Abstract: In some examples, a distribution of values of a property of a given layer to be printed as part of three-dimensional (3D) printing is predicted, wherein the predicting is based on a distribution of values of the property in a previous layer that has been printed as part of the 3D printing. 3D printing of an object is controlled based on the predicted distribution of values of the property of the given layer.

Abstract: A system and method for providing three dimensional printing production quality prediction is described herein. The system may include logic to scan a region of interest associated with a layer of a plurality of parts during printing to obtain an input for the region of interest and compute an input metric associated with the layer based on the input. In response to an initial set of print jobs, at least a portion of the plurality of parts is mechanically tested to determine at least one output. In response to a production print job, a likelihood of a part of the plurality of parts to satisfy a quality specification is predicted by inputting the input metric to at least one machine learning function comprising the at least one output, wherein the at least one machine learning function is trained during the initial set of print jobs.

Abstract: In some examples, a request to print a first three-dimensional (3D) part is received. In response to determining that the first 3D part is not similar to any 3D part referred to by an information base, a representation of the first 3D part is extracted, an indication to conduct an operation to produce a design rule for the first 3D part is sent. In response to determining that the first 3D part is similar to a matching 3D part referred to by the information base, a design rule for the matching 3D part is retrieved to print the first 3D part, where the design rule for the matching 3D part specifies a dependency of a property of the matching 3D part on an aspect associated with printing the matching 3D part.

Abstract: A system and method for providing three dimensional printing production quality prediction is described herein. The system may include logic to scan a region of interest associated with a layer of a plurality of parts during printing to obtain an input for the region of interest and compute an input metric associated with the layer based on the input. In response to an initial set of print jobs, at least a portion of the plurality of parts is mechanically tested to determine at least one output. In response to a production print job, a likelihood of a part of the plurality of parts to satisfy a quality specification is predicted by inputting the input metric to at least one machine learning function comprising the at least one output, wherein the at least one machine learning function is trained during the initial set of print jobs.

Abstract: In some examples, a request to print a first three-dimensional (3D) part is received. In response to determining that the first 3D part is not similar to any 3D part referred to by an information base, a representation of the first 3D part is extracted, an indication to conduct an operation to produce a design rule for the first 3D part is sent. In response to determining that the first 3D part is similar to a matching 3D part referred to by the information base, a design rule for the matching 3D part is retrieved to print the first 3D part, where the design rule for the matching 3D part specifies a dependency of a property of the matching 3D part on an aspect associated with printing the matching 3D part.

Abstract: In some examples, a distribution of values of a property of a given layer to be printed as part of three-dimensional (3D) printing is predicted, wherein the predicting is based on a distribution of values of the property in a previous layer that has been printed as part of the 3D printing. 3D printing of an object is controlled based on the predicted distribution of values of the property of the given layer.