Method and apparatus for robust reduction of shape error in laser powder deposition based additive manufacturing process due to uncertainty
US-2021141970-A1 · May 13, 2021 · US
US11531920B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-11531920-B2 |
| Application number | US-202016859349-A |
| Country | US |
| Kind code | B2 |
| Filing date | Apr 27, 2020 |
| Priority date | Apr 27, 2020 |
| Publication date | Dec 20, 2022 |
| Grant date | Dec 20, 2022 |
A practical reading order for non-experts. Skip the full description unless you need deep technical detail.
What the patent document calls the invention.
A short plain-language summary of the technical disclosure.
Who owns or filed the patent and who is credited as inventor.
Filing, priority, publication, and grant dates set the timeline.
The legal scope of protection — read this for what is actually claimed.
Technology tags used to group this patent with similar filings.
Prior art links and similar publications in this corpus.
Official abstract text for this publication.
A method of evaluating an additive manufacturing process includes receiving a set of additive manufacturing parameters and an additive manufacturing part design at an analysis module, receiving a set of random values at the analysis module, determining a probability distribution of stochastic flaws within a resultant additively manufactured article using at least one multidimensional space physics model, and categorizing the additive manufacturing part design as defect free when the probability distribution is below a predefined threshold. Each value in the set of random values corresponds to a distinct variable in a set of variables. Each variable in the set of variables at least partially defines at least one of an uncontrolled additive manufacturing parameter and an uncontrollable additive manufacturing parameter.
Opening claim text (preview).
The invention claimed is: 1. A method of evaluating an additive manufacturing process comprising: receiving a set of additive manufacturing parameters and an additive manufacturing part design at an analysis module; generating a set of random values using a random number generator; receiving the set of random values at the analysis module, each value in the set of random values corresponds to a distinct variable in a set of variables, and each variable in the set of variables at least partially defines at least one of an uncontrolled additive manufacturing parameter and an uncontrollable additive manufacturing parameter; determining a probability distribution of stochastic flaws within a resultant additively manufactured article using at least one multidimensional space physics model; categorizing the additive manufacturing part design as defect free when the probability distribution is below a predefined threshold; and manufacturing a part according to the additive manufacturing part design in response to the probability distribution being below the predefined threshold. 2. The method of claim 1 , and wherein each variable in the set of variables corresponds to a distinct one of the at least one of the uncontrolled additive manufacturing parameters and the uncontrollable additive manufacturing parameters. 3. The method of claim 2 , wherein the uncontrolled additive manufacturing parameters and the uncontrollable additive manufacturing parameters include at least one of a local powder packing density, a hatch-contour offset, an interlayer dwell time, a powder particle size, a stripe overlap, a layer thickness, and a stripe width. 4. The method of claim 3 , wherein the uncontrolled additive manufacturing parameters and the uncontrollable additive manufacturing parameters include each of a local powder packing density, a hatch-contour offset, an interlayer dwell time, a powder particle size, a stripe overlap, a layer thickness, and a stripe width. 5. The method of claim 1 , wherein receiving the set of random values is reiterated at least 2000 times to determine the probability distribution of stochastic flaws. 6. The method of claim 1 , wherein each random value in the set of random values is defined in a distribution map for the corresponding variable in the distinct set of variables, and the distribution map defines a possible distribution of the values that the corresponding random variable can be and includes data defining odds of the value of the random variable being at each value on the distribution map. 7. The method of claim 6 , wherein each random value is randomly selected from the corresponding distribution map according to the odds defined in the corresponding distribution map. 8. The method of claim 1 , wherein the at least one multidimensional space physics model includes at least one of a model for determining a probability of stochastic unmelt, a probability of stochastic keyhole flaws, a probability of stochastic balling, a probability of stochastic overhang, and a probability of stochastic unmelt with balling. 9. The method of claim 8 , wherein the at least one multidimensional space physics model includes all of the model for determining a probability of stochastic unmelt, the probability of stochastic keyhole flaws, the probability of stochastic balling, the probability of stochastic overhang, and the probability of stochastic unmelt with balling. 10. The method of claim 1 , further comprising determining a correlation between at least one variable in the set of variables and the probability of the occurrence of at least one of the stochastic flaws. 11. The method of claim 10 , wherein the step of determining the probability distribution of stochastic flaws is adapted based on the determined correlation. 12. An additive manufacturing apparatus comprising: a chamber; a platform within the chamber; and a controller, the controller including a processor and a memory, the memory storing instructions for causing the controller to determine a probability distribution of stochastic flaws within a resultant additively manufactured article using at least one multidimensional space physics model and categorize the additive manufacturing part design as defect free when the probability distribution is below a predefined threshold in response to receiving a set of additive manufacturing parameters and an additive manufacturing part design at an analysis module stored in the controller and generating a set of random values using a random number generator, each value in the set of random values corresponds to a distinct variable in a set of variables, and each variable in the set of variables at least partially defines at least one of an uncontrolled additive manufacturing parameters and an uncontrollable additive manufacturing parameters, the controller further includes instructions for causing the additive manufacturing system to manufacture a part according to the additive manufacturing part design in response to the probability distribution being below the predefined threshold. 13. The additive manufacturing system of claim 12 , wherein each variable in the set of variables corresponds to a distinct one of the at least one of the uncontrolled additive manufacturing parameters and the uncontrollable additive manufacturing parameters. 14. The additive manufacturing system of claim 13 , wherein the uncontrolled additive manufacturing parameters and the uncontrollable additive manufacturing parameters include at least one of a local powder packing density, a hatch-contour offset, an interlayer dwell time, a powder particle size, a stripe overlap, a layer thickness, and a stripe width. 15. The additive manufacturing system of claim 14 , wherein the uncontrolled additive manufacturing parameters and the uncontrollable additive manufacturing parameters include each of a local powder packing density, a hatch-contour offset, an interlayer dwell time, a powder particle size, a stripe overlap, a layer thickness, and a stripe width. 16. The additive manufacturing system of claim 12 , wherein receiving the set of random values is reiterated at least 2000 times to determine the probability distribution of stochastic flaws. 17. The additive manufacturing system of claim 12 , wherein the at least one multidimensional space physics model includes at least one of a model for determining a probability of stochastic unmelt, a probability of stochastic keyhole flaws, a probability of stochastic balling, a probability of stochastic overhang, and a probability of stochastic unmelt with balling. 18. The additive manufacturing system of claim 17 , wherein the at least one multidimensional space physics model includes all of the model for determining a probability of stochastic unmelt, the probability of stochastic keyhole flaws, the probability of stochastic balling, the probability of stochastic overhang, and the probability of stochastic unmelt with balling. 19. The additive manufacturing system of claim 12 , further comprising determining a correlation between at least one variable in the set of variables and the probability of the occurrence of at least one of the stochastic flaws. 20. The additive manufacturing system of claim 19 , wherein the step of determining the probability distribution of stochastic flaws is adapted based on the determined correlation.
Probabilistic graphical models, e.g. probabilistic networks · CPC title
Data acquisition or data processing · CPC title
Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS] · CPC title
Surface or curve machining, making three-dimensional [3D] objects, e.g. desktop manufacturing · CPC title
Powder bed fusion, e.g. selective laser melting [SLM] or electron beam melting [EBM] · CPC title
Related publications grouped by family.
Answers are generated from the same data shown on this page.