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

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-co...

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Veröffentlicht in:Integrating materials and manufacturing innovation 2019-06, Vol.8 (2), p.194-216
Hauptverfasser: Megahed, Mustafa, Mindt, Hans-Wilfried, Willems, Jöerg, Dionne, Paul, Jacquemetton, Lars, Craig, James, Ranade, Piyush, Peralta, Alonso
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container_end_page 216
container_issue 2
container_start_page 194
container_title Integrating materials and manufacturing innovation
container_volume 8
creator Megahed, Mustafa
Mindt, Hans-Wilfried
Willems, Jöerg
Dionne, Paul
Jacquemetton, Lars
Craig, James
Ranade, Piyush
Peralta, Alonso
description 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.
doi_str_mv 10.1007/s40192-019-00133-8
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subjects Additive Manufacturing Benchmarks 2018
Characterization and Evaluation of Materials
Chemistry and Materials Science
Consistency
Construction materials
Empirical analysis
Geometric accuracy
Manufacturability
Manufacturing
Materials Science
Mathematical models
Metallic Materials
Metallurgical analysis
Monitoring
Nanotechnology
Powder beds
Process parameters
Quality
Quantitative analysis
Structural Materials
Surfaces and Interfaces
Thematic Section: Additive Manufacturing Benchmarks 2018
Thin Films
title LPBF Right the First Time—the Right Mix Between Modeling and Experiments
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