On-line strategic control of liquid composite mould filling process

Citation
Em. Sozer et al., On-line strategic control of liquid composite mould filling process, COMPOS P A, 31(12), 2000, pp. 1383-1394
Citations number
26
Categorie Soggetti
Material Science & Engineering
Journal title
COMPOSITES PART A-APPLIED SCIENCE AND MANUFACTURING
ISSN journal
1359835X → ACNP
Volume
31
Issue
12
Year of publication
2000
Pages
1383 - 1394
Database
ISI
SICI code
1359-835X(2000)31:12<1383:OSCOLC>2.0.ZU;2-F
Abstract
Liquid composite moulding (LCM) processes are used to manufacture high qual ity and complex-shaped fibre reinforced polymeric composite parts in the ae rospace, automotive, marine and civil industries. A thermoset resin is inje cted into a mould cavity filled with a reinforcing fibrous preform. The com posite part is demoulded after the filling is completed and resin has cured . During prototype development, the design engineers may combine their manu facturing experience with simulations to decide which LCM process must be u sed for the selected part. For complicated mould shapes, the manufacturing engineer has to make decisions about injection pressure, flow rate, locatio n of gates and vents, etc, to achieve a high-quality composite part which i s free of dry spots. Inherent variability in the process and the possible e rrors in characterization of material properties, such as fibre volume frac tion and permeability, challenge the manufacturing engineer to reduce the n umber of unacceptable parts. An on-line strategic controller with in situ s ensor data can influence the flow front pattern during mould filling and dr ive the process towards successful completion. Some of these variabilities are considered in off-line mould filling simulations. By analysing the simu lation results, the sensors are placed inside the mould to identify the var iabilities and take corrective action(s) to eliminate voids. Sensor data an d the control actions are cast in the form of a decision tree. Data acquisi tion software collects the in situ sensor data and implements the control a ctions from this decision tree. A case study was included in which various race-tracking and hulk permeability variations can be expected during manuf acturing. The proposed controller is described in detail for this selected case study and its usefulness is verified with experiments. (C) 2000 Publis hed by Elsevier Science Ltd.