Problem

Flaws in laser powder bed fusion (LPBF) additive manufacturing (AM) components detrimentally affect part quality and thus mechanical performance, thereby limiting applications of the technology in industry. Though OEMs optimize processing conditions to achieve the best possible quality, stochastic flaws persist in AM material. These internal flaws negatively affect fatigue properties, limit the ability to define design limits, hamper qualification efforts, and consequently prevent widespread use of AM in many critical applications.

Objective

The objective of this effort is to develop and demonstrate key processes necessary to realize interlayer repair in an LPBF system based on automated flaw detection demonstrated in prior efforts. Specifically, the project seeks to optimize process parameters to repair flaws by remelting between layers and document impact on remaining flaws via post-build computed tomography (CT) scans. Another objective is to demonstrate the ability to realize interlayer repair procedures in a production LPBF system using the software application program interface (API).

Technical Approach

The Applied Research Laboratory at the Pennsylvania  State University (ARL/PSU) is leading the program which includes Moog AMC (Moog) and 3D Systems (3DS). Experiments are being designed to optimize process parameters necessary to achieve successful interlayer remelt repair. One build designed by ARL/PSU is exacerbating formation of stochastic flaws, e.g. parts located near the cross-flow exit. A series of remelt process conditions is being applied to various regions of the part (performed by 3DS). Post-build CT scans are used to assess the effectiveness of each remelt condition by The Applied Research Laboratory at the Pennsylvania State
University (ARL/PSU) is leading the program which includes Moog AMC (Moog) and 3D Systems (3DS). Experiments are being designed to optimize process parameters necessary to achieve successful interlayer remelt repair. One build designed by ARL/PSU is exacerbating formation of stochastic flaws, e.g. parts located near the cross-flow exit. A series of remelt process conditions is being applied to various regions of the part (performed by 3DS). Post-build CT scans are used to assess the effectiveness of each remelt condition by ARL/PSU.

Demonstration of key capabilities necessary to realize an integrated interlayer remelt repair of specified regions is planned. An API designed by 3DS is being employed to remelt specified regions prior to recoating the next layer. An application developed by ARL/PSU is used to specify the remelt region and process parameters with process monitoring data collected before and after the repair operation to confirm operation.
Finally, the ability to realize interlayer repair is assessed with an interrupted build strategy. A build created by Moog with process parameters known to generate defects is removed partway through the build and CT scanned. Interlayer remelt parameters are being applied to the top surface and post- repair CT scans compared to assess effectiveness.

Finally, the ability to realize interlayer repair is assessed with an interrupted build strategy. A build created by Moog with process parameters known to generate defects is removed partway through the build and CT scanned. Interlayer remelt parameters are being applied to the top surface and post- repair CT scans compared to assess effectiveness.

Project Participants

Project Principal

Other Project Participants

  • Moog AMC
  • 3D Systems

Public Participants

  • U.S. Department of Defense

Project Summary

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