NSF/DOE/APC Workshop - Future of Modeling in Composites Molding Processes June 9 and 10, 2004 Glancey – SCA Group 9 and 10 June 2004 Automation and Control For Liquid Injection Molding Systems Progress and Future Challenges James Glancey University of Delaware NSF/DOE/APC Workshop Future of Modeling in Composites Molding Processes Design and Optimization Group June 9-10, 2004

NSF/DOE/APC Workshop - Future of Modeling in Composites Molding Processes Glancey – SCA Group 9 and 10 June 2004 Presentation Overview Potential Benefits of Automation and Control for LCM Systems Benchmarks for Automation and Controls in Other Industries Examples of Recent Developments Localized Heating Smart Injection Line and Real Time Adaptive Control Developments Short and Long Term Automation Strategies for LCM

NSF/DOE/APC Workshop - Future of Modeling in Composites Molding Processes Glancey – SCA Group 9 and 10 June 2004 Key Issues to being Addressed in LCM Manufacturing Quality Need exists to continue to improve individual part quality Dry spots/voids, especially with complex geometries Cost Abundant injection lines Extended injection times Trial and error approach for making parts Overcoming “Manual Manufacturing Processes”

NSF/DOE/APC Workshop - Future of Modeling in Composites Molding Processes Glancey – SCA Group 9 and 10 June 2004 Potential Benefits of Automation Improve controllability as a means to automate Reduce manual operations Improve part quality, reduce resin waste, and decrease injection for VARTM Requirements: Versatile Simple Low cost System Integration Value

NSF/DOE/APC Workshop - Future of Modeling in Composites Molding Processes Glancey – SCA Group 9 and 10 June 2004 Automated Manufacturing Benchmarks 3) Injection Molding Station1) Flexible Manufacturing 2) CNC Machining

NSF/DOE/APC Workshop - Future of Modeling in Composites Molding Processes Glancey – SCA Group 9 and 10 June 2004 Automation of Processes

NSF/DOE/APC Workshop - Future of Modeling in Composites Molding Processes Glancey – SCA Group 9 and 10 June 2004 General Characteristics of Production Methods

NSF/DOE/APC Workshop - Future of Modeling in Composites Molding Processes Glancey – SCA Group 9 and 10 June 2004 Typical Annual Production

NSF/DOE/APC Workshop - Future of Modeling in Composites Molding Processes Glancey – SCA Group 9 and 10 June 2004 Example: Defect Reduction In Casting via Automation Common Casting Defects

NSF/DOE/APC Workshop - Future of Modeling in Composites Molding Processes Glancey – SCA Group 9 and 10 June 2004 Example of Automation in Composites- Pultrusion Highly Automated High Production Rates Consistent, High Quality Parts Technically and Economically Viable

NSF/DOE/APC Workshop - Future of Modeling in Composites Molding Processes Glancey – SCA Group 9 and 10 June 2004 Integrating Part Quality into the Manufacturing System Automated and Semi-Automated Quality Assessments On-Line Part Characterization and Statistical Quality Control

NSF/DOE/APC Workshop - Future of Modeling in Composites Molding Processes Glancey – SCA Group 9 and 10 June 2004 Current Work In VARTM No Control Controlled w/Segmented Line High Permeability Region High Permeability Region Controlling Resin Flow within the Mold - Critical for Automation - Localized Heating - Segmented Injection Line - Flow Sensing - Real-Time Simulations - Closed-Loop Control

NSF/DOE/APC Workshop - Future of Modeling in Composites Molding Processes Glancey – SCA Group 9 and 10 June 2004 Controller Design PID Process reu y Traditional Form: Adaptive Form: Process Model State Calculation State Controller y u r e

NSF/DOE/APC Workshop - Future of Modeling in Composites Molding Processes Glancey – SCA Group 9 and 10 June 2004 Potential Strategies for LCM Automation Short-term – Resin Flow Control Continue to develop actuation methods (Smart Injection Line, Localized Heating, etc) Develop Other Techniques Work towards true closed-loop control of the flow Long-Term – True System Automation Integrate, Exploit and Adapt Existing Science and Technology Computer Controls, Sensors, Modern Control Theory - In Particular Stochastic Methods System Integration Integration of Quality Control into the Manufacturing Process