A powder production method includes providing an elongated workpiece and repeatedly contacting an outer surface of the elongated workpiece with a reciprocating cutter according to a predetermined at least one frequency to produce a powder. The powder includes a plurality of particles, wherein at least 95% of the produced particles have a diameter or maximum dimension ranging from about 10 μm to about 200 μm. A system for producing powders having a plurality of particles including a cutter and at least one controller is also provided herein.

A powder production method includes providing an elongated workpiece and repeatedly contacting an outer surface of the elongated workpiece with a reciprocating cutter according to a predetermined at least one frequency to produce a powder. The powder includes a plurality of particles, wherein at least 95% of the produced particles have a diameter or maximum dimension ranging from about 10 μm to about 200 μm. A system for producing powders having a plurality of particles including a cutter and at least one controller is also provided herein.

Provided is a method for manufacturing material powder for metal laminating modelling, in which a virgin material is manufactured based on the particle size distribution of the virgin material being an unused material powder, and the fluidity of an unsintered reused material after the virgin material is reused a predetermined number of times by a metal laminating modelling device, so that the particle size distribution of the virgin material corresponds to the fluidity of the reused material that is equal to or greater than a predetermined standard value. Silica particles may be added to the virgin material.

Provided is a method for manufacturing material powder for metal laminating modelling, in which a virgin material is manufactured based on the particle size distribution of the virgin material being an unused material powder, and the fluidity of an unsintered reused material after the virgin material is reused a predetermined number of times by a metal laminating modelling device, so that the particle size distribution of the virgin material corresponds to the fluidity of the reused material that is equal to or greater than a predetermined standard value. Silica particles may be added to the virgin material.

Provided is a method for manufacturing material powder for metal laminating modelling, in which a virgin material is manufactured based on the particle size distribution of the virgin material being an unused material powder, and the fluidity of an unsintered reused material after the virgin material is reused a predetermined number of times by a metal laminating modelling device, so that the particle size distribution of the virgin material corresponds to the fluidity of the reused material that is equal to or greater than a predetermined standard value. Silica particles may be added to the virgin material.

A printer includes a heat control device configured to cause a temperature of a part that is printed by the printer to remain within a predetermined range as a height of the part increases from about 0 mm to about 30 mm. The predetermined range is from about 545° C. to about 600° C. The heat control device includes a heat plate that is configured to generate heat in a downward direction toward the part.

A printer includes a heat control device configured to cause a temperature of a part that is printed by the printer to remain within a predetermined range as a height of the part increases from about 0 mm to about 30 mm. The predetermined range is from about 545° C. to about 600° C. The heat control device includes a heat plate that is configured to generate heat in a downward direction toward the part.

An expeditionary additive manufacturing (ExAM) system [10] for manufacturing metal parts [20] includes a mobile foundry system [12] configured to produce an alloy powder [14] from a feedstock [16], and an additive manufacturing system [18] configured to fabricate a part using the alloy powder [14]. The additive manufacturing system [18] includes a computer system [50] having parts data and machine learning programs in signal communication with a cloud service. The parts data [56] can include material specifications, drawings, process specifications, assembly instructions, and product verification requirements for the part [20]. An expeditionary additive manufacturing (ExAM) method for making metal parts [20] includes the steps of transporting the mobile foundry system [12] and the additive manufacturing system [18] to a desired location; making the alloy powder [14] at the location using the mobile foundry system; and building a part [20] at the location using the additive manufacturing system [18].

An expeditionary additive manufacturing (ExAM) system [10] for manufacturing metal parts [20] includes a mobile foundry system [12] configured to produce an alloy powder [14] from a feedstock [16], and an additive manufacturing system [18] configured to fabricate a part using the alloy powder [14]. The additive manufacturing system [18] includes a computer system [50] having parts data and machine learning programs in signal communication with a cloud service. The parts data [56] can include material specifications, drawings, process specifications, assembly instructions, and product verification requirements for the part [20]. An expeditionary additive manufacturing (ExAM) method for making metal parts [20] includes the steps of transporting the mobile foundry system [12] and the additive manufacturing system [18] to a desired location; making the alloy powder [14] at the location using the mobile foundry system; and building a part [20] at the location using the additive manufacturing system [18].

An optical manufacturing process sensing and status indication system is taught that is able to utilize optical emissions from a manufacturing process to infer the state of the process. In one case, it is able to use these optical emissions to distinguish thermal phenomena on two timescales and to perform feature extraction and classification so that nominal process conditions may be uniquely distinguished from off-nominal process conditions at a given instant in time or over a sequential series of instants in time occurring over the duration of the manufacturing process. In other case, it is able to utilize these optical emissions to derive corresponding spectra and identify features within those spectra so that nominal process conditions may be uniquely distinguished from off-nominal process conditions at a given instant in time or over a sequential series of instants in time occurring over the duration of the manufacturing process.