Quality Monitoring of the EBM Process

Transcription

1 Quality Monitoring of the EBM Process 1 st International Conference on Electron Beam Additive Manufacturing M.Sc. Stephan Janson* M.Sc. Fabian Bayerlein Prof. Dr.-Ing. Michael F. Zäh Institute for Machine Tools and Industrial Management Application Center Augsburg Technical University of Munich Nürnberg, 27. April 2016

2 Agenda Institute Profile / AM-Lab Selection of suitable QM Systems Integration into the EBM System Testing and Results Conclusion and Outlook 2

3 Agenda Institute Profile / AM-Lab Selection of suitable QM Systems Integration into the EBM System Testing and Results Conclusion and Outlook 3

4 Institute Profile Institute for Machine Tools and Industrial Management () Wettzell Ingolstadt Straubing Augsburg Neuherberg Freising- Weihenstephan Garching Munich Raitenhaslach Freyung- Grafenau Iffeldorf Zugspitze Ottobrunn Obernach/ Walchensee Berchtesgaden Projektgruppe RMV 4

5 Institute Profile The Additive Manufacturing Laboratory Fields of Competence Process development Technologies Laser beam melting Electron beam melting Process monitoring Simulation Functional integration & lightweight design Laser beam sintering 3D printing Powder analysis Process chain optimization 5

6 Institute Profile EBM-System Available at the, based on a pro-beam K6 Self-developed powder supply and recoating mechanism Modular design Maximum acceleration voltage: 100 kv Maximum beam current: 100 ma Maxium beam power : 10 kw Power supply Vacuum pumps Beam generator HMI High voltage generator Vacuum chamber 6

7 Agenda Institute Profile / AM-Lab Selection of suitable QM Systems Integration into the EBM System Testing and Results Conclusion and Outlook 7

8 Selection of Suitable QM Systems Prioritization of Selection Criteria A questionnaire with the target preference matrix was filled out by experts in research and industry The count of preferences was summed up and normalized to obtain the weighted score uncertainty of measurement costs measuring time possibility for calibration analyzability of results accessibility for maintenance effort for implementation degree of innovation Weighted score 8

9 Selection of Suitable QM Systems Application of Weighted Selection Criteria on Available QM Systems Requirements analysis CMOS- Camera uncertainty of measurement costs Experts Survey measuring time possibility for calibration analyzability of results accessibility for maintenance effort for implementation 9 9 degree of innovation Weighted score 9

10 Agenda Institute Profile / AM-Lab Selection of suitable QM Systems Integration into the EBM System Testing and Results Conclusion and Outlook 10

11 Integration into the EBM System scmos-camera High-performance scmos (scientific CMOS) camera pco edge 5.5 with a actively cooled sensor Maximum resolution 5.5 MP (2560 x 2160) Quantum efficiency of 30 % at 800 nm Suitable for near infrared (NIR) use Maximum framerate of 100 Hz Mounted outside of the light-optical system of the EBM machine Possible Orientation of the scmos-camera 10 mm Mounting on EBM-System High Dynamic Range Image in Visible (l.) and in NIR-Spectrum (r.) 10 mm 11

12 Integration into the EBM System ELO-System (Electron Optical System) Working principle similar to Scanning Electron Microscope Generates a signal of backscattered and secondary electrons High detail and high contrast images Maximum magnification limited by energy input and local charge 10 mm EBM-Machine with ELO-System Defect detection in a specimen using the ELO-System 12

13 Agenda Institute Profile / AM-Lab Selection of suitable QM Systems Integration into the EBM System Testing and Results Conclusion and Outlook 13

14 Testing and Results Specimen Design and Process Limitations Void number Height [mm] Diameter [mm] 1 2,00 3,00 2 1,00 2,00 3 0,50 1,00 4 0,25 1,00 5 0,10 1,00 6 0,05 1,00 Ø 10 mm Section of the CAD-geometry of a specimen showing the intentional voids inside CT Sections of the specimens show that voids with h < 0,25 mm were not intentionally producible 14

15 Testing and Results Capability of the ELO System High contrast High depth of view Capable of detecting small voids Easy to integrate into the EBM-Machine Robust for EBM-Conditions ELO-image of a finished -test-plate 50 µm 5 mm 10 mm ELO-image of a specimen with various void dimensions 15

16 Height difference [mm] Height of the void [mm] Testing and Results Deviations of Measurements in Specimens with Intentional Voids 2,5 2 1,5 CAD 1 0,5 CAM mean CT mean Specimen with voids 0 Void 1 Void 2 Void 3 Camera > CAD (Influence on the layers over the void) CT< CAD (Downskin-Effect due to heat accumulation over loose powder) The deviation CAD-CT scales with the dimension of the void 0,40 0,30 0,20 0,10 0,00-0,10-0,20-0,30-0,40-0,50 Void 1 Void 2 Void 3 CAD-CT CAD-CAM CT-CAM 16

17 Testing and Results 3D Reconstruction of a Build-Job 3D reconstruction of a buildjob from layer-images and original slice-data Fast visual check on macroscopic defects Appearance can be adjusted by varying the threshold values for color and opacity Data-chain not fully automated yet 3D reconstruction of a build-job (l.) and detailed view (r.) 17

18 Testing and Results Detection of Defects due to Altered Process Parameters Specimen Cuboid 1 Cuboid 2 Cuboid 3 Parameters Reference: Standard process parameters (focus current 28 ma, scanning velocity 4500 mm/s, beam current 15 ma) Defocused beam (focus current 40 ma) Reduced scanning velocity (3000 mm/s) Detailed layer-per-layer detection of defects Number, center position and dimension of the defects are given as output Appropriate filters and thresholds are needed for data-extraction 10 mm Cross-section of CT- (up) and Camera-Data (down) Application of Filters and Thresholds 18

19 Agenda Institute Profile / AM-Lab Selection of suitable QM Systems Integration into the EBM System Testing and Results Conclusion and Outlook 19

20 Conclusion and Outlook Conclusion Two monitoring systems were implemented in the EBM machine: scmos camera ELO-system (Electron optical system) Defects occurring during the additive build-up of parts can be detected Existence of the defects was validated by CT-scans of the specimens Images taken layer by layer can be assembled to 3D renderings of the parts including their inner structure for a quick visual check For detailed analysis, counting and classification of defects can be performed automatically to determine whether the part has to be declared a reject These applications represent post-process analyses at the moment 20

21 Conclusion and Outlook Outlook For in-process control the underlying machine software must be able to receive and process data from the monitoring system and to intervene in the manufacturing process online Further research in the field of powderbed properties and material qualification will be conducted for a better understanding of the process needs Funding Most of the presented results were generated in the Cornet project ZeDAM (Zero Defect Additive Manufacturing). We are grateful for the generous funding. 21

22 M.Sc. Stephan Janson Research Group Additive Manufacturing Technical University of Munich Institute for Machine Tools and Industrial Management Application Center Augsburg Beim Glaspalast Augsburg Tel Fax stephan.janson@.tum.de