US 9,999,924 B2Granted

Method and system for monitoring additive manufacturing processes

AssigneeSigma Labs, Inc.

InventorsVivek R. Dave, R. Bruce Madigan, Mark J. Cola, Martin S. Piltch

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Abstract

This invention teaches a quality assurance system for additive manufacturing. This invention teaches a multi-sensor, real-time quality system including sensors, affiliated hardware, and data processing algorithms that are Lagrangian-Eulerian with respect to the reference frames of its associated input measurements. The quality system for Additive Manufacturing is capable of measuring true in-process state variables associated with an additive manufacturing process, i.e. those in-process variables that define a feasible process space within which the process is deemed nominal. The in-process state variables can also be correlated to the part structure or microstructure and can then be useful in identifying particular locations within the part likely to include defects.

Claims15

Dependent claims

An additive manufacturing method, comprising:

depositing a layer of metal material;
melting a region of the layer of metal material to form a part with a heat source that scans across the region of the layer of metal material to melt the region;
monitoring an amount of energy emitted by the heat source by maintaining a path along which the heat source scans the region within a first field of view of a first optical sensor to provide a first information set;
monitoring a fixed portion of the region of the layer of metal material with a second optical sensor to provide a second information set, the fixed portion of the region being positioned so that the path extends both into and out of a second field of view of the second optical sensor;
and
subsequent to melting the region of the layer of metal material, determining whether the first and second information sets indicate the region falls within a known-good range of a baseline dataset associated with the part being produced by the additive manufacturing method by:
correlating data included in the second information set with data included in the first information set, wherein the data correlated from the first and second information sets was collected while the heat source passed through the fixed portion of the region;
calculating a plurality of state variables using at least a portion of the first information set and at least a portion of the second information set;
and
comparing the plurality of state variables with a plurality of ranges associated with state variables of the known-good range of the baseline dataset;
and
adjusting the additive manufacturing operation when the correlated information associated with the layer of metal material indicates an out of parameters event.

9 more elements

An additive manufacturing method, comprising:

depositing a layer of metal powder;
melting a region of the layer of metal powder to form a part being produced by the additive manufacturing method with a heat source that scans across the region of the layer of metal powder to melt the region;
monitoring an amount of energy emitted by the scanning heat source with a first optical sensor that follows a path along which the heat source scans the region to provide a first information set;
monitoring a fixed portion of the region using a second optical sensor to provide a second information set, the fixed portion of the region being positioned such that the path is located both within and outside of a field of view of the second optical sensor;
and
subsequent to melting the region of the layer of metal powder, determining whether the first and second information sets indicate the region falls within a known-good range of a baseline dataset associated with the part being produced by the additive manufacturing method by:
comparing at least a portion of the first and second information sets with ranges associated with the known-good range of the baseline dataset to identify one or more portions of the part that may include a manufacturing defect;
and
in response to the first and second information sets indicating the region falls outside of the known good range of the baseline dataset, adjusting the additive manufacturing operation.

6 more elements

Dependencies are inferred from the claim text.

Facts

Application: 14/832,691Filed 21 Aug 2015 · us provisional application
Priority: 22 Aug 2014
Published: US 2016/0184893 A130 Jun 2016
Granted: 19 Jun 2018
Term ends: Not estimatedThe source records don’t support an estimate.

Classification22 codes

B29C 64/153
Using only solid materials: using layers of powder being selectively joined, e.g. by selective laser sintering or melting
B22F 10/28
Direct sintering or melting: powder bed fusion, e.g. selective laser melting [SLM] or electron beam melting [EBM]
B22F 10/31
Process control: calibration of process steps or apparatus settings, e.g. before or during manufacturing
B22F 10/38
Process control: to achieve specific product aspects, e.g. surface smoothness, density, porosity or hollow structures