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3D printer calibration and control — Voxel8, Inc. (US10394202B2)

Voxel8, Inc. · Google Patents

Google Patents · Patents · License: Open Access

patent, google patents, intellectual property, US10394202B2, Voxel8, Inc., John Minardi, en, 2019

ABSTRACT

Abstract

Calibration and control of a 3D printing device is disclosed. In one aspect, sensor-based feedback may be used to iteratively determine and align line height calibration settings of the 3D printing device. In another aspect, the 3D printing device may include an instruction pre-processor to detect placeholder data in received machine instructions and to replace the placeholder data with instructions that are executable by the 3D printing device.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional Patent Application No. 62/208,222, filed Aug. 21, 2015 and entitled âClosed- Loop 3D Printing Incorporating Sensor Feedback,â U.S. Provisional Patent Application No. 62/340,389, filed May 23, 2016 and entitled âSYSTEM AND METHOD TO CONTROL A THREE-DIMENSIONAL (3D) PRINTER,â U.S. Provisional Patent Application No. 62/340,421, filed May 23, 2016 and entitled âSYSTEM AND METHOD TO CONTROL A THREE-DIMENSIONAL (3D) PRINTER,â U.S. Provisional Patent Application No. 62/340,453, filed May 23, 2016 and entitled âSYSTEM AND METHOD TO CONTROL A THREE-DIMENSIONAL (3D) PRINTING DEVICE,â U.S. Provisional Patent Application No. 62/340,436, filed May 23, 2016 and entitled âSYSTEM AND METHOD TO CONTROL A THREE-DIMENSIONAL (3D) PRINTER,â and U.S. Provisional Patent Application No. 62/340,432, filed May 23, 2016 and entitled â3D PRINTER CALIBRATION AND CONTROL,â the contents of each of the aforementioned applications are expressly incorporated herein by reference in their entirety.

FIELD OF THE DISCLOSURE

The present disclosure is generally related to calibrating and/or controlling a three-dimensional (3D) printer.

BACKGROUND

Prior to initiation of printing, some 3D printers, e.g., printer hardware and software, may build a computational model of each âsliceâ or âlayerâ of the entire 3D printing process. For example, some 3D printers may select printer parameters, e.g., nozzle temperature, layer height, in-fill patterns, maximum speed, maximum acceleration, and so forth, beforehand, taking into account expected properties of the input materials. However, such 3D printers may not account for variances of the material properties, e.g., when a new source material is input into the printer system, and/or the impact of the interaction between the new input materials and the various components of the 3D printer or the environment the 3D printer is in.

For 3D printers that do provide for sensing material and/or tool properties during printing, optical imaging devices, e.g., cameras, may be used. For example, optical imaging devices may be used to identify surface defects, dimensional inaccuracies that fall outside of acceptable tolerances, and similar failure modes. The solution for these failure modes may include interrupting the printing process, shutting down the 3D printer, and removing the defective printed object.

SUMMARY

The present disclosure may enable a reliable 3D printer and printing system adapted to print objects, which satisfy required tolerances, by incorporating sensor-based feedback to update the internal path-plan representation mid-print or on-the-fly, to produce objects in an efficient manner with a high throughput.

Calibration and control systems and methods for 3D printers are also described herein. For example, in some aspects, a sensor (e.g., profilometer) may be used to determine print layer height during a calibration process at a 3D printer, including 3D printers having multiple extruders (and, by extension, multiple available printing materials for deposition). To illustrate, in some aspects, a profilometer may be used to iteratively determine a âzeroâ height for a first extruder of the 3D printer that is configured to deposit a first material (e.g., a plastic). After determining the âzeroâ height for the first extruder, a layer of the first material may be deposited. The profilometer may then iteratively be used to determine a âzeroâ height for a second extruder of the 3D printer that is configured to deposit a second material (e.g., a material that includes a metal, such as silver). Advantageously, the âzeroâ heights of the two extruders may be aligned during calibration to improve 3D printing performance.

In some aspects, a 3D printer includes an instruction pre-processor (e.g., code monitor) that enables control of certain functions. To illustrate, the 3D printer may support execution of machine instructions represented in a numerical control programming language, such as GCode. The 3D printer may include a monitor, such as a GCode monitor, that is configured to intercept particular data in GCode machine instructions and to cause the 3D printer to perform specific functions in response. To illustrate, when specific keywords or numbers are intercepted, the 3D printer may replace the intercepted instruction(s) with different instructions, may forward the intercepted instruction(s) to a specific component or controller of the 3D printer, etc. The ability to intercept and react to specific keywords or numbers in GCode may provide a layer of software abstraction for the 3D printer. To illustrate, different 3D printers may replace a âwipe toolâ GCode instruction with different instructions that are specific to the different 3D printers. As another example, a 3D printer may recognize specific keyword(s) or number(s) as being directed to a component that is not typically controlled using GCode.

In a first aspect, the a computer-implemented method for 3D printing includes receiving, by a processing device, a 3D model of an object to be printed; receiving, by the processing device, sensed information including a material property(ies) of a material to be three-dimensionally printed; and generating, by the processing device, a set of sensor-based printer control parameters, e.g., a head path and at least one printing property, to print the object based, at least in part, on the sensor input. In some implementations, the method may further include initiating 3D printing of the object in the 3D printer according to the head path-plan; receiving, during 3D printing, information from a sensor(s) associated with the 3D printing; and adjusting a printing property(ies) based on the sensor information. In some variations, the printing property(ies) is adjusted without stopping the 3D printing. In some implementations, the printer includes multiple printing heads and each printing head is adapted to output a material with different material properties.

In some implementations, the printing property(ies) to be modified based on sensor feedback may include head speed, extrusion speed, head temperature, dwell time before printing, dwell time after printing, applied extrusion pressure (which may be applied pneumatically or volumetrically), retraction technique, minimum nozzle size, minimum layer thickness, maximum layer thickness. The input and/or sensed material property(ies) may include one or more of viscosity, density, strength, yield stress, melting temperature, melting pressure, glass transition temperature, average particle size, largest particle size, solvent evaporation rate, and solvent permeability, which may be identified experimentally or theoretically.

In some embodiments, generating a set of sensor-based printer control parameters comprises slicing the 3D model into a number of ordered layers and generating a set of sensor-based printer control parameters for each ordered layer; optimizing printer head travel paths; and/or combining printer head movements with extrusion commands. In some implementations, each ordered layer comprises a polygon(s) and/or a polyline(s).

In some implementations, the method may further include exporting a generated sensor-based printer control parameter to the 3D printer, wherein the sensor-based printer control parameter is storable as a variable; and resolving, manually by a printer operator or automatically by the processing device, the variable into a value set.

In some implementations, the received material property and/or other sensor-based information may include information received from an optical camera, an imaging device, and/or an in-line imaging device, and the method further includes comparing an image recorded by the optical camera, the imaging device, and/or the in-line imaging device to an expected image. In some variations, the method includes adjusting a rate of extrusion, based on the comparison of the recorded and expected images.

In a second aspect, a non-transitory computer program product embodied on a computer-readable medium comprises computer code for 3D printing. In some embodiments, the code includes instructions executable by a processing device for receiving a 3D model of an object to be printed; receiving information including a material property(ies) of a material to be three-dimensionally printed; and generating a set of sensor-based printer control parameters to print the object by a 3D printer based at least in part on a sensor input.

In a third aspect, a 3D printing system includes a processing device, a printer head(s), and a sensor(s), e.g., a force probe, a weight sensor, an optical camera, an imaging device, an in-line imaging device, a profilometer, a laser measurement device, a 3D scanner, and an automatic digital multimeter. In some variations, the processing device is adapted to execute instructions for receiving a 3D model of an object to be printed; receiving information including a material property(ies) of a material to be three-dimensionally printed; and generating a set of sensor-based printer control parameters to print the object by a 3D printer based at least in part on sensor input. In some variations, the processing device is further adapted to execute instructions for initiating 3D printing of the object in the 3D printer; receiving, during 3D printing, information from a sensor(s) associated with the 3D printing; and adjusting a printing property(ies) based on the sensor information. In some variations, the sensor(s) is mountable on a dispensing system.

In some implementations, the processing device is configured to compare an image recorded by an optical camera, an imaging device, and/or an in-line imaging device with an expected image. An extrusion multiplier may be adapted to adjust a rate of extrusion, based on the comparison of the recorded and expected images.

In a fourth aspect, a method includes scanning, by a profilometer of a 3D printing device, at least a region of a deposition platform of the 3D printing device to generate first scan data. The method also includes depositing, by a first extruder of the 3D printing device, a first line of a first material on the region of the deposition platform. The method further includes scanning, by the profilometer, the first line to generate second scan data. The method includes determining a height of the first line based on the first scan data and the second scan data and adjusting a line height calibration setting of the 3D printing device based on the height of the first line.

In a fifth aspect, a computer-readable storage device stores instructions that are executable by a processor to cause the processor to perform operations including receiving first scan data from a profilometer, the first scan data associated with at least a region of a deposition platform. The operations also include receiving second scan data from the profilometer, the second scan data associated with a first line of a first material deposited by a first extruder on the region of the deposition platform. The operations further include determining a height of the first line based on the first scan data and the second scan data and initiating an adjustment of a line height calibration setting associated with the first extruder based on the height of the first line.

In a sixth aspect, a 3D printing device includes a profilometer configured to scan at least a region of a deposition platform to generate first scan data and a first extruder configured to deposit a first line of a first material on the region of the deposition platform. The profilometer is further configured to scan the first line to generate second scan data. The 3D printing device further includes a controller coupled to the profilometer, the first extruder, or both. The controller is configured to determine a height of the first line based on the first scan data and the second scan data and to adjust a line height calibration setting associated with the first extruder based on the height of the first line.

In a seventh aspect, a computing device includes a processor and memory accessible to the processor, the memory storing instructions that are executable by the processor to cause the processor to perform operations including receiving first scan data from a profilometer, the first scan data associated with at least a region of a deposition platform. The operations also include receiving second scan data from the profilometer, the second scan data associated with a first line of a first material deposited by a first extruder on the region of the deposition platform. The operations further include determining a height of the first line based on the first scan data and the second scan data and initiating an adjustment of a line height calibration setting associated with the first extruder based on the height of the first line.

In an eighth aspect, a method includes obtaining, at a 3D printing device, machine instructions to generate a physical model of an object. The method also includes analyzing the machine instructions to detect placeholder data, where the placeholder data identifies a function to be performed by the 3D printing device. The method further includes determining one or more instructions that are executable to cause the 3D printing device to perform the function and modifying the machine instructions by replacing the placeholder data with the one or more instructions.

In a ninth aspect, a computer-readable storage device stores instructions that are executable by a processor to cause the processor to perform operations including obtaining machine instructions to generate a physical model of an object. The operations also include analyzing the machine instructions to detect placeholder data, where the placeholder data identifies a function to be performed by a 3D printing device. The operations further include determining one or more instructions that are executable to cause the 3D printing device to perform the function and modifying the machine instructions by replacing the placeholder data with the one or more instructions.

In a tenth aspect, a 3D printing device includes one or more extruders configured to deposit material on a deposition platform and an actuator coupled to the one or more extruders, the deposition platform, or a combination thereof. The 3D printing device also includes a controller configured to control the actuator and an interface configured to receive machine instructions to generate a physical model of an object. The 3D printing device further includes an instruction pre-processor configured to detect placeholder data in the machine instructions, to determine one or more instructions that are executable by the controller to perform a function identified by the placeholder data, to modify the machine instructions by replacing the placeholder data with the one or more instructions, and to send the modified machine instructions to the controller.

In an eleventh aspect, a computing device includes a processor and a memory accessible to the processor, the memory storing instructions that are executable by the processor to cause the processor to perform operations including generating placeholder data that identifies a function to be performed by a 3D printing device. The operations also include processing the model data and the placeholder data to generate machine instructions executable by the 3D printing device to generate a physical model of the object, where the machine instructions include the placeholder data.

In a twelfth aspect, a method includes obtaining model data specifying a 3D model of an object. The method also includes generating placeholder data that identifies a function to be performed by a 3D printing device. The method further includes processing the model data and the placeholder data to generate machine instructions executable by the 3D printing device to generate a physical model of the object, where the machine instructions include the placeholder data.

BRIEF DESCRIPTION OF DRAWINGS

The foregoing features and advantages of embodiments of the disclosure will become more apparent from a reading of the following description in connection with the accompanying drawings, in which:

FIG. 1 shows a block diagram of an illustrative embodiment of a 3D printing system in accordance with some aspects of the present disclosure;

FIG. 2 shows a block diagram of an illustrative embodiment of a 3D printer in the printing system of FIG. 1 ;

FIG. 3 shows a perspective view of an illustrative embodiment

CROSS-REFERENCE TO RELATED APPLICATIONS

FIELD OF THE DISCLOSURE

The present disclosure is generally related to calibrating and/or controlling a three-dimensional (3D) printer.

BACKGROUND

SUMMARY

BRIEF DESCRIPTION OF DRAWINGS

The foregoing features and advantages of embodiments of the disclosure will become more apparent from a reading of the following description in connection with the accompanying drawings, in which:

FIG. 1 shows a block diagram of an illustrative embodiment of a 3D printing system in accordance with some aspects of the present disclosure;

FIG. 2 shows a block diagram of an illustrative embodiment of a 3D printer in the printing system of FIG. 1 ;

FIG. 3 shows a perspective view of an illustrative embodiment of the 3D printer of FIG. 2 ;

FIG. 4A shows a side view of an illustrative embodiment of a dispensing system in the 3D printer of FIG. 3 ;

FIG. 4B shows a perspective view of the illustrative embodiment of a dispensing system of FIG. 4A ;

FIG. 5 shows a perspective view of an illustrative embodiment of a dispensing tip or nozzle for the dispensing system of FIG. 3 ;

FIG. 6 shows a flow chart of an illustrative embodiment of a 3D printing method in accordance with some aspects of the present disclosure; and

FIG. 7 shows a diagram of another illustrative embodiment of a 3D printer, such as a 3D printer that may be included in the 3D printing system of FIG. 1 ; and

FIGS. 8, 9, 10, and 11 show illustrative embodiments of operation at a 3D printer.

DETAILED DESCRIPTION

Embodiments of the disclosure include a 3D printer and 3D printing system that include the system, hardware, electronics, input materials, and at least a portion of the software needed to three-dimensionally print an object, and, more specifically, an object comprising at least one material property and, in some implementations, a plurality of input materials having a least one different material property. Advantageously, the 3D electronics printer uses sensor-based data from at least one sensor to update a head path-plan and machine commands to print a 3D object.

Three-Dimensional (3D) Printing System

Referring to FIGS. 1 and 2 , illustrative embodiments of a 3D printing system 100 and an exemplary 3D printer 20 , respectively, are shown. In some embodiments, the system 100 may comprise the 3D printer 20 and a remote server (processing device) 10 that are in communication via a communications network 15 . A communications network 15 generally connects a client with a server, and, in the case of peer-to-peer communications, may connect two peers. Communication may take place via any medium such as a public-switched telephone network (PSTN), a wired or wireless local area network (LAN) or a wired or wireless wide area network (WAN) links (e.g., T1, T3, 56 kb, X.25), broadband connections (e.g., ISDN, Frame Relay, ATM), wireless personal area network (PAN), wireless links (e.g., 802.11, Bluetooth, Zigbee, IrDa, or other suitable protocol), and so on. To exchange data via a communications network 15 , the processing devices and communications network 15 may use various methods, protocols, and standards, including, inter alia, token ring, Ethernet, TCP/IP, UDP, HTTP, FTP, and SNMP. Thus, the communications network 15 may carry, for example, TCP/IP, UDP, OSI or other protocol communications, and HTTP/HTTPS requests made by a Web browser and the connection may be made between the peers and communicated over such TCP/IP networks. Those of ordinary skill in the art can appreciate that plural communications networks 15 may also be used by the remote server 10 and the 3D printer 20 .

The type of communications network 15 is not a limitation, however, and any suitable network may be used. Non-limiting examples of networks that can serve as, or be part of, the communications network 15 include a wireless or wired Ethernet-based intranet, a LAN or WAN, and/or the global communications network known as the World Wide Web and/or the Internet, which may accommodate many different communications media and protocols.

When used in a LAN networking environment, processing devices may be connected to the LAN through a network interface or adapter. When used in a WAN networking environment, processing devices typically include a modem or other communication mechanism. Modems may be internal or external, and may be connected to a system bus, e.g., via a user-input interface, or other appropriate mechanism. Processing devices may also be connected over the Internet, an Intranet, Extranet, Ethernet, or any other system that provides communications. Furthermore, components of the system may communicate through a combination of wired or wireless paths.

Those skilled in the art may appreciate that embodiments of the disclosure may be practiced with various computer system configurations, including multiprocessor systems, microprocessor-based or programmable consumer electronics, minicomputers, mainframe computers, and the like. Embodiments of the disclosure may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through the communications network 15 . In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.

In some embodiments, each of the 3D printer 20 and the remote server 10 may include a processing device

12 , 22 ; a data storage device 14 , 24 ; memory

16 , 26 ; and a user interface 18 , 28 . The processing device

12 , 22 may comprise an operating system that manages at least a portion of the hardware elements included therein.

The processing device

12 , 22 may be structured and arranged to perform or execute a series of instructions, e.g., an application, an algorithm, a driver program, and the like, that result in manipulated data. There are many examples of processing devices

12 , 22 including, for the purpose of illustration and not limitation, network appliances, personal computers, workstations, mainframes, networked clients, servers, media servers, application servers, database servers, and web servers. The processing device

12 , 22 may be a commercially available processor such as an Intel Core, Motorola PowerPC, MIPS, UltraSPARC, or Hewlett-Packard PA-RISC processor, but also may be any type of available processing device

12 , 22 or controller.

Certain aspects and functions of the present disclosure may be located on a single processing device

12 , 22 or system 100 or may be distributed among a plurality of processing devices

12 , 22 or systems 100 connected to one or more communications networks 15 . For example, various aspects and functions may be distributed among one or more processing systems 22 configured to provide a service to one or more client computers, or to perform an overall task as part of a distributed system. Additionally, aspects may be performed on a client- server 12 or multi-tier system that includes components distributed among one or more server systems 22 that perform various functions. Thus, the disclosure is not limited to executing on any particular system or group of systems. Moreover, aspects may be implemented in software, hardware or firmware, or any combination thereof. Thus, aspects in accord with the present disclosure may be implemented within methods, acts, systems, system elements, and components using a variety of hardware and software configurations, and the disclosure is not limited to any particular distributed architecture, network, or communication protocol.

Typically, a processing device

12 , 22 executes an operating system that may be, for example, a Windows-based operating system (e.g., Windows 7, Windows 2000 (Windows ME), Windows XP operating systems, and the like) available from the Microsoft Corporation of Seattle, Wash.; a MAC OS System X operating system available from Apple Computer of Cupertino, Calif.; a Linux-based operating system distributions (e.g., the Enterprise Linux operating system) available from Red Hat, Inc. of Raleigh, N.C.; or a UNIX operating system available from various sources. Many other operating systems may be used, and embodiments are not limited to any particular implementation. Operating systems conventionally may be stored in memory

16 , 26 .

The processing device

12 , 22 and the operating system together define a processing platform for which application programs in high-level programming languages may be written. These component applications may be executable, intermediate (for example, Câ) or interpreted code which communicate over a communication network (for example, the Internet) using a communication protocol (for example, TCP/IP). Similarly, aspects in accordance with the present disclosure may be implemented using an object-oriented programming language, such as SmallTalk, Java, C++, Ada, or C# (C-Sharp). Other object-oriented programming languages may also be used. Alternatively, functional, scripting, or logical programming languages may be used. For instance, aspects of the system may be implemented using an existing commercial product, such as, for example, Database Management Systems such as SQL Server available from Microsoft of Seattle, Wash., and Oracle Database from Oracle of Redwood Shores, Calif. or integration software such as Web Sphere middleware from IBM of Armonk, N.Y. However, a processing device

12 , 22 running, for example, SQL Server may be able to support both aspects in accordance with the present disclosure and databases for sundry applications not within the scope of the disclosure. In one or more of the embodiments of the present disclosure, the processing device

12 , 22 may be adapted to execute at least one application, algorithm, driver program, and the like. The applications, algorithms, driver programs, and the like that the processing device

12 , 22 may process and may execute can be stored in memory

16 , 26 .

Memory

16 , 26 may be used for storing programs and data during operation of the processing devices

12 , 22 . Memory

16 , 26 can be multiple components or elements of a data storage device(s) 14 , 24 or, in the alternate, can be stand-alone devices. More particularly, memory

16 , 26 can include volatile storage, e.g., random access memory (RAM), and/or non-volatile storage, e.g., a read-only memory (ROM). The former may be a relatively high performance, volatile, random access memory such as a dynamic random access memory (DRAM) or static memory (SRAM). Various embodiments in accordance with the present disclosure may organize memory

16 , 26 into particularized and, in some cases, unique structures to perform the aspects and functions disclosed herein. Advantageously, memory

16 , 26 may include software for 3D modeling and head path-planning for 3D printing purposes. The software may be uploaded in the memory 16 of the remote server 10 or, in the alternative, in the memory 26 associated with of the 3D printer 20 .

User-input interfaces 18 , 28 , e.g., graphical user interfaces (GUI) and the like, provide a vehicle for human interaction, with a machine, e.g., the processing device

12 , 22 , in which the human user provides input to direct the machine's actions while the machine provides output and other feedback to the user for use in future input. User-input interfaces 18 , 28 are well known to the art and will not be described in detail.

Components of the processing device

12 , 22 may be coupled by an interconnection element such as a bus 19 , 29 . The bus 19 , 29 may include one or more physical busses, e.g., between components that are integrated within a same machine, but may also include any communication coupling between system elements, e.g., specialized or standard computing bus technologies such as IDE, SCSI, PCI, and InfiniBand. Thus, the bus 19 , 29 enables communications, e.g., the transfer of data and instructions, to be exchanged internally, between printer 20 and system 100 components.

Three-Dimensional (3D) Printer

In addition to the processing device 22 , data storage device 24 , memory 26 , and user interface 28 described previously, as shown in FIGS. 2 and 3 , the 3D printer 20 may also include one or more sensors

21 , 23 , a build plate 25 , a multi-axis positioning system 27 , and a dispending system (âprinter headâ) 30 . The build plate 25 may be disposed below the dispensing system 30 and configured to provide a, e.g., planar, surface for 3D printing. In some implementations, the build plate 25 may be supported on a frame, e.g., by a kinematic coupling, to be removable and accurately replaced, even during a build cycle of a single object. In operation, the build plate 25 may translate vertically, e.g., in the z-axis, by a lead screw, ball nut, stepper motor, and the like (e.g., riding along vertically disposed metal rails using spaced brass bushings for low friction and ease of travel). The multi-axis positioning system 27 is structured and arranged to position the dispensing system 30 in multiple axes, e.g., three-axes, relative to the build plate 25 reliably and repeatably.

In some variations, the 3D printer 20 may include one or more sensors

21 , 23 , e.g., a force probe, a weight sensor, an optical camera, an imaging device, an in-line imaging device, a profilometer, a thermometer, a 3D scanner, a laser measurement device, an automatic digital multimeter, and so forth. A first sensor(s) 21 may be configured for sensing one or more properties of extrudable materials, prior to initiation of a printing operation; while a second sensor(s) 23 may be configured for sensing and collecting data on various components of the 3D printer 20 and/or on the print product while the printing operation is on-going. In some embodiments, material property data, e.g., one or more of viscosity, density, strength, yield stress, melting temperature, melting pressure, glass transition temperature, average particle size, largest particle size, solvent evaporation rate, and solvent permeability, may be combined, by at least one of the processing devices

12 , 22 , with printing properties, e.g., head speed, extrusion speed, head temperature, dwell time before printing, dwell time after printing, applied extrusion pressure, retraction technique, minimum nozzle size, minimum layer thickness, maximum layer thickness, and so forth, to compose a head path-plan that includes initial selective printer parameters, e.g., nozzle temperature, layer height, in-fill patterns, maximum speed, maximum acceleration, and so forth.

Referring to FIGS. 3, 4A, and 4B , the dispensing system 30 may include a cartridge holder 31 that is structured and arranged to hold multiple, e.g., two, removable cartridges

32 , 34 , each cartridge

32 , 34 preferably retaining an extrudable material to form the 3D object and, more preferably, retaining materials having at least one different material property, e.g., viscosity, density, strength, yield stress, melting temperature, melting pressure, glass transition temperature, average particle size, largest particle size, solvent evaporation rate, solvent permeability, and so forth, of the extruded materials. For example, in one implementation, one of the removable cartridges 32 may be structured and arranged to extrude a heated filament, e.g., a polymer, a composite, a ceramic, a fused filament fabrication (FFF)/matrix material, a thermoplastic (e.g., ABS, PLA, ULTEM thermoplastic-based filament), and the like, and the other cartridge 34 may be structured and arranged to extrude an electrically-conductive material, e.g., room temperature silver.

More particularly, the first cartridge 32 may be structured and arranged to push or pull a first material, e.g., through a heated end 37 (âhotendâ) of a dispensing tip or nozzle. A heating device heats up the filament sufficiently at the heated end 37 to put it into a liquid or semi-liquid state. While the heating device is heating the extrudable material, heat removal devices, e.g., one or more cooling fans 36 , a heat exchange device, and the like, cools the portion of the first cartridge 32 that is not near the heated end 37 . The multi-axis positioning system 27 moves the dispensing tip or nozzle relative to the build plate 25 to position the dispensing tip or nozzle and to dispense the heated filament, respectively, in a programmed geometry and according to the head path-plan to create the printed object.

The second cartridge 34 may be adapted for dispensing, e.g., pneumatically, a second material, e.g., a mixture of a functional ink, such as conductive, magnetic, dielectric, and/or semiconductor materials (e.g., room temperature silver), and a matrix ink, such as epoxy, silicones, thermoplastic urethane, or combinations thereof, having at least one material property that differs from the first material in the first cartridge 32 . Referring to FIG. 5 , each cartridge

32 , 34 may comprise a hollow dispensing tip or nozzle 38 that is structured and arranged to accurately deliver the extrudable material via an opening 39 at a distal end of the dispensing tip or nozzle 38 . The dimensions of the opening 39 and of the hollow dispensing tip or nozzle 38 may vary depending on the material being extruded and the necessary precision of the build.

Method of Three-Dimensional (3D) Printing

A vast majority of contemporary 3D printers executes printing commands and performs head path-planning using a numerical control programming language known as âGCode.â Indeed, GCode remains an industry standard for controlling automated machine tools, e.g., a 3D printer, during computer-assisted manufacturing. However, different programming techniques may be required to transform user-input parameters into printing parameters, and, moreover, into head path-planning.

Referring to FIG. 6 , an illustrative embodiment of a closed-loop method for 3D printing in accordance with the present disclosure is shown. Once a user designates or selects a material(s) to be extruded via a 3D printing operation (STEP 1 ), the user may obtain, e.g., experimentally, empirically, or theoretically, relevant material properties (STEP 2 ). Some relevant material characteristics or material properties may include, for the purpose of illustration and not limitation: density, strength, viscosity, yield stress, electrical conductivity, thermal conductivity, melting temperature, average particle size, largest particle size, solvent permeability, solvent evaporation rate, glass transition temperature, and various other rheological properties. The relevant material properties, as well as a description of each property, may be input or entered (STEP 3 ), e.g., using a graphical user interface (GUI), into the processing device, or read into the processing device from a file stored in memory.

The user may also upload a 3D model of the object to be printed (STEP 4 ) using the selected extrudable material(s). Advantageously, the 3D model of the object to be printed may be uploaded locally or remotely but processed remotely by the remote server, e.g., using 3D model slicing and head path-planning software. Model slicing processing and path-planning remotely reduce the storage, execution speed, and similar requirements for the local processing device associated with the 3D printer. Notwithstanding, in some variations, processing may be accomplished locally on the 3D printer's processing device. The following description, however, is predicated on remote processing.

The processing device of the remote server may be configured to process the input 3D model and material properties to generate an executable head path-plan (STEP 5 ) suitable for printing and that includes various (output) printing control parameters. Printing control parameters from such user input properties may include, for the purpose of illustration and not limitation: dispensing tip or nozzle speed, extrusion speed, dispensing tip or nozzle temperature, dwell time before printing, dwell time after printing, pneumatically-applied extrusion pressure, volumetrically-applied extrusion pressure, minimum nozzle size, minimum layer thickness, maximum layer thickness, minimum part density, maximum part height, retraction technique employed, and various other printing parameters.

Generating a computer-executable path-plan (STEP 5 ) suitable for 3D printing and that takes into account the various printing control parameters may include sub-steps comprising standard data flow for slicing the model associated with additive manufacturing, viz. prepare the 3D mesh for each layer or slice (STEP 5 A), prepare polygon outlines for each slice (STEP 5 B), offset the polygons on each slice (<figure-callout id="5C" label="STEP" filenames="US10394202-20

CLAIMS

Claims ( 7 )

What is claimed is:

1. A method comprising:

scanning, by a profilometer of a three-dimensional (3D) printing device, at least a region of a deposition platform of the 3D printing device to generate first scan data;

depositing, by a first extruder of the 3D printing device, a first line of a first material on the region of the deposition platform;

scanning, by the profilometer, the first line to generate second scan data;

determining a height of the first line based on the first scan data and the second scan data;

adjusting a line height calibration setting of the 3D printing device based on the height of the first line;

after adjusting the line height calibration setting of the 3D printing device, depositing, by the first extruder, a portion of the first material on the region of the deposition platform to form at least one layer of the first material;

depositing, by a second extruder of the 3D printing device, a second line of a second material on the at least one layer of the first material;

scanning, by the profilometer, the second line to generate third scan data;

determining a height of the second line based on the third scan data; and

adjusting a second line height calibration setting of the 3D printing device based on the height of the second line; and

after forming the at least one layer of the first material, scanning, by the profilometer, the at least one layer of the first material to generate fourth scan data, wherein the height of the second line is determined further based on the fourth scan data.

2. The method of claim 1 , further comprising, after adjusting the line height calibration setting of the 3D printing device, iteratively, until a criterion is satisfied:

depositing an additional line of the first material on the region of the deposition platform; determining a height of the additional line based on scan data; and

adjusting the line height calibration setting,

wherein the criterion is satisfied when the line height calibration setting is determined to differ from a height of a particular line by an amount that is less than a threshold.

3. The method of claim 1 , further comprising, before depositing the first line, determining a surface profile of the deposition platform, wherein determining the height of the first line based on the first scan data and the second scan data includes accounting for the surface profile of the deposition platform.

4. The method of claim 1 , further comprising filtering the first scan data and the second scan data using a median filtering process before determining the height of the first line.

5. The method of claim 1 , wherein the first material is different from the second material.

6. The method of claim 1 , wherein the height of the second line is determined further based on the line height calibration setting.

7. The method of claim 1 , further comprising, after adjusting the second line height calibration setting of the 3D printing device, iteratively, until a criterion is satisfied:

depositing an additional line of the second material on the at least one layer of the first material;

determining a height of the additional line based on scan data; and

adjusting the second line height calibration setting,

wherein the criterion is satisfied when the second line height calibration setting is determined to differ from a height of a particular line of the second material by an amount that is less than a threshold.

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