Methods and apparatus for machine learning predictions and multi-objective optimization of manufacturing processes

A non-transitory computer readable medium storing code representing a plurality of processor-executable instructions, the code comprising code to cause the processor to:

• receive, at a compute device, a manufacturing request that includes an electronic file with a digital model representative of a physical object;
• determine from the digital model a set of features associated with the physical object;
• produce at least one predictive value for the manufacturing request based on at least one regression machine learning model and the set of features associated with the physical object;
• and
• generate a response based on (1) the at least one predictive value for the manufacturing request, and (2) a multi-objective optimization model, the response including a set of attributes associated with a manufacture process of the physical object, the set of attributes complying with a multi-objective condition satisfied in the multi-objective optimization model.

A method, comprising:

• receiving a manufacturing request including an electronic file with a digital model representative of a physical object;
• determining from the digital model a set of features associated with the physical object;
• producing a set of predictive values for the manufacturing request based on a set of regression machine learning models and the set of features associated with the physical object;
• and
• generating a response including a set of attributes associated with a manufacture process of the physical object based at least on the set of predictive values and a multi-objective optimization model, the response complying with a selected multi-objective condition satisfied in the multi-objective optimization model.