Identifying uncertainty in Laser Powder Bed Fusion models

Published

June 30, 2016

Author(s)

Felipe F. Lopez, Paul Witherell, Brandon Lane

Abstract

A limitation frequently encountered in additive manufacturing (AM) models is a lack of indication about their precision and accuracy. Often overlooked, information on model uncertainty is required for validation of AM models, qualification of AM-produced parts, and uncertainty management. This paper presents a discussion on the origin and propagation of uncertainty in Laser Powder Bed Fusion (L-PBF) models. Four sources of uncertainty are identified: modeling assumptions, unknown simulation parameters, numerical approximations, and measurement error in calibration data. Techniques to quantify uncertainty in each source are presented briefly, along with estimation algorithms to diminish prediction uncertainty with the incorporation of online measurements. The methods are illustrated with a case study based on a transient, stochastic thermal model designed for melt pool width predictions. Model uncertainty is quantified for single track experiments and the effect of online estimation in overhanging structures is studied via simulation. The application of these concepts to estimation and control of the L-PBF process is suggested.

Proceedings Title

Proceedings of the ASME 2016 Manufacturing Science and Engineering Conference (MSEC2016)

Conference Dates

June 27-July 1, 2016

Conference Location

Blacksburg, VA, US

Conference Title

The ASME 2016 Manufacturing Science and Engineering Conference (MSEC2016)

Pub Type

Conferences

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Keywords

additive manufacturing, uncertainty quantification, melt pool width

Citation

Lopez, F. , Witherell, P. and Lane, B. (2016), Identifying uncertainty in Laser Powder Bed Fusion models, Proceedings of the ASME 2016 Manufacturing Science and Engineering Conference (MSEC2016), Blacksburg, VA, US, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=919851 (Accessed November 21, 2024)