WO2020046290A1 - Tolérancement fonctionnel permettant une conception et une planification de processus de fabrication d'objets fabriqués de manière additive - Google Patents

Tolérancement fonctionnel permettant une conception et une planification de processus de fabrication d'objets fabriqués de manière additive Download PDF

Info

Publication number
WO2020046290A1
WO2020046290A1 PCT/US2018/048514 US2018048514W WO2020046290A1 WO 2020046290 A1 WO2020046290 A1 WO 2020046290A1 US 2018048514 W US2018048514 W US 2018048514W WO 2020046290 A1 WO2020046290 A1 WO 2020046290A1
Authority
WO
WIPO (PCT)
Prior art keywords
design
functional
computer
processor
simulation
Prior art date
Application number
PCT/US2018/048514
Other languages
English (en)
Inventor
Suraj Ravi MUSUVATHY
Erhan Arisoy
Mark R. BURHOP
Pranav Srinivas KUMAR
Original Assignee
Siemens Aktiengesellschaft
Siemens Corporation
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Siemens Aktiengesellschaft, Siemens Corporation filed Critical Siemens Aktiengesellschaft
Priority to PCT/US2018/048514 priority Critical patent/WO2020046290A1/fr
Publication of WO2020046290A1 publication Critical patent/WO2020046290A1/fr

Links

Classifications

    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B33—ADDITIVE MANUFACTURING TECHNOLOGY
    • B33Y—ADDITIVE MANUFACTURING, i.e. MANUFACTURING OF THREE-DIMENSIONAL [3-D] OBJECTS BY ADDITIVE DEPOSITION, ADDITIVE AGGLOMERATION OR ADDITIVE LAYERING, e.g. BY 3-D PRINTING, STEREOLITHOGRAPHY OR SELECTIVE LASER SINTERING
    • B33Y50/00—Data acquisition or data processing for additive manufacturing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • G06F30/23—Design optimisation, verification or simulation using finite element methods [FEM] or finite difference methods [FDM]

Definitions

  • the present invention relates generally to additive manufacturing, in particular computer-aided design of additive manufactured products.
  • Additive manufacturing (also referred to as 3D printing) involves processes for the production of three-dimensional (3D) articles through the incremental depositing and bonding of materials. Additive manufacturing may benefit from improvements.
  • a method includes creating, using a processor, a design for a part.
  • the method further includes specifying, using the processor, one or more functional tolerances for mechanical properties associated with the part.
  • the method additionally includes simulating, using the processor, operation of the part.
  • the method further includes verifying, using the processor, that the design meets design goals associated with the one or more functional tolerance in response to the simulation.
  • a system in one or more other example embodiments, includes a 3D printer and a computing device that includes at least one memory and processor configured to create a design for a part.
  • the processor is further operable to specify one or more functional tolerances for mechanical properties associated with the part.
  • the processor is further operable to simulate operation of the part.
  • the processor is further operable to verify that the design meets design goals associated with the one or more functional tolerance in response to the simulation.
  • a computer program product in one or more other example embodiments, includes a non-transitory storage medium readable by a processing circuit, the storage medium storing instructions executable by the processing circuit to cause a method to be performed.
  • the method includes creating a design for a part.
  • the method further includes specifying one or more functional tolerances for mechanical properties associated with the part.
  • the method additionally includes simulating operation of the part.
  • the method includes verifying that the design meets design goals associated with the one or more functional tolerance in response to the simulation.
  • FIG. 1 is a functional block diagram of a system that facilitates additive manufacturing
  • FIG. 2 is a schematic diagram of an illustrative architecture according to one or more embodiments;
  • FIG. 3 depicts a flow diagram of a method for specifying and evaluating functional tolerances for additively manufactured parts according to one or more embodiments;
  • FIG. 4 depicts a flow diagram of a method for manufacturing an additively manufactured part using functional tolerances according to one or more embodiments.
  • FIG. 1 illustrates an exemplary additive manufacturing system 100.
  • additive manufacturing processes include fused deposition modeling, fused filament fabrication, robocasting, electron beam freeform fabrication, direct metal laser sintering, electron-beam melting, selective laser melting, selective heat sintering, selective laser sintering, and stereo lithography. Many of these processes involve depositing and melting/softening/bonding materials in selective locations layer by layer to build up the desired 3D article.
  • a non-exhaustive list of example materials that may be used in additive manufacturing includes metals, thermoplastics and ceramics.
  • Additive manufacturing processes typically employ machines specifically configured to carry out their respective processes, which are generally referred to as 3D printers or additive machines. However, it should be appreciated that some 3D printers may further be capable of machining/subtractive processes as well and correspond to hybrid additive/subtractive machines.
  • the system 100 includes at least one processor 102 operatively configured to generate instructions 104 usable by a 3D printer 106 to control the operation of the 3D printer 106 in order to build a part 120 via additive manufacturing.
  • Various software components e.g., programs, modules, applications
  • One or more computing devices 108 which may or may not be external to the 3D printer 106, can be used to generate a 3D model 126 of the part 120.
  • the instructions 104 can have a G-code format or other numerical control (NC) programming language format.
  • the 3D printer 106 can include a deposition head 112 and a build plate 114.
  • the deposition head 112 can include an integrated heat source 116 such as a laser (or electrode) that is operative to melt/soften material 118 such as powdered metal (or metal wire) that can be provided from the deposition head 112.
  • the 3D printer 106 can be operative to build the part 120 up from the build plate 114 in a series of layers 122 via depositing a layer 122 of material 118 on top of the series of layers 122 in a build direction 130.
  • the deposition head 112 can simultaneously melt/soften and output a continuous flow of material 118 that bonds to the build plate and/or previously applied layers 122 that make up the part 120.
  • the material 118 may correspond to a metal (in a powder or wire form).
  • the 3D printer 106 includes a controller 124 that can control the operation of hardware components (e.g., motors, electrical circuits and other components) of the 3D printer in order to selectively move the deposition head and/or the build plate in order to deposit material in the various patterns.
  • Controller 124 may include at least one processor that is operative responsive to software and/or firmware stored in the 3D printer or received from the one or more computing devices 108 to control the hardware components of the 3D printer (e.g., the deposition head and heat source).
  • the controller 124 can additionally be operative to control the hardware of the 3D printer by reading and interpreting the generated instructions 104.
  • the generated instructions 104 can be provided to or acquired by the controller 124 over a network connection.
  • the controller 124 can include a wired or wireless network interface component (not shown) operative to receive the instructions.
  • the one or more computing devices 108 are operative to receive a 3D model 126 of a part and/or facilitate the creation of the 3D model 126 and generate the instructions 104 based on the 3D model 126 of the part.
  • the 3D model 126 is a geometric model that includes geometric dimensioning and tolerancing (GD&T) of the part to be manufactured.
  • the geometric model can be created using design software, which is then converted to a finite element analysis (FEA) model.
  • the geometric model can be used to verify a desired form and fit prior to producing the part.
  • the FEA model can be used in a simulation to verify the mechanical performance of the part.
  • parameters can be included that relate to thermal response data that defines how an additive manufacturing material designated to be used retains heat, reacts at different temperatures, cools as a function of other heated or cooled layers, or otherwise.
  • the simulation parameters can also include structural load information for the part, such as weight, mass, density, or other parameters for specific points of the part, the material to be used to manufacture the part, and others.
  • additively manufactured parts face additional issues in which simply using GD&T can result in manufactured parts that do not function as desired.
  • additive manufacturing there are additional factors that are not currently considered when using traditional materials and processes. For example, an additive manufacturing process plan has a significant impact on a material micro structure in localized regions of a part, and subsequently the final functional properties of the part once manufactured.
  • additively manufactured parts cannot currently be manufactured to the precision of machine or casted parts, in which precision can be on the order of microns.
  • a technical package used to create an additive manufactured part can be enhanced by adding functional tolerances and material properties for the part to the technical package which can be used to evaluate whether a design will satisfy desired functional aspects (i.e., how the part should perform in operation) in a simulation, in addition to the form and fit included in a traditional technical package.
  • FIG. 2 is a schematic diagram of an illustrative architecture 200 in accordance with one or more example embodiments of the disclosure.
  • the architecture 200 can include one or more optimization servers 202 and one or more 3D printers 204. While 3D printers 204 and/or multiple servers 202 can form part of a networked architecture 200, these components will be described in the singular hereinafter for ease of explanation. However, it should be appreciated that any functionality described in connection with the server 202 can be distributed among multiple servers 202.
  • a 3D printer 204 can include, for example, any of a variety of sensors and components as described in FIG. 1 that are configured to additively manufacture one or more parts (part).
  • the server 202 can be configured to communicate with a 3D printer 204 via one or more networks 206 which can include, but are not limited to, any one or more different types of communications networks such as, for example, cable networks, public networks (e.g., the Internet), private networks (e.g., frame-relay networks), wireless networks, cellular networks, telephone networks (e.g., a public switched telephone network), or any other suitable private or public packet- switched or circuit-switched networks.
  • the network(s) 206 can have any suitable communication range associated therewith and can include, for example, global networks (e.g., the Internet), metropolitan area networks (MANs), wide area networks (WANs), local area networks (LANs), or personal area networks (PANs).
  • the network(s) 206 can include communication links and associated networking devices (e.g., link-layer switches, routers, etc.) for transmitting network traffic over any suitable type of medium including, but not limited to, coaxial cable, twisted-pair wire (e.g., twisted-pair copper wire), optical fiber, a hybrid fiber-coaxial (HFC) medium, a microwave medium, a radio frequency communication medium, a satellite communication medium, or any combination thereof.
  • coaxial cable twisted-pair wire (e.g., twisted-pair copper wire)
  • optical fiber e.g., twisted-pair copper wire
  • HFC hybrid fiber-coaxial
  • the server 202 can include one or more processors (processor(s)) 208, one or more memory devices 210 (generically referred to herein as memory 210), one or more input/output (“I/O”) interface(s) 212, one or more network interfaces 214, and data storage 216.
  • the server 202 can further include one or more buses 234 that can functionally couple various components of the server 202.
  • the bus(es) 234 can include at least one of a system bus, a memory bus, an address bus, or a message bus, and may permit exchange of information (e.g., data (including computer-executable code), signaling, etc.) between various components of the server 202.
  • the bus(es) 234 can include, without limitation, a memory bus or a memory controller, a peripheral bus, an accelerated graphics port, and so forth.
  • the bus(es) 234 can be associated with any suitable bus architecture including, without limitation, an Industry Standard Architecture (ISA), a Micro Channel Architecture (MCA), an Enhanced ISA (EISA), a Video Electronics Standards Association (VESA) architecture, an Accelerated Graphics Port (AGP) architecture, a Peripheral Component Interconnects (PCI) architecture, a PCI-Express architecture, a Personal Computer Memory Card International Association (PCMCIA) architecture, a Universal Serial Bus (USB) architecture, and so forth.
  • ISA Industry Standard Architecture
  • MCA Micro Channel Architecture
  • EISA Enhanced ISA
  • VESA Video Electronics Standards Association
  • AGP Accelerated Graphics Port
  • PCI Peripheral Component Interconnects
  • PCMCIA Personal Computer Memory Card International Association
  • USB Universal Serial Bus
  • the memory 210 of the server 202 can include volatile memory (memory that maintains its state when supplied with power) such as random access memory (RAM) and/or non-volatile memory (memory that maintains its state even when not supplied with power) such as read-only memory (ROM), flash memory, ferroelectric RAM (FRAM), and so forth.
  • volatile memory memory that maintains its state when supplied with power
  • non-volatile memory memory that maintains its state even when not supplied with power
  • ROM read-only memory
  • FRAM ferroelectric RAM
  • Persistent data storage can include non-volatile memory.
  • volatile memory can enable faster read/write access than non-volatile memory.
  • certain types of non-volatile memory e.g., FRAM
  • FRAM can enable faster read/write access than certain types of volatile memory.
  • the memory 210 can include multiple different types of memory such as various types of static random access memory (SRAM), various types of dynamic random access memory (DRAM), various types of unalterable ROM, and/or writeable variants of ROM such as electrically erasable programmable read-only memory (EEPROM), flash memory, and so forth.
  • the memory 210 can include main memory as well as various forms of cache memory such as instruction cache(s), data cache(s), translation lookaside buffer(s) (TLBs), and so forth.
  • cache memory such as a data cache can be a multi-level cache organized as a hierarchy of one or more cache levels (Ll, L2, etc.).
  • the data storage 216 can include removable storage and/or non-removable storage including, but not limited to, magnetic storage, optical disk storage, and/or tape storage.
  • the data storage 216 can provide non-volatile storage of computer-executable instructions and other data.
  • the memory 210 and the data storage 216, removable and/or non-removable, are examples of computer-readable storage media (CRSM) as that term is used herein.
  • CRSM computer-readable storage media
  • the data storage 216 can store computer-executable code, instructions, or the like that can be loadable into the memory 210 and executable by the processor(s) 208 to cause the processor(s) 208 to perform or initiate various operations.
  • the data storage 216 can additionally store data that can be copied to memory 210 for use by the processor(s) 208 during the execution of the computer-executable instructions.
  • output data generated as a result of execution of the computer-executable instructions by the processor(s) 208 can be stored initially in memory 210, and may ultimately be copied to data storage 216 for non-volatile storage.
  • the data storage 216 can store one or more operating systems (O/S) 230; one or more database management systems (DBMS) 232; and one or more program modules, applications, engines, computer-executable code, scripts, or the like such as, for example, 3D modeling and simulation engine 218, which may, in turn, include one or more sub-modules such as, for example, a part design module 220, a finite element modeling module 222, and a simulation module 224.
  • Any of the components depicted as being stored in data storage 216 can include any combination of software, firmware, and/or hardware.
  • the software and/or firmware can include computer- executable code, instructions, or the like that can be loaded into the memory 210 for execution by one or more of the processor(s) 208 to perform any of the operations described earlier in connection with correspondingly named modules.
  • the 3D modeling and simulation engine 218 can be used to design parts based on geometric dimensioning and tolerancing (GD&T), as well as desired functional tolerances for the parts to account for material variations in materials used to additively manufacture the parts, as well as a process plan providing operational guidelines and constraints for the 3D printer when manufacturing the parts. Accordingly, in addition to simply considering the geometry of a part, the designer can also provide design input related to the functional behavior of the part.
  • GD&T geometric dimensioning and tolerancing
  • desired functional tolerances for the parts to account for material variations in materials used to additively manufacture the parts
  • process plan providing operational guidelines and constraints for the 3D printer when manufacturing the parts. Accordingly, in addition to simply considering the geometry of a part, the designer can also provide design input related to the functional behavior of the part.
  • the part design module 220 can allow a designer to create a 3D technical package for the design of a part desired to be additively manufactured using, for example, 3D printer 204.
  • the design can specify a geometry for the part, a material specification for the part and a process plan.
  • the geometry of the part can entail a desired shape, structures and micro-structures associated with the part and a relative arrangement for the part.
  • the material specification can reflect a desired material used to create the part, as well as related properties, for example, a desired strength for the part, a desired stiffness for the part, material variations associated with the part, cooling properties of the part (efficiency), heat exchange associated with the part, fatigue life for the part or any other physical functional domain in which the part is used.
  • the tolerance can be value of a designer of the part or based on constraints placed on the part due to an overall design goal of an assembly, component or system in which the part has been incorporated in order to achieve a desired performance.
  • the material specification can be mapped to a material microstructure for the part.
  • the material microstructure can be converted to a process structure property (PSP) map.
  • PSP map can be used to determine a localized mechanical behavior of smaller regions within the part.
  • the process plan can include information related to a build orientation for the part, a desired laser level used to construct the part and other aspects of desired operation for the 3D printer 204 while manufacturing the part.
  • the finite element modeling module 222 can be used to perform finite element analysis and modeling for the 3D technical package.
  • Finite element analysis can entail the modeling of parts and systems in a virtual environment, for the purpose of finding and solving potential (or existing) structural or performance issues.
  • a finite element (FE) model includes a system of points, called“nodes”, which form the shape of the design. Connected to these nodes are the finite elements themselves which form the finite element mesh and contain the material and structural properties of the model, defining how the part will react to certain conditions.
  • the simulation module 224 can be used to perform a simulation on a layer by layer basis for the part, based on the FEA model (mesh) of the complete geometry for the part using the specified geometric tolerances and functional tolerances for the part to determine whether the design meets design goals (form, fit and function) specified for the part and/or assembly in which the part is incorporated.
  • the simulation module 224 can output the computed geometric properties and functional properties associated with the simulated design, which can be compared to a set of nominal geometric and functional tolerances assigned to the part by the designer and/or the server 202. If the output indicates that the designed part is within the nominal geometric and functional tolerances, the design for the part can be sent to 3D printer 204 via network 206 for manufacturing.
  • the PSP map of the smaller regions of the part can be used to perform simulation of the entire part using all localized properties of the smaller regions to compute the functional properties for the part.
  • the architecture 200 can further include one or more datastores 226 accessible via the network(s) 206 by the server 202 and 3D printer 204.
  • the datastore(s) 226 can include, but are not limited to, databases (e.g., relational, object-oriented, etc.), file systems, flat files, distributed datastores in which data is stored on more than one node of a computer network, peer-to-peer network datastores, or the like.
  • the data storage 216 can further store various types of data utilized by components of the server 202 such as, for example, any of the data stored in the datastore(s) 226. Any data stored in the data storage 216 can be loaded into the memory 210 for use by the processor(s) 208 in executing computer-executable code. In addition, any data stored in the datastore(s) 226 can be accessed via the DBMS 232 and loaded in the memory 210 for use by the processor(s) 208 in executing computer-executable code.
  • the processor(s) 208 can be configured to access the memory 210 and execute computer-executable instructions loaded therein.
  • the processor(s) 208 can be configured to execute computer-executable instructions of the various program modules, applications, engines, or the like of the server 202 to cause or facilitate various operations to be performed in accordance with one or more embodiments of the disclosure.
  • the processor(s) 208 can include any suitable processing unit capable of accepting data as input, processing the input data in accordance with stored computer- executable instructions, and generating output data.
  • the processor(s) 208 can include any type of suitable processing unit including, but not limited to, a central processing unit, a microprocessor, a Reduced Instruction Set Computer (RISC) microprocessor, a Complex Instruction Set Computer (CISC) microprocessor, a microcontroller, an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), a System-on-a-Chip (SoC), a digital signal processor (DSP), and so forth.
  • RISC Reduced Instruction Set Computer
  • CISC Complex Instruction Set Computer
  • ASIC Application Specific Integrated Circuit
  • FPGA Field-Programmable Gate Array
  • SoC System-on-a-Chip
  • DSP digital signal processor
  • processor(s) 208 can have any suitable microarchitecture design that includes any number of constituent components such as, for example, registers, multiplexers, arithmetic logic units, cache controllers for controlling read/write operations to cache memory, branch predictors, or the like.
  • the microarchitecture design of the processor(s) 208 can be capable of supporting any of a variety of instruction sets.
  • the O/S 230 can be loaded from the data storage 216 into the memory 210 and can provide an interface between other application software executing on the server 202 and hardware resources of the server 202. More specifically, the O/S 230 can include a set of computer-executable instructions for managing hardware resources of the server 202 and for providing common services to other application programs (e.g., managing memory allocation among various application programs). In certain example embodiments, the O/S 230 can control execution of one or more of the program modules depicted as being stored in the data storage 216.
  • the O/S 230 can include any operating system now known or which may be developed in the future including, but not limited to, any server operating system, any mainframe operating system, or any other proprietary or non-proprietary operating system.
  • the DBMS 232 can be loaded into the memory 210 and may support functionality for accessing, retrieving, storing, and/or manipulating data stored in the memory 210, data stored in the datastore(s) 226, and/or data stored in the data storage 216.
  • the DBMS 232 can use any of a variety of database models (e.g., relational model, object model, etc.) and can support any of a variety of query languages.
  • the DBMS 232 can access data represented in one or more data schemas and stored in any suitable data repository.
  • the input/output (I/O) interface(s) 212 can facilitate the receipt of input information by the server 202 from one or more I/O devices as well as the output of information from the server 202 to the one or more I/O devices.
  • the I/O devices can include any of a variety of components such as a display or display screen having a touch surface or touchscreen; an audio output device for producing sound, such as a speaker; an audio capture device, such as a microphone; an image and/or video capture device, such as a camera; a haptic unit; and so forth. Any of these components can be integrated into the server 202 or may be separate.
  • the I/O devices can further include, for example, any number of peripheral devices such as data storage devices, printing devices, and so forth.
  • the I/O interface(s) 212 can also include an interface for an external peripheral device connection such as universal serial bus (USB), FireWire, Thunderbolt, Ethernet port or other connection protocol that can connect to one or more networks.
  • the I/O interface(s) 212 can also include a connection to one or more antennas to connect to one or more networks via a wireless local area network (WLAN) (such as Wi-Fi) radio, Bluetooth, and/or a wireless network radio, such as a radio capable of communication with a wireless communication network such as a Long Term Evolution (LTE) network, WiMAX network, 3G network, etc.
  • WLAN wireless local area network
  • LTE Long Term Evolution
  • the server 202 can further include one or more network interfaces 214 via which the server 202 can communicate with any of a variety of other systems, platforms, networks, devices, and so forth.
  • the network interface(s) 214 can enable communication, for example, with 3D printer 204 and/or the data store(s) 226 via the network(s) 206.
  • program modules, applications, computer- executable instructions, code, or the like depicted in FIG. 2 as being stored in the data storage 216 are merely illustrative and not exhaustive and that processing described as being supported by any particular module can alternatively be distributed across multiple modules or performed by a different module.
  • various program module(s), script(s), plug-in(s), Application Programming Interface(s) (API(s)), or any other suitable computer-executable code hosted locally on the server 202, the device/system 204, and/or hosted on other computing device(s) accessible via one or more of the network(s) 206 can be provided to support functionality provided by the program modules, applications, or computer-executable code depicted in FIG. 2 and/or additional or alternate
  • functionality may be modularized differently such that processing described as being supported collectively by the collection of program modules depicted in FIG. 2 may be performed by a fewer or greater number of modules, or functionality described as being supported by any particular module may be supported, at least in part, by another module.
  • program modules that support the functionality described herein may form part of one or more applications executable across any number of systems or devices in accordance with any suitable computing model such as, for example, a client-server model, a peer-to-peer model, and so forth.
  • any of the functionality described as being supported by any of the program modules depicted in FIG. 2 may be implemented, at least partially, in hardware and/or firmware across any number of devices.
  • the server 202 can include alternate and/or additional hardware, software, or firmware components beyond those described or depicted without departing from the scope of the disclosure. More particularly, it should be appreciated that software, firmware, or hardware components depicted as forming part of the server 202 are merely illustrative and that some components may not be present or additional components may be provided in various embodiments. While various illustrative program modules have been depicted and described as software modules stored in data storage 216, it should be appreciated that functionality described as being supported by the program modules may be enabled by any combination of hardware, software, and/or firmware. It should further be appreciated that each of the above- mentioned modules may, in various embodiments, represent a logical partitioning of supported functionality.
  • This logical partitioning is depicted for ease of explanation of the functionality and may not be representative of the structure of software, hardware, and/or firmware for implementing the functionality. Accordingly, it should be appreciated that functionality described as being provided by a particular module may, in various embodiments, be provided at least in part by one or more other modules. Further, one or more depicted modules may not be present in certain embodiments, while in other embodiments, additional modules not depicted may be present and may support at least a portion of the described functionality and/or additional functionality. Moreover, while certain modules may be depicted and described as sub-modules of another module, in certain embodiments, such modules may be provided as independent modules or as sub- modules of other modules.
  • FIG. 3 depicts a flow diagram of a method 300 for specifying and evaluating functional tolerances for additively manufactured parts according to one or more embodiments.
  • a computing device for example server 202
  • a finite element (FE) model can be created based on the design for the part.
  • each finite element can be mapped to one or more process plan parameters.
  • localized mechanical properties are predicted using PSP maps based on manufacturing process parameters used to design the part.
  • the localized mechanical properties are compared with the specified geometric and functional tolerances associated with the part design to determine whether the associated tolerances have been met.
  • bulk performance for the part can be computed based on the FE model.
  • the FE model can include a collection of localized mechanical properties, which can be used to determine bulk mechanical properties for the part.
  • bulk properties associated with the part design can be compared to global tolerances associated with part or associated assembly. The bulk properties are performance characteristics for the entire part as opposed to localized properties at material scale. For example, small regions of different materials with different local properties can be combined to give an aggregate or bulk property for a larger region.
  • FIG. 4 depicts a flow diagram of a method 400 for manufacturing an additively manufactured part using functional tolerances according to one or more embodiments.
  • a computing device for example server 202
  • the design can be based on a geometric model of the part, mechanical properties and a desired functional behavior for the part.
  • the designer can specify geometric and functional tolerances for the part.
  • the designer can specify a process plan associated with additively manufacturing the part.
  • a finite element model can be created for the part based on the design to define how the part will react to certain operational conditions.
  • a simulation can be performed on a layer-by-layer basis for the part, based on the FEA model (mesh) of the complete geometry for the part using the specified geometric tolerances and functional tolerances for the part to obtain information/output about an actual operation of the part.
  • the computing device can determine whether output from the simulation meets design goals (i.e., does the design meet the specified design constraints and tolerances) specified for the part and/or assembly in which the part is incorporated.
  • the method 400 proceeds to block 435, where the design can be used to manufacture the part, for example, using 3D printer 204. If the simulation indicates that the design goals have not been met, the method 400 proceeds to block 440, where the designer can re-design the part taking into account any out of range constraints and tolerances output by the previous simulation. After the re-design of block 440, the method 400 returns to block 420.
  • the present disclosure may be a system, a method, and/or a computer program product.
  • the computer program product may include a computer readable storage medium (or media) having computer readable program instructions thereon for causing a processor to carry out aspects of the present disclosure.
  • the computer readable storage medium can be a tangible device that can retain and store instructions for use by an instruction execution device.
  • the computer readable storage medium may be, for example, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing.
  • a non-exhaustive list of more specific examples of the computer readable storage medium includes the following: a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanically encoded device such as punch-cards or raised structures in a groove having instructions recorded thereon, and any suitable combination of the foregoing.
  • RAM random access memory
  • ROM read-only memory
  • EPROM or Flash memory erasable programmable read-only memory
  • SRAM static random access memory
  • CD-ROM compact disc read-only memory
  • DVD digital versatile disk
  • memory stick a floppy disk
  • a mechanically encoded device such as punch-cards or raised structures in a groove having instructions recorded thereon
  • a computer readable storage medium is not to be construed as being transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission media (e.g., light pulses passing through a fiber-optic cable), or electrical signals transmitted through a wire.
  • Computer readable program instructions described herein can be downloaded to respective computing/processing devices from a computer readable storage medium or to an external computer or external storage device via a network, for example, the Internet, a local area network, a wide area network and/or a wireless network.
  • the network may comprise copper transmission cables, optical transmission fibers, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers.
  • a network adapter card or network interface in each computing/processing device receives computer readable program instructions from the network and forwards the computer readable program instructions for storage in a computer readable storage medium within the respective computing/processing device.
  • Computer readable program instructions for carrying out operations of the present disclosure may be assembler instructions, instruction-set-architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state-setting data, or either source code or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C++ or the like, and conventional procedural programming languages, such as the "C" programming language or similar programming languages.
  • the computer readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server.
  • the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider).
  • electronic circuitry including, for example, programmable logic circuitry, field- programmable gate arrays (FPGA), or programmable logic arrays (PLA) may execute the computer readable program instructions by utilizing state information of the computer readable program instructions to personalize the electronic circuitry, in order to perform aspects of the present disclosure.
  • These computer readable program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.
  • These computer readable program instructions may also be stored in a computer readable storage medium that can direct a computer, a
  • the computer readable storage medium having instructions stored therein comprises an article of manufacture including instructions which implement aspects of the function/act specified in the flowchart and/or block diagram block or blocks.
  • the computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable apparatus or other device to produce a computer implemented process, such that the instructions which execute on the computer, other programmable apparatus, or other device implement the functions/acts specified in the flowchart and/or block diagram block or blocks.
  • each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s).
  • the functions noted in the block may occur out of the order noted in the figures.
  • two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved.

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Chemical & Material Sciences (AREA)
  • Manufacturing & Machinery (AREA)
  • Materials Engineering (AREA)
  • Computer Hardware Design (AREA)
  • Evolutionary Computation (AREA)
  • Geometry (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)

Abstract

L'invention concerne des systèmes, des procédés et des supports lisibles par ordinateur permettant de spécifier et d'évaluer des tolérances fonctionnelles pour des pièces fabriquées de manière additive. Le procédé consiste à créer, à l'aide d'un processeur, une conception pour une pièce. Le procédé consiste également à spécifier, à l'aide du processeur, une ou plusieurs tolérances fonctionnelles pour des propriétés mécaniques associées à la pièce. Le procédé consiste également à simuler, à l'aide du processeur, le fonctionnement de la pièce. Le procédé consiste également à vérifier, à l'aide du processeur, que la conception répond à des objectifs de conception associés à la tolérance ou aux tolérances fonctionnelles en réponse à la simulation.
PCT/US2018/048514 2018-08-29 2018-08-29 Tolérancement fonctionnel permettant une conception et une planification de processus de fabrication d'objets fabriqués de manière additive WO2020046290A1 (fr)

Priority Applications (1)

Application Number Priority Date Filing Date Title
PCT/US2018/048514 WO2020046290A1 (fr) 2018-08-29 2018-08-29 Tolérancement fonctionnel permettant une conception et une planification de processus de fabrication d'objets fabriqués de manière additive

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
PCT/US2018/048514 WO2020046290A1 (fr) 2018-08-29 2018-08-29 Tolérancement fonctionnel permettant une conception et une planification de processus de fabrication d'objets fabriqués de manière additive

Publications (1)

Publication Number Publication Date
WO2020046290A1 true WO2020046290A1 (fr) 2020-03-05

Family

ID=63528991

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/US2018/048514 WO2020046290A1 (fr) 2018-08-29 2018-08-29 Tolérancement fonctionnel permettant une conception et une planification de processus de fabrication d'objets fabriqués de manière additive

Country Status (1)

Country Link
WO (1) WO2020046290A1 (fr)

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20150352794A1 (en) * 2014-06-05 2015-12-10 Commonwealth Scientific And Industrial Research Organisation Distortion prediction and minimisation in additive manufacturing
WO2016133679A1 (fr) * 2015-02-20 2016-08-25 Siemens Product Lifecycle Management Software Inc. Simulation assistée par ordinateur de processus de fabrication additive
US20170232515A1 (en) * 2016-02-01 2017-08-17 Seurat Technologies, Inc. Additive Manufacturing Simulation System And Method

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20150352794A1 (en) * 2014-06-05 2015-12-10 Commonwealth Scientific And Industrial Research Organisation Distortion prediction and minimisation in additive manufacturing
WO2016133679A1 (fr) * 2015-02-20 2016-08-25 Siemens Product Lifecycle Management Software Inc. Simulation assistée par ordinateur de processus de fabrication additive
US20170232515A1 (en) * 2016-02-01 2017-08-17 Seurat Technologies, Inc. Additive Manufacturing Simulation System And Method

Similar Documents

Publication Publication Date Title
JP6501464B2 (ja) 部品の三次元印刷
US10409932B2 (en) Computer-aided simulation of multi-layer selective laser sintering and melting additive manufacturing processes
US6782305B2 (en) Method of geometric information sharing and parametric consistency maintenance in a collaborative design environment
CN107766651B (zh) 一种铸件残余应力释放数值模拟方法
CN103617070B (zh) 虚拟机迁移方法及装置
US11295254B2 (en) Flexible product manufacturing planning
EP3259691B1 (fr) Processus de fabrication additive comprenant une simulation assistée par ordinateur des processus de fabrication additive
CN110383273B (zh) 增材制造中的散热支撑结构
US8255189B2 (en) System and method for SOA-based wire harness development
CN109304869A (zh) 用于先进增材制造的系统和方法
US20190111590A1 (en) Conformal cooling molds with lattice structures for injection molding
Zheng et al. Product family design and optimization: a digital twin-enhanced approach
US11221610B1 (en) Optimized support design for sintering parts with complex features
WO2020046290A1 (fr) Tolérancement fonctionnel permettant une conception et une planification de processus de fabrication d'objets fabriqués de manière additive
WO2019112661A1 (fr) Prédiction et compensation de la distorsion de fabrication d'une géométrie conçue d'un objet
US9792391B2 (en) Refining of material definitions for designed parts
Abdullin New Capabilities of the ProCAST 2017 Software in simulating casting processes
US20190311758A1 (en) Components including structures having decoupled load paths
US11416642B2 (en) Preparation of a three-dimensional model for data transmission
US10872180B2 (en) Complex feature cloning in additive manufacturing datasets
han et al. A novel framework for online decision-making and feedback optimization of complex products process parameter based on edge-cloud collaboration
Yan et al. Printing Ready Topology Optimization for Material Extrusion Polymer Additive Manufacturing
Senanayake et al. Digital technologies for rapid design and production of replacement aircraft components
WO2022046085A1 (fr) Conception collaborative utilisant une comparaison de modèles
CN117610686A (zh) 模型状态机生成方法、装置、电子设备和计算机可读介质

Legal Events

Date Code Title Description
NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 18766527

Country of ref document: EP

Kind code of ref document: A1