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LPBF Right the First Time—the Right Mix Between Modeling and Experiments

  • Mustafa MegahedEmail author
  • Hans-Wilfried Mindt
  • Jöerg Willems
  • Paul Dionne
  • Lars Jacquemetton
  • James Craig
  • Piyush Ranade
  • Alonso Peralta
Thematic Section: Additive Manufacturing Benchmarks 2018
Part of the following topical collections:
  1. Additive Manufacturing Benchmarks 2018

Abstract

Laser powder bed fusion (LPBF) is an additive manufacturing process with many adjustable input parameters that directly affect manufacturability and quality of the final product. The selection of the optimal input parameters makes the process qualification and part certification a costly and time-consuming task if performed using the traditional sequential and empirical approach.

Within the scope of the DARPA open manufacturing program, a rapid qualification framework is developed that relies on parallel multi-physics modeling and experimental efforts for verification and validation of the process input parameters during process development and material characterization. Product manufacturability is tested a priori via modeling and in-process monitoring is deployed to ensure input parameters are rapidly screened, and an optimal process window is selected. Process consistency and repeatability is further ensured through process characterization, process qualification, and via quantitative analysis of digital In-Process Quality Metrics™ (IPQM®s).

This paper discusses the rapid qualification methodology, model validation, and the application of the framework towards manufacturing of a challenging part defined by AFRL. The combination of numerical predictions, experimental refinement, and in-process monitoring delivered the first print right at first trial. Distortions are within predictions, geometric accuracy is within expectations, and quantitative metallurgical analysis shows dense as-built material with properties expected to fulfill performance requirements. In-process monitoring results provide a quantitative, digital Quality Signature™ or Digital Quality Record™ of process consistency and product quality.

Keywords

Metal additive manufacturing Laser powder bed fusion Process modeling Validation Powder scale Residual stress Distortion Simulation Experimental validation Certification In-process monitoring Process development Process qualification ICME Uncertainty quantification 

Notes

Authors’ Contributions

All authors contributed to the effort described in this article.

Funding Information

This study is financially supported by the DARPA Open Manufacturing program, USA.

Compliance with Ethical Standards

Competing Interests

The results presented in this work are that of the team involved in the DARPA Open Manufacturing program. References to literature and results of other research teams are made neutrally to gain better understanding of the modeling algorithms and the implications for real-life applications.

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Copyright information

© The Minerals, Metals & Materials Society 2019

Authors and Affiliations

  1. 1.ESI Software Germany GmbHEssenGermany
  2. 2.ESI US R&DHuntsvilleUSA
  3. 3.Sigma Labs Inc.Santa FeUSA
  4. 4.Stratonics Inc.Lake ForestUSA
  5. 5.Honeywell AerospacePlymouthUSA
  6. 6.Honeywell AerospacePhoenixUSA

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