Self-Configurable Production of CFRP Aerospace Components Based on Multi- Criteria Structural Optimization

Transcription

1 High Performance Production of CFRP-Structures Self-Configurable Production of CFRP Aerospace Components Based on Multi- Criteria Structural Optimization Dr.-Ing. C. Schmidt, P. Weber, K. Völtzer, O. Deniz CFK-Valley Convention 2015 June 16 th 2015 Stade Stand: 06/2015 IFW / PUK / IFL Seite 1

2 Agenda Industry 4.0 and Challenges Approach of - -Development Process - Multi Criteria Optimization - Reconfigurable Automated Fiber Placement System - Self-Parametrized Process Monitoring Conclusion Scm IFW / PUK / IFL Seite 2

3 I 4.0 and Challenges Individual Customer Needs Customized Products Cost-efficient and with high Quality is marked by a strong product individualization in terms of the conditions of a highly flexiblelized large-volume production.* Process reliability from the first component Systematic data collection and usage alongside the value chain Knowledge-based configuration of production systems *) Quelle: BMBF Scm IFW / PUK / IFL Seite 3

4 Research Project Stade CFK Nord Hannover Leibniz Universität Hannover Braunschweig TU Braunschweig Clausthal-Zellerfeld TU Clausthal Aircraft Design & Simulation Materials & Processes Production Technology & Automation IFW / PUK / IFL Seite 4

5 -Development Process Conventional Structure development Process planning Planning Conceptual Embodiment Detail Rough planning Detailed planning Manufacturing Structure development Planning Conceptual Preliminary Embodiment Rough planning Vorgehen beim Entwickeln und Konstruieren nach VDI 2221 Specific Process planning Detailed planning Detail Manufacturing nach VDI 2221 Continuous information exchange from structural to manufacturing Self-configuration of production systems and its process monitoring by the structural development Feedback from manufacturing constraints and experiences Scm IFW / PUK / IFL Seite 5

6 -Development Process Production-integrated optimization of CFRPfuselage structures Structure development Planning Conceptual Preliminary Embodiment Rough planning Specific Detailed planning Detail Manufacturing Process planning nach VDI 2221 Automated production of CFRP-structures by a modular reconfigurable fiber placement system Simulation based online-process monitoring in fiber placement Scm IFW / PUK / IFL Seite 6

7 Specific Design Multidisciplinary Structure Design and Optimization Initial Topology Manufacturing Analysis and Mapping Deviations in FE Model Automated Model Generation Definition of the objectives and constraints Optional: Response Surfaces of Manufacturability Evolution of Structural Response Multidisciplinary Optimization with Evolutionary Strategies Optimized Design Dz IFW / PUK / IFL Seite 7

8 Initial Topology the -Design Local Stiffener Diagonal Stiffeners Foam Cores Intersections Skin Scm IFW / PUK / IFL Seite 8

9 Optimization of the Structure Design Parameter within model generator Window Topology Window Frame Lay-up Frame Window Stiffener Profile Stringer Window Intersection Skin Stiffener Geometry Design scope > 100 Parameter Different profile topology possible Material Number of plies and corresponding orientations are optimized simultaneously Dz IFW / PUK / IFL Seite 9

10 Manufacturing Analysis Considering manufacturing influences Maximum slope 0,154 Laying width b max = 26 mm h max,= 4 mm Tows Segmented Roller d max = 70 mm Maximum curvature 0,028 1/mm Dz IFW / PUK / IFL Seite 10

11 Manufacturing Analysis Validation of gap estimation Without manufacturing restrictions d max =1.2 mm With manufacturing restrictions d max =1.03 mm 45 mm d max = Dz IFW / PUK / IFL Seite 11

12 Multidisciplinary Structure Optimization Results 200% 150% 163,9% 100% 97,7% 79,0% 112,0% 99,0% 100,0% 70,0% 50% 57,0% 0% ~ 2,3 % lighter ~ 12 % larger window Increased manufacturability Minimized production deviations Constraints Reference Manufacturability Dz IFW / PUK / IFL Seite 12

13 -Development Process Production-integrated optimization of CFRPfuselage structures Structure development Planning Conceptual Preliminary Embodiment Rough planning Specific Detailed planning Detail Manufacturing Process planning nach VDI 2221 Automated production of CFRP-structures by a modular reconfigurable fiber placement system Simulation based online-process monitoring in fiber placement Scm IFW / PUK / IFL Seite 13

14 Modular Automated Fiber Placement System Material storage Feeding unit Cutting unit Compaction unit Heating unit Monitoring Wb IFW / PUK / IFL Seite 14

15 Controlling the Lay-up Process Parameters for individual process adaption F c Lay-up head: 4 x ¼ Tows by segmented, pressure controlled compaction device Segment lift s = 4 mm Individual tow-feed with adjustable tension F σ Individual tow cutting Minimum tow length l min = 67 mm Variable compaction force F c Controlled IR-heater W s p1 p4 s F σ l min Roboter: Kuka Quantec KR300 R2500 ULTRA KR C4 robot controller with Kuka CNC Kuka ForceTorqueControl 3.0 Load 300 kg Maximum working space 2500 mm Repeatability: <+/- 0,06 mm Wb IFW / PUK / IFL Seite 15

16 F c Compaction Force Monitoring the Lay-up Process Concept of thermal monitoring ROI V f Speed DT 32 ºC Tow 4 T p 4 = T p 3 Q T p 4 < T p 3 4 T p Temperatur Analysis of temperature differences T p 4 T p 3 Edge and failure detection within the Region of Interest (ROI) Edge detection with dynamic threshold (DT) Resolution 0,125 mm Pixel Detectability depending on process parameters (V f, F c, T p ) Vö IFW / PUK / IFL Seite 16

17 80 cm Position [Frames] Monitoring the Lay-up Process Detection of Edges Mapping of edges to corresponding tows Saving of position in robot coordinate system 40 ºC width Gap Comparison of targeted and actual position Tow-/gap-/overlap-width Overlap 0 6, ,5 100 mm 18, Vö IFW / PUK / IFL Seite 17

18 T [ºC] Monitoring the Lay-up Process Detection of failures like bridging ROI Selection region of interest (ROI) Generation of dynamic threshold value for hot and cold spots Bridging over gap with material change ROI Cold/Hot Spots Detection of temperature anomaly Nx [Pixel] Ny[Pixel] Vö IFW / PUK / IFL Seite 18

19 Conclusion Integrated process monitoring reduces QA-efforts and non-productive time. Considering manufacturing restrictions during the component phase reduces iterative adaption between manufacturing and and hereby rampup efforts. The configuration of process monitoring with information from manufacturing analysis allows an individual monitoring of the manufacturing. In total, all this rise the process stability in an individual production of mostly single components. Vö IFW / PUK / IFL Seite 19

20 Dr.-Ing. Carsten Schmidt Head of Research Group High performance Production of CFRP-Structures Managing Director of CFK Nord Research Department Institute of Production Engineering and Machine Tools (IFW) Leibniz Universität Hannover CFK Nord Ottenbecker Damm Stade Tel.: Funded by the European Regional Development Fund/MSC Lower Saxony Thank you for your attention. Scm IFW / PUK / IFL Seite 22