US 2024/0390984 A1Published application

Predictive defect model for highly productive laser powder bed fusion additive manufacturing

AssigneeRaytheon Technologies Corporation

InventorsParisa Farahmand, Masoud Anahid

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Abstract

This disclosure is directed to a method for modeling additive manufacturing of a part, including a number of steps. The steps include constructing a model for estimating output of a simulated additive manufacturing process, followed by entering process operating parameters for an additive manufacturing system into the model to produce an output. The output is compared to acceptance criteria to determine whether the output is acceptable or unacceptable. Next regions of operating parameters that support production of the part with acceptable quality characteristics are determined based upon the output. Regions of operating parameters that support production of the part with acceptable quality characteristics are added to a process map for additive manufacturing the part. The steps are repeated for different operating parameters until the process map is complete.

Claims20

Dependent claims

A method for modeling additive manufacturing of a part, comprising the steps of:

(i) constructing a model for estimating output of a simulated additive manufacturing process based upon powder composition, part design, physical properties of a melt pool channel, Bernoulli's equation, energy and mass conservation equations, a laser attenuation coefficient that represents a power loss ratio of the laser to its incident power on a powder bed, wherein the laser attenuation coefficient is a function of recoil pressure, vapor jet velocity and temperature and vapor-driven gas flow;
(ii) entering process operating parameters for an additive manufacturing system into the model to produce an output as a defect status, wherein the operating parameters include:
(1) laser beam spot size, build plate temperature, and layer thickness;
(2) temperature-dependent thermophysical properties of the powder;
(3) feedstock properties including average powder particle size;
and
(4) laser hatching strategy including hatch distance, hatch delay time, and stripe width;
(iii) comparing the output to acceptance criteria to determine whether the output is acceptable or unacceptable;
(iv) determining, based upon the output, regions of operating parameters that support production of the part with acceptable quality characteristics;
(v) adding regions of operating parameters that support production of the part with acceptable quality characteristics to a process map for additive manufacturing the part;
and
(vi) repeating steps (ii) through (v) for different operating parameters until the process map is complete, wherein the complete process map includes:
(1) at least one single-track map that indicates regions for an unstable melt pool;
and
(2) at least one single-stripe map that indicates regions for vapor-induced lack-of-fusion defects.

12 more elements

Dependencies are inferred from the claim text.

Facts

Application: 18/323,875Filed 25 May 2023
Published: 28 Nov 2024
Term ends: Not estimatedThe source records don’t support an estimate.

Classification11 codes

B22F 10/36
Process control: of energy beam parameters
B22F 10/85
Data acquisition or data processing: for controlling or regulating additive manufacturing processes
B22F 10/28
Direct sintering or melting: powder bed fusion, e.g. selective laser melting [SLM] or electron beam melting [EBM]
B22F 10/366
Of energy beam parameters: scanning parameters, e.g. hatch distance or scanning strategy