Theme : Smart Materials and Smart Manufacturing
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