Applied process monitoring and control for manufacturing of advanced composites

Transcription

1 Applied process monitoring and control for manufacturing of advanced composites Dr Nikos Pantelelis National Technical University of Athens, Athens, GREECE Efthymios Bistekos Synthesites Ltd, Athens, GREECE

2 Process Monitoring and Control Production automation Continuous temperature optimisation for injection and curing Quality control Scrap reduction Improve productivity Increase process know-how and decrease dependency from craftmanship

3 Dielectric vs. Electrical monitoring

4 Cure and Flow Sensors Several sensor models have been manufactured and tested to match a range of composite materials processing sensing requirements process monitoring sensor = resistance sensor + RTD sensor cure monitoring system and in-mould sensor Inline sensor Pot sensor Viscosity rise gelation end-of-cure No pipe cleaning injection window mixing ratio Addition of fresh resin or rejection injection window

5 Lab-scale trials (AC vs DC) Resistance vs Impedance of curing Cytec s 890 epoxy system for 120 o C to 180 o C

6 Lab-scale trials (AC vs DC) Resistance and Impedance vs degree of cure of Bakelite L20 system (45 o C to 80 o C)

7 Lab-scale trials (viscosity vs resistance) Resistance and viscosity monitoring of Bakelite s neat L20 epoxy resin at various temperatures

8 Resistance/ viscosity correlation Resistance and viscosity are directly related σ( T) [ η( T)] k = Const η ( T) = C [ R( T)] K

9 Polarisation? No thanks

10 Process quality control 100:37 100:34 100:31 Mixing ratio deviations (L20 system for 100:37, 100:34 and 100:31)

11 Effect of hardener s ratio in curing time 1,0 ±3% hardener variation 0,8 Exact ratio S11 S12 S13 S14-3% hardener S15 S16 S17 Remaining Cure Factor Cure Monitoring Index 0,6 0,4 +3% Exact +3% hardener -3% S18 S19 S110 S111 S112 S113 0,2 30% time variation 0,0 Curing time [min]

12 End-of-Cure monitoring

13 End-of-Cure monitoring R170 α170 R170 α180 R180 α170 Resistance vs Degree of 170, 180 o C

14 Monitoring aged resins Resistance vs mixing ratio of fresh and aged monocomponent resin

15 Aerospace resin o C o C Case 3 Case 2,4 Case 1

16 Viscosity vs resistance Case 3 Case 2,4 Case 1

17 Industrial Application: CFRP Speargun Cure monitoring of carbon/epoxy RTM production Outlet gate Inlet gate No direct contact with the part is necessary

18 With and without control With control No control

19 Speed-up with manual control

20 Conclusions Viscosity and resin aging can be monitored so resin quality control is possible before the start of the injection Process monitoring system has been successfully implemented in process monitoring at industrial conditions. Using the system faster opening of the mould was possible leading to 30-36% process speed-up and 60% increase in production rate. Sensors and monitoring system proved robust and reliable, requiring no special treatment during production. Similar systems can be used in vacuum infusion, LRTM, pultrusion, SMC, autoclaves as well as reactive thermoplastics production.

21 What s next? Intelligent sensorised automation in composites production Inline Sensors Mould Composite part In-mould Sensor Monitoring System

22 10 organisations from 6 European countries Introduction of artificial intelligence in process monitoring, modelling and control Wide range of applications from RTM to pultrusion and from RT to high-temp Field trials in four industrial applications (RTM, infusion and pultrusion) without (monitoring) and with control Please visit

23 Consortium CEMCAT (Research Centre, Co-ordinator) Sotira (Automotive industry) Atoutveille (Consulting) Synthesites (Process monitoring and control) NTUA (Process monitoring, modeling & control) BIBA (Wireless communications and logistics) Newcastle University (Artificial Intelligence) Inasmet (Material and process modelling) Acciona (Constructions Industry) Karnic (Boat industry) iremo project is partially funded by the European Commission