US 12,169,401 B2
Systems and methods for automated prediction of machining workflow in computer aided manufacturing
Tania Campanelli, Fano (IT); Daniele Spitaletta, Pistoia (IT); and Luigi Galavotti, Florence (IT)
Assigned to HEXAGON TECHNOLOGY CENTER GMBH, Heerbrugg (CH)
Filed by HEXAGON TECHNOLOGY CENTER GMBH, Heerbrugg (CH)
Filed on May 19, 2023, as Appl. No. 18/199,727.
Application 18/199,727 is a continuation of application No. 17/191,386, filed on Mar. 3, 2021, granted, now 11,693,394.
Claims priority of provisional application 62/984,755, filed on Mar. 3, 2020.
Prior Publication US 2023/0341842 A1, Oct. 26, 2023
Int. Cl. G05B 19/418 (2006.01)
CPC G05B 19/4188 (2013.01) [G05B 19/41815 (2013.01); G05B 19/4183 (2013.01); G05B 19/41865 (2013.01)] 11 Claims
OG exemplary drawing
 
1. A method comprising:
selecting one or more sequences of machining types for a feature of one or more features, wherein the selection of the one or more sequences of machining types is based on the feature and user's machining selections from a database of prior selections of machining types;
selecting one or more tools associated with the selected one or more sequences of machining types;
determining one or more machining parameters for the selected one or more tools, wherein the determined one or more machining parameters are based on whether the selected one or more sequences of machining types is using inefficient or incorrect parameters by comparing the determined one or more machining parameters with at least one of: dataset of another user, historical data of a same user, and default parameters recommended by a manufacturer of the machining tool;
tagging the determined one or more machining parameters based on a threshold to not be used for training process and given less weight for purposes of determining future predictions;
determining a machining workflow prediction in a computer aided manufacturing (CAM) environment based on the selected one or more sequences of machining types, the selected one or more tools, and the determined and untagged one or more machining parameters, thereby determining the machining workflow prediction based on a user's skill set and experiential habits.