Application of Additive Manufacturing in Aerospace Industry

This Presentation based on the benefits and the advantage of the Additive Manufacturing in the world. There how it make this useful around the companies and other things

1. 1 APPLICATION OF ADDITIVE MANUFACTURING IN AEROSPACE AND AERONAUTICS DAYALBAGH EDUCATIONAL INSTITUTE SUBMITTED BY- ABHIJEET AGARWAL M.TECH 1 ST YEAR FULL TIME SUBMITTED TO- Prof. Ram Swarup Sharma

2. Additive manufacturing of metallic components 2 Wire Feed Directed Energy Deposition* Powder Feed Directed Energy Deposition* Powder Bed Fusion* Fusion of successive layers of metal using a focused heat source which follows a pre-programmed path Each additive manufacturing process has unique characteristics and end uses Pre-programmed features of equipment limit broad application

3. Benefits of additive manufacturing aerospace components Reducing the number of processing steps Reducing weight Increase fuel efficiency Expand function and application Reducing lead time Reducing life cycle costs 3

4. Additive manufacturing aerospace applications Selective material addition Blades and vanes Case features Heat exchangers Fuel Nozzles Bearing housings Brackets Repair 4

5. Why is additive manufacturing important to the aerospace industry? Production of geometries not possible with common manufacturing methods Expand materials applications Enables production of functional light weight structures Fuel efficiency, weight Consolidation of parts Cost, weight, mechanical uniformity, waste, lead time Repair rather than remake Cost Potential for competitive advantage 5

6. Repair of aerospace components via powder feed directed energy deposition Thermal profile measurement is very difficult and may not be entirely accurate since molten pool is so small Microstructure is influenced by substrate cross section thickness, repair volume, and process parameters Need to achieve target geometry and mechanical properties Very difficult to be successful on first attempt Failure can result in costly rework or even scraping component 6

7. The dichotomy of additive manufacturing benefits Design complexity makes post process inspection and qualification challenging Destructive inspection and certification can be costly For repair applications, destructive testing is not possible Qualifying complex components is costly and can require years of research 7 New tools and methods are needed to reduce qualification costs

8. Why is process modeling necessary? Solving complex multi-objective problem in one process development program: Time and cost Many process variables affect resulting quality Material challenges Geometric constraints/effects Monitoring/controlling challenges Measurement of molten pool temperatures, stress, and defect formation is difficult Development relies on many experimental iterations Repair applications often require near base metal properties Need to qualify many materials due to complexity of engine design 8

9. Structure/process/property relationships The type of AM process, process parameters, component geometry, and tool paths/scan strategies affect cooling rate Cooling rate affects microstructure Multiple passes of the heat source can result in microstructure variation as a result of thermal cycling 9 Affects on microstructure of the Material changes the mechanical properties and component life . Base Metal Microstructure Microstructure of Deposited Material

10. What information can be calculated using process models? 10 Temperature Profiles Fluid Flow Profile and Track Geometry Residual Stress and Distortion Phase Fractions Mechanical Properties

11. Additive manufacturing of metallic components consists of many complex physical processes 11 Physical Processes During Powder Bed AM

12. Experimental validation of process models is critical to deriving benefit Trusted modelling results come from extensive experimental validation Temperature measurement High speed video imaging Metallographic evaluation Residual stress measurement Mechanical testing Important to recognize limitations to experimental validation methods Experimental validation can be challenging 12 Identifying reliable and cost effective methods to validate process models is important

13. Determining parameters for material addition to a thin wall component Laser powder feed directed energy deposition Analytical heat transfer calculation Understand effects of process parameters on in molten pool geometry Evaluated a range of powers, travel speeds, and wall thicknesses Laser spot size and powder feed rate fixed 13 Heat source traveling along thin wall component

14. Calculation of Track Geometry using a heat transfer and fluid flow model Laser powder feed AM Three-dimensional temperature profile influences track geometry, microstructure and mechanical properties Track geometry is important to achieving target component geometry Evaluation of single tracks using various laser powers for material addition to IN-718 flat plate 14 Diagram of Model Solution Domain

15. Calculation of Track Geometry using a heat transfer and fluid flow model Calculated track geometries were comparable with experimental results With a well validated model we can predict cooling rates which will allow for the prediction of residual stress, distortion, phase fractions and grain morphology 15 Comparison of Experimental and Calculated Track Geometries for Travel Speed of 24 in/min

16. What Improvement needed ? Agreement and availability of material physical property data Continue to experimentally validate assumptions and models Identifying new methods of model validation User friendly models, which require limited experience and expertise Model run time is critical when basic experiments can be completed in minutes or hours. Days may be too much time!! Developing models to prescribe process parameters and tool paths for a given material and component geometry 16 Process optimization via integrated process models is highly desirable

17. Summary The complexity of components produced by additive manufacturing gives rise to many benefits and challenges With operator ability to modify process parameters and tool path, the need for fundamental understanding becomes critical Process modeling provides fundamental process information which is otherwise difficult to experimentally measure Integrated process models can be useful for process optimization and the prescription of process parameters and tool paths As modeling capability improves, it will be important to maintain a user friendly interface and improve calculation efficiency 17

18. 18 THANK YOU