US 12,330,217 B2
Method and system for optimizing process parameters in an additive manufacturing process
Ali Bonakdar, Nuns Island (CA); Farzad Liravi, Kitchener (CA); Ehsan Toyserkani, Waterloo (CA); Usman Ali, Waterloo (CA); Shoja'edin Chenouri, Waterloo (CA); and Yahya Mahmoodkhani, Waterloo (CA)
Assigned to Siemens Energy Global GmbH & Co. KG, Munich (DE); and University of Waterloo, Waterloo, CA (US)
Appl. No. 17/599,392
Filed by Siemens Energy Global GmbH & Co. KG, Munich (DE); and University of Waterloo, Waterloo (CA)
PCT Filed Mar. 29, 2019, PCT No. PCT/US2019/024909
§ 371(c)(1), (2) Date Sep. 28, 2021,
PCT Pub. No. WO2020/204883, PCT Pub. Date Oct. 8, 2020.
Prior Publication US 2022/0176457 A1, Jun. 9, 2022
Int. Cl. B22F 10/85 (2021.01); B22F 10/28 (2021.01); B22F 10/38 (2021.01); B22F 12/41 (2021.01); B33Y 10/00 (2015.01); B33Y 50/02 (2015.01); G05B 13/02 (2006.01)
CPC B22F 10/85 (2021.01) [B22F 10/28 (2021.01); B22F 10/38 (2021.01); B22F 12/41 (2021.01); G05B 13/024 (2013.01); B33Y 10/00 (2014.12); B33Y 50/02 (2014.12); G05B 2219/49023 (2013.01)] 12 Claims
OG exemplary drawing
 
1. A method for determining optimal values of significant process parameters in an additive manufacturing (AM) process for printing a part from a specified process material, comprising:
defining a set of target output material properties to be optimized,
identifying an initial set of process parameters pertaining to the AM process,
a screening phase comprising:
executing a first plurality of experimental print runs based on a first experiment design applied to said initial set of process parameters,
obtaining a first output response by measuring the target output material properties for each print run,
based on the first output response, determining, from said initial set of process parameters, a subset of process parameters that affect the target output material properties, and
an optimization phase comprising:
executing a second plurality of experimental print runs based on a second experiment design applied to said subset of process parameters,
obtaining a second output response by measuring the target output material properties for each print run, and
based on the second output response, determining optimal values for each process parameter in said subset of process parameters, for which a maximization or minimization of the target output material properties is predicted,
wherein the first experiment design comprises a two-level Placket Burman design, involving at least a “low” level and a “high” level of each of the parameters of the initial set of process parameters,
wherein the number of first experimental print runs is at least k+1, and
where k is the number of process parameters in the initial set of process parameters.