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Accurate Modeling of 3D Selective Laser Melting for Large Parts

  • today
  • access_time 10:00 - 10:25 AM EDT
  • location_onRoom 140F
  • blur_circularConference
  • monetization_onPaid Upgrade
  • schoolOptimization

This presentation illustrates how recent advances in materials physics and computer science have been applied to additive manufacturing. The resultant technology shows significant promise to:

  • Reduce process development time (10X), especially for complex integrated components
  • Reduce labor, equipment, and waste materials costs
  • Increase quality and reliability
  • Improve operator training on a virtual machine emulator, thereby freeing up production equipment and eliminating raw materials costs associated with training and trial and error at no cost 

The development of new tools in materials science enables the prediction of how process conditions like scan rate, laser power, and build orientation affect part quality. These process parameters influence complex coupled phenomena like: melting, capillary and gravitational flow, phase separation and inhomogeneous solidification. Optimization of process parameters in the preproduction phase can be time-consuming and costly, especially for large (integrated) components with active geometry. 

The presentation will detail how improved algorithms and custom engineering workstations have been developed to address these challenges, allowing detailed prediction and computer rendering of small (1 -5 micron) features and defects in large detail components. The question of how to conduct and interpret these large-scale intensive computer simulations by manufacturing engineers on the shop floor will be illustrated using emulation technology. Examples of the “virtual” manufacture of two real-world components — namely a prosthetic implant and an aircraft engine airfoil — will be presented and compared with quality metrics obtained from the manufacture and testing of the actual parts. 

Learning Objectives:

  • Appreciate how deep new science can be captured and transitioned to manufacturing using state-of-the art engineering workstations; see a real-world example using selective laser melting
  • Make informed decisions on how to implement new physics-based AI in real-world materials and process operations
  • Increase productivity and quality of additive manufacturing and have a window on how similar technology could be used in general manufacturing (machining) and joining (welding) operations.