System and method for manufacturing personalized and customized hardware components according to their description
阅读说明：本技术 根据其描述制造个性化和定制的硬件组件的系统和方法 (System and method for manufacturing personalized and customized hardware components according to their description ) 是由 莫兰·比顿 大卫·默梅尔斯坦 摩西·拉米 于 2019-05-06 设计创作，主要内容包括：本发明涉及用于基于其描述制造组件和产品的系统和方法。所述方法经由适于通过通信链路与用户交互的通信接口检索来自所述用户的输入；解析所述输入以产生与所述描述相对应的一个或多个关键词；从预先存储的组件列表中识别一个或多个组件的组合,用于制造所述一个或多个组件的代码,和外壳；优化所述识别出的一个或多个组件的组合；从所述优化的组合生成至少一个具有软件代码,库文件,立体光刻(STL)文件,或Gerber文件中的至少一个的制造文件,所述至少一个制造文件与用于制造所述至少一个硬件组件的所述制造过程相关联。该方法是自动化的,以促进在平台上使用用户描述的规范的端到端制造。(The present invention relates to systems and methods for manufacturing components and products based on their descriptions. The method retrieves input from a user via a communication interface adapted to interact with the user over a communication link; parsing the input to generate one or more keywords corresponding to the description; identifying a combination of one or more components, code for manufacturing the one or more components, and a shell from a pre-stored component list; optimizing a combination of the identified one or more components; generating at least one manufacturing file having at least one of software code, a library file, a Stereolithography (STL) file, or a Gerber file associated with the manufacturing process for manufacturing the at least one hardware component from the optimized combination. The method is automated to facilitate end-to-end manufacturing using user-described specifications on a platform.)
1. A computer-implemented method for generating a manufacturing process for manufacturing at least one hardware component, the method comprising the steps of:
retrieving input from a user via a communication interface adapted to interact with the user over a communication link, the input being associated with a description of the at least one hardware component;
at a processor of a computing device, parsing the input to generate one or more keywords corresponding to the description;
identifying, at the processor, at least one combination of one or more components from a pre-stored component list, the combination of one or more components identified by matching the one or more generated keywords to at least one description associated with each of the components available in the pre-stored component list;
optimizing, at the processor, a combination of the identified one or more components;
generating, at the processor, at least one manufacturing file having at least one of software code, a library file, a Stereolithography (STL) file, or a Gerber file from the optimized combination, the at least one manufacturing file associated with the manufacturing process for manufacturing the at least one hardware component.
2. The computer-implemented method of claim 1, wherein the computer-implemented method further comprises sending, by the processor, the generated at least one manufacturing file to one or more manufacturing machines of the manufacturing process used to manufacture the at least one hardware component.
3. The computer-implemented method of claim 1, wherein the computer-implemented method further comprises optimizing, at the processor, a location of one or more sub-components associated with the at least one hardware component that are available in the at least one manufacturing file as presented on a display of the computing device.
4. The computer-implemented method of claim 1, wherein the computer-implemented method further comprises automatically routing, at the processor, as presented on a display of the computing device, to a final electronic part placement and connection scheme available in the at least one manufacturing file.
5. The computer-implemented method of claim 1, wherein the computer-implemented method further comprises automatically generating, at the processor, software code for manufacturing the at least one hardware component based on the input retrieved from the user.
6. The computer-implemented method of claim 1, wherein the computer-implemented method further comprises automatically generating, at the processor, a manufacturing process for the at least one manufactured shell of the hardware component.
7. The computer-implemented method of claim 1, wherein the computer-implemented method further comprises redesigning wiring available in the at least one manufacturing file as presented on a display of the computing device.
8. The computer-implemented method of claim 1, wherein the steps of identifying, optimizing, and generating are implemented by a pre-stored artificial intelligence algorithm executed by the processor of the computing device.
9. The computer-implemented method of claim 1, wherein the steps of identifying, optimizing, and generating are implemented by a pre-stored machine learning algorithm executed by the processor of the computing device.
10. The computer-implemented method of claim 1, wherein the generating further comprises modifying the manufacturing process using one or more pre-stored augmented reality techniques.
11. The computer-implemented method of claim 1, wherein the input is received in the form of any content or combination of content selected from text, images, audio, video, or animation.
12. A computing device for generating a manufacturing process for manufacturing at least one hardware component, the computing device comprising:
an input/output (I/O) interface to retrieve input from a user via a communication interface adapted to interact with the user over a communication link, the input associated with a description of the at least one hardware component;
a parser for parsing the input to generate one or more keywords corresponding to the description;
a combination identifier for identifying at least one combination of one or more components from a pre-stored list of components, the combination of one or more components being identified by matching the one or more generated keywords to at least one description associated with each of the components available in the pre-stored list of components;
a combination optimizer for optimizing a combination of the identified one or more components;
a manufacturing file generator to generate at least one manufacturing file having at least one of software code, a library file, a Stereolithography (STL) file, or a Gerber file from the optimized combination, the manufacturing file associated with the manufacturing process used to manufacture the at least one hardware component.
13. The computing device of claim 12, wherein the computing device is further configured to:
transmitting, by a processor of the computing device, the generated at least one manufacturing file to one or more manufacturing machines of the manufacturing process used to manufacture the at least one hardware component; or
Optimizing, at the processor of the computing device, a location of one or more sub-components associated with the at least one hardware component available in the at least one manufacturing file as presented on a display of the computing device; or
Automatically routing, at the processor of the computing device, as presented on a display of the computing device, to a final electronic part placement and connection scheme available in the at least one manufacturing file; or
Redesigning wiring available in the at least one manufacturing file as presented on a display of the computing device; or
The manufacturing process is modified using one or more pre-stored augmented reality techniques.
14. The computing device of claim 12, wherein the computing device further comprises:
a pre-stored artificial intelligence algorithm executed by a processor of the computing device; or
A pre-stored machine learning algorithm executed by a processor of the computing device.
15. The computing device of claim 10, wherein the manufacturing file generator is further configured to:
automatically generating software code for manufacturing the at least one hardware component based on the input retrieved from the user; and/or
A manufacturing process for automatically generating a shell for the at least one manufactured hardware component.
Technical Field
The present disclosure relates to the field of manufacturing, and more particularly, to systems and methods for manufacturing personalized and customized hardware components (such as, but not limited to, manufactured or refined items or substances for sale or physical or tangible parts), and software (code) for manufacturing personalized and customized hardware according to the description thereof.
Background
Today, there are a wide variety of small, often handheld, electronic devices, commonly referred to as mobile internet devices, including particularly a wide variety of products commonly referred to as mobile phones and tablet computers. In the current state of the art, all such devices are designed by their manufacturers to include various hardware functions, such as cameras or positioning system receivers chosen by the manufacturer to attract as many potential customers as possible. Likewise, the manufacturer determines the form factor, i.e., size, shape, weight, color, and other physical attributes, of each product in order to satisfy as many users as possible with a minimum of specific combinations. Finally, manufacturers configure the operating software of their devices to provide various functions such that a particular function or group of related functions performs in exactly the same way across as many device models as possible.
Limiting the amount of hardware and software combinations benefits device manufacturers by reducing the complexity of the various systems and programs that device manufacturers use for product development and manufacture. The primary mechanism that current manufacturers use to determine exactly what a particular new product should be and what should be done is a complex function of the cost and benefit of its existing capabilities interacting with the customer's wishes. However, in general, the end user desires are entirely comprehensive as set forth by wholesale customers, such as wireless carriers and major retailers, and occasionally as illustrated by observational studies classifying people by seemingly reasonable but ultimately arbitrary attributes.
Manufacturers are aware that individual end users and smaller groups of end users often have special needs for which the mass production process described above cannot provide cost-effective point solutions (point solutions).
The following is considered by the applicant to be the closest prior art: US7233885B1 discloses a computer-assisted method for clearly and accurately describing a customized product, the method comprising identifying the product in response to a request for product information from a user; automatically initiating a real-time transmission of at least one document associated with the standard product to the user if the standard product matches the identified product; if no standard product matches the identified product, the request for product information is electronically forwarded to the engineering entity. Certain exemplary embodiments include a computer-assisted method for designing a product, the method comprising receiving from a user a value for at least one design parameter related to the product; automatically designing a predetermined portion of the product in response to at least one of the design parameter values if the value of each design parameter received from the user is within the predetermined set of design parameters; and documents about the designed product are provided to the user electronically. Electronic manufacturing processes lack production arrangements that reduce the indirect costs associated with production line set-up and production defects.
Electronics manufacturing lacks production arrangements that reduce the indirect costs associated with production line setup and production defects. Such an arrangement should minimize the need to reconfigure production line equipment for the production of different PCBA products (hereinafter also referred to interchangeably as "hardware components" or "items"). Preferably, this arrangement will achieve these goals at various levels of system design. Ideally, such a system would amplify its efficiency gains by incorporating modern computer process control technology and implementing system responsiveness that a human operator could provide.
Therefore, what is needed is an automated system and method for manufacturing personalized and customized hardware components (such as, but not limited to, manufactured or finished articles or substances for sale or physical or tangible parts), and software (code) for manufacturing personalized and customized hardware according to the description thereof.
All publications herein are incorporated by reference to the same extent as if each individual publication or patent application was specifically and individually indicated to be incorporated by reference. Where a definition or use of a term in an incorporated reference is inconsistent or contrary to the definition of that term provided herein, the definition of that term provided herein applies and the definition of that term in the reference does not apply.
Disclosure of Invention
The present disclosure relates to the field of production, and more particularly, to systems and methods for manufacturing personalized and customized hardware for products based on verbal descriptions.
Accordingly, one aspect of the present disclosure relates to a computer-implemented method for generating a manufacturing process and code for manufacturing at least one hardware component including an enclosure thereof. The computer-implemented method includes: retrieving input (e.g., a verbal description) from a user via a communication interface adapted to interact with the user over a communication link, the input being associated with a description of the at least one hardware component; at a processor of a computing device, parsing the input to generate one or more keywords corresponding to the description; identifying, at the processor, at least one combination of one or more components from a pre-stored list of components, code for manufacturing the one or more components and a shell of the one or more components, the combination of one or more components identified by matching the one or more generated keywords to at least one description associated with each of the components available in the pre-stored list of components; optimizing, at the processor, a combination of the identified one or more components; generating, at the processor, at least one manufacturing file having at least one of software code, a library file, a Stereolithography (STL) file, or a Gerber file associated with the manufacturing process for manufacturing the at least one hardware component from the optimized combination.
In an aspect, the computer-implemented method may transmit, by the processor, the generated at least one manufacturing file to one or more manufacturing machines of the manufacturing process used to manufacture the at least one hardware component.
In an aspect, the computer-implemented method may optimize, at the processor, a location of one or more sub-components associated with the at least one hardware component available in the at least one manufacturing file, as presented on a display of the computing device.
In an aspect, the computer-implemented method may automatically route, at the processor, as presented on a display of the computing device, to a final electronic part placement and connection scheme available in the at least one manufacturing file.
In an aspect, the computer-implemented method may redesign the wiring available in the at least one manufacturing file as presented on a display of the computing device.
In an aspect, the computer-implemented method may generate, at the processor, the code for the operations of the described embodiments. The code is generated according to specifications of the electrical scheme and the user description.
In an aspect, the computer-implemented method may generate, at the processor, a flow for manufacturing the shell of the hardware manufactured in the last step. The shell is generated using proprietary and/or genetic algorithms to connect parts and components and assembled into a complete three-dimensional shell model according to specifications described by the user.
In one aspect, the computer-implemented method, at the processor, may be done in parallel with the manufacture of the product, or may be done at the beginning or end of the manufacture of the product, in order to manufacture the shell. Basically, the manufacture of the housing depends on the specifications of the user.
In one aspect, the steps of identifying, optimizing, and generating are implemented by a pre-stored artificial intelligence algorithm executed by the processor of the computing device.
In an aspect, the steps of identifying, optimizing, and generating are implemented by a pre-stored machine learning algorithm executed by the processor of the computing device.
In one aspect, the method may modify the manufacturing process using one or more pre-stored augmented reality techniques.
In one aspect, the input is received in the form of any content or combination of content selected from text, images, audio, video or animation.
Another aspect of the present disclosure relates to a computing device for generating a manufacturing process for manufacturing at least one hardware component. The computing device includes: an input/output (I/O) interface to retrieve input from a user via a communication interface adapted to interact with the user over a communication link, the input associated with a description of the at least one hardware component; a parser for parsing the input to generate one or more keywords corresponding to the description; a combination identifier for identifying a combination of at least one or more components from a pre-stored component list; a combination optimizer for optimizing a combination of the identified one or more components; a manufacturing file generator to generate at least one manufacturing file having at least one of software code, a library file, a Stereolithography (STL) file, or a Gerber file from the optimized combination.
In one aspect, the combination of one or more components is identified by matching the one or more generated keywords to at least one description associated with each of the components available in the pre-stored list of components.
In an aspect, the at least one manufacturing file is associated with the manufacturing process used to manufacture the at least one hardware component.
Another aspect of the disclosure relates to a method for producing a product from a verbal description. The method may comprise the steps of: providing a description of the product in natural language, in which keywords related to (a) a code for operating the product, (b) an electronic device of the product, and (c) a cover of the product are detected.
Based on the detected code of the product, keywords of the electronic device and the shell, (a) retrieving a generic combination of components from a database; (b) optimizing the retrieved component combinations; (c) a manufacturing file is generated that includes the code and library files, a Stereolithography (STL) file, and a Gerber file from the combination.
The method may comprise the steps of: optimizing the position of the PCB in the housing model; automatically wiring to a final electronic part placement and connection scheme, automatically generating code for manufacturing the one or more components, and producing and/or manufacturing a three-dimensional housing for the one or more components; designing wiring between the electronic part and the PCB; sending the manufacturing document to a manufacturing machine; and manufacturing the product by the manufacturing machine.
In one aspect, the detecting is performed using artificial intelligence analysis.
According to an aspect of the invention, the optimizing comprises redesigning the product using augmented reality techniques.
In another aspect, the invention is directed to a system for manufacturing a product from a verbal description. The system may include an input device for inputting a verbal description of a product and converting it into a sentence; a keyword detector for detecting keywords related to a code of a product, an electronic device and a housing in the sentence; a code database for storing therein code components for later use; an electronic device database for storing therein information of the electronic components and combinations thereof; a shell database for storing information of shell components and combinations thereof therein; the code module is used for generating a code and a library according to the relevant key words and relevant information of the code stored in the code database; the electronic equipment module is used for generating a Gerber file according to the related keywords and the related information of the electronic equipment stored in the electronic equipment database; the shell module is used for generating an STL file according to the relevant keywords and the relevant information of the shell stored in the shell database; an optimizer for optimizing the size of the PCB and the position of the electrical components in the housing; one or more manufacturing machines to manufacture the product from the generated Gerber, STL, and code files.
In one aspect, the optimization of the PCB may require further operations, such as changing the size, shape and separation of the PCB into multiple PCBs.
In one aspect, optimization of the housing requires operations such as scaling, altering materials and textures, altering the position of electronic components, and other such operations to properly manufacture a housing suitable for the product.
In an aspect, the input device includes the capability to input an audio signal.
In one aspect, the input device further includes the capability to input images.
In an aspect, the input device further includes the ability to input an augmented reality scan.
In one aspect, the keyword detector employs artificial intelligence analysis capabilities.
In one aspect, the keyword detector employs speech processing and natural language processing and denoising.
The method is automated to facilitate end-to-end manufacturing of customized products with specifications described by a user on a platform. The platform may be a network-defined platform and/or a platform that runs or executes computer-implemented instructions.
Various objects, features, aspects and advantages of the present subject matter will become more apparent from the following detailed description of preferred embodiments and the accompanying drawings in which like numerals represent like components.
Drawings
The accompanying drawings are included to provide a further understanding of the disclosure, and are incorporated in and constitute a part of this specification. The drawings illustrate exemplary embodiments of the disclosure and, together with the description, serve to explain the principles of the disclosure. These figures are for illustration only and thus are not a limitation of the present disclosure, and wherein:
FIG. 1 is a block diagram that schematically illustrates a method for manufacturing a product from a verbal description thereof, in accordance with an embodiment of the present invention.
FIG. 2 is a block diagram that schematically illustrates a system for manufacturing a product from its verbal description, in accordance with an embodiment of the present invention.
Fig. 3 illustrates exemplary functional modules of the proposed computing device, according to an aspect of the present disclosure.
Fig. 4 illustrates an exemplary flow diagram of the present system, according to an embodiment of the disclosure.
Detailed Description
The following is a detailed description of embodiments of the disclosure depicted in the accompanying drawings. The embodiments are in such detail as to clearly communicate the disclosure. However, the amount of detail offered is not intended to limit the anticipated variations of embodiments; on the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the scope of the disclosure as defined by the appended claims.
The disclosed embodiments include various steps, which will be described below. The steps may be performed by hardware components or may be embodied in machine-executable instructions, which may be used to cause a general-purpose processor or special-purpose processor programmed with the instructions to perform the steps. Alternatively, the steps may be performed by hardware, a combination of software and firmware, or by an operator.
Embodiments of the present disclosure may be provided as a computer program product that may include a machine-readable storage medium having tangibly embodied thereon instructions, which may be used to program a computer (or other electronic devices) to perform a process. The machine-readable medium may include, but is not limited to, a fixed (hard) drive, magnetic tape, a floppy disk, an optical disk, a compact disc-read only memory (CD-ROM), and a magneto-optical disk, semiconductor memory such as ROM, PROM, Random Access Memory (RAM), Programmable Read Only Memory (PROM), erasable PROM (eprom), electrically erasable PROM (eeprom), flash memory, magnetic or optical cards, or other type of media/machine-readable medium suitable for storing electronic instructions (e.g., computer programming code, such as software or firmware).
If a component or feature is referred to in the specification as being included or having a feature "may (may)", "may (can)", "may (result)" or "may (light)", that particular component or feature need not be included or have that feature.
As used in the description herein and in the claims that follow, the meaning of "a", "an" and "the" includes plural reference unless the context clearly dictates otherwise. In addition, as used in the specification herein, the meaning of "in., (in)" includes "in., (in)" and "on., (on)" unless the context clearly indicates otherwise.
Exemplary embodiments will now be described more fully hereinafter with reference to the accompanying drawings, in which exemplary embodiments are shown. These exemplary embodiments are provided for illustrative purposes only, and thus the present disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art. The disclosed invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Various modifications will be apparent to those skilled in the art.
The general principles defined herein may be applied to other embodiments and applications without departing from the scope of the invention. Moreover, all statements herein reciting embodiments of the invention, as well as specific examples thereof, are intended to encompass both structural and functional equivalents thereof. Additionally, it is intended that such equivalents include both currently known equivalents as well as equivalents developed in the future (i.e., any elements developed that perform the same function, regardless of structure). Also, the phraseology and terminology used are for the purpose of describing the exemplary embodiments and should not be regarded as limiting. Thus, the present invention is to be accorded the widest scope encompassing numerous alternatives, modifications and equivalents consistent with the principles and features disclosed. For the purpose of clarity, details relating to technical material that is well known in the technical fields related to the invention have not been described in detail so as not to unnecessarily obscure the present invention.
Each of the appended claims defines a separate invention, which for infringement purposes is recognized as including equivalents to the various elements or limitations specified in the claims. Depending on the context, in some cases all references below to the "invention" may refer to certain specific embodiments only. In other cases, it will be recognized that references to the "invention" may refer to subject matter recited in one or more, but not necessarily all, of the claims.
All methods described herein can be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context. The use of any and all examples, or exemplary language (e.g., "such as") provided with respect to certain embodiments herein, is intended merely to better illuminate the invention and does not pose a limitation on the scope of the invention unless otherwise claimed. No language in the specification should be construed as indicating any non-claimed element as essential to the practice of the invention.
The present disclosure relates to the field of manufacturing, and more particularly, to systems and methods for manufacturing personalized and customized hardware components of a product from a product description.
In an exemplary embodiment, the present invention may be implemented using one or more internet of things (IoT) devices. For example, the computing device may be an IoT device, or the manufacturing device may be an IoT device. The manufacturing equipment may be any manufacturing machine such as, but not limited to, a wafer manufacturing system, a high rigidity grinder, a probing machine, a dicing machine, or a 3D printer, and includes electronic components such as, but not limited to, resistors, capacitors, diodes, and transistors formed directly on the surface of a silicon crystal.
In another example embodiment, the computing device and/or the manufacturing machine may be embedded/integrated with one or more internet of things (IoT) devices.
In a typical network architecture of the present disclosure, multiple network devices may be included, such as transmitters, receivers, and/or transceivers that may include one or more IoT devices.
As used herein, the IoT device may be a device that includes sensing and/or control functions as well as a WiFi transceiver radio or interface, a Bluetooth (Bluetooth) transceiver radio or interface, a Zigbee transceiver radio or interface, an ultra-wideband (UWB) transceiver radio or interface, a Wi-Fi-Direct transceiver radio or interface, a low energy Bluetooth (BLE) transceiver radio or interface, and/or any other wireless network transceiver radio or interface that allows the IoT to communicate with a wide area network and one or more other devices. In some embodiments, the IoT devices do not include a cellular network transceiver radio or interface and thus may not be configured to communicate directly with the cellular network. In some embodiments, the IoT device may include a cellular transceiver radio and may be configured to communicate with a cellular network using the cellular network transceiver radio.
IoT devices may include home automation network devices that allow a user to access, control, and/or configure various home appliances located within or outside of the user's premises. The network device may include a home automation switch that may be coupled with the home appliance. In some embodiments, the network device may be used in other environments that may support a local area network to enable communication with the network device.
The user may communicate with the network device using an access device that may include any human interface having network connectivity functionality that allows access to the network. For example, the access device may include a stand-alone interface (e.g., a cellular phone, a smart phone, a home computer, a laptop computer, a tablet, a Personal Digital Assistant (PDA), a computing device, a wearable device, such as a smart watch, a wallPanel, keyboard, etc.), built-in interfaces in home appliances or other devices such as televisions, refrigerators, security systems, game machines, browsers, etc., voice or gesture interfaces (e.g., Kinect)TMSensor, WiimoteTMEtc.), an IoT device interface (e.g., an Internet-enabled device such as a wall switch, control interface, or other suitable interface), etc. In some embodiments, the access device may include a cellular or other broadband network transceiver radio or interface and may be configured to communicate with a cellular or other broadband network using the cellular or broadband network transceiver radio. In some embodiments, the access device may not include a cellular network transceiver radio or interface.
The user may interact with the network device using an application program, a Web browser, a proprietary program, or any other program executed and operated by the access device. In some embodiments, the access device may communicate (e.g., communication signals) directly with the network device. For example, the access device may use ZigbeeTMSignal, BluetoothTMSignal, WiFiTMSignals, Infrared (IR) signals, UWB signals, WiFi-Direct signals, BLE signals, audio signals, etc. are in Direct communication with the network device. In some embodiments, the access device may communicate with the network device via a gateway and/or a cloud network.
The local area network may include a wireless network, a wired network, or a combination of wired and wireless networks. The wireless network may include any wireless interface or combination of wireless interfaces (e.g., Zigbee, bluetooth, WiFi, IR, UWB, WiFi-Direct, BLE, cellular, Long Term Evolution (LTE), WiMax, etc.). The wired network may include any wired interface (e.g., fiber optic, ethernet, power line, ethernet over coaxial cable, Digital Signal Line (DSL), etc.). The wired and/or wireless networks may be implemented using various routers, access points, bridges, gateways, etc. connected to the devices in the local area network. For example, the local area network may include a gateway. The gateway may provide communication capabilities via radio signals to network devices and/or access devices to provide communication, location and/or other services to the devices. The gateway is directly connected to the external network and may provide access to the external network for other gateways and devices in the local area network. The gateway may be designated as the primary gateway.
The network access provided by the gateway may be any type of network familiar to those skilled in the art that can support data communications using any of a variety of commercially available protocols. For example, the gateway may provide wireless communication capabilities for the local area network using a particular communication protocol such as WiFi (e.g., an IEEE 802.11 family of standards, or other wireless communication technologies, or any combination thereof). Using a communication protocol, the gateway may provide a radio frequency over which wireless-enabled devices in the local area network may communicate. Gateways may also be referred to as base stations, access points, node bs (node bs), evolved node bs (enodebs), access point base stations, femtocells (femtocells), home base stations, home node bs, home enodebs, and the like.
Although the present subject matter is explained in view of the computing device 302 performing a method for generating a manufacturing process for manufacturing at least one hardware component, the computing device 302 may be implemented as an application on a server. It is to be appreciated that the computing device 302 may also be implemented in various computing systems, such as laptop computers, desktop computers, notebook computers, workstations, servers, web servers, cloud-based environments, and the like.
It should be appreciated that the computing device 302 may be accessed by multiple users (not shown) through their interfaces or applications residing on the computing device 302. Examples of the computing device 302 may include, but are not limited to, portable computers, personal digital assistants, handheld devices such as mobile phones and smart phones, workstations, and cloud-based environments.
In one embodiment, the network may be a wireless network, a wired network, or a combination thereof. The network may be implemented as one of various types of networks, such as an Intranet, a Local Area Network (LAN), a Wide Area Network (WAN), the internet, and so forth. Further, the network may be a private network or a shared network. The shared network represents a combination of different types of networks using various protocols such as hypertext transfer protocol (HTTP), transmission control protocol/internet protocol (TCP/IP), Wireless Application Protocol (WAP), etc. to communicate with each other. Further, the network 104 may include a variety of network devices, including routers, bridges, servers, computing devices, storage devices, and the like.
In one implementation, the computing device 302 (which may include multiple devices communicating in a wired or wireless environment) may include at least one of: a mobile wireless device, a smartphone, a mobile computing device, a wireless device, a wired device, a network device, a docking device, a personal computer, a laptop computer, a tablet computer, a personal digital assistant, a wearable device, a remote computing device, a server, a functional computing device, or any combination thereof. While in a preferred and non-limiting embodiment, the primary computing device 108 is a smartphone (which may include suitable hardware and software components for implementing the various functions described), it is also contemplated that the computing device 302 may be any suitable computing device configured, programmed or modified to implement one or more of the functions of the described system.
The present invention will be understood from the following detailed description of the preferred embodiment ("best mode") which is intended to be illustrative, but not limiting.
In the interest of brevity, some well-known features, methods, systems, processes, components, circuits, and the like, may not be described in detail. The present invention greatly reduces planning and manufacturing time compared to the prior art. For example, from describing a product in natural language, such as: "Wireless cleaners for artificial grass have a pumping power of 300 WSP", it may take several minutes to obtain a design chart, end-to-end simulation and manufacturing documentation.
The present invention also allows learning from previous designs so that when a user defines a product that contains elements that have already been designed in a previous product, those elements can be used for a new planning product.
FIG. 1 is a block diagram that schematically illustrates a method for manufacturing a product from a verbal description thereof, in accordance with an embodiment of the present invention.
Block 100: a product description request of a user. At block 100, a user describes a product using natural language. For example, "turn on LED alarm device when temperature is above 35 degrees celsius. It should be noted that the product description may be provided by text, images, sounds, combinations thereof, and the like.
In fact, this is all that the user has to do. At the end of this process, a manufacturing file is generated based on the system of the present invention, such as a Gerber-formatted file for printed circuit boards, an STL file for shell 3D printing, and the like.
Block 101: natural language processing to detect keywords. At block 101, the system analyzes the description provided by the user for detecting three categories of keywords: (a) a 3D model, (b) an electronic device, and (c) code.
Preferably, the keywords may also be detected by speech analysis and artificial intelligence analysis. Blocks 102 through 104 process the code design. The code may be that of a CPU, integrated circuit, or the like.
Block 102: a combination of generic code components. At block 102, the system retrieves code components and features, such as network, control, logic, components and component functions, from its database. Examples of such code might be:
IF_THEN_:_>35,ON
COMPONENT 1:DS18B20
FUNCTION 1:GET_DATA
COMPONENT2:LED
FUNCTION2:ON/OFF
block 103: the code components are optimized into a graph. At block 103, the system optimizes the code blocks into a code map according to the given code block and electrical scheme.
For example:
IF_:DSl8B20.GET_DATA>35
THEN_:LED-55MM.ON
for example: the electrical scheme is provided by an electronic design module.
Block 104: code and library files are generated. At block 104, the system converts the code graph into a complete code file and code library according to the electronic model assigned to the main CPU of the product. Blocks 105 to 108 process an electronic design, for example a PCB (printed circuit board).
Block 105: and searching the general electronic component. At block 105, the system retrieves electronic components and features, combinations of required components, from the database, such as: batteries, power connectors, switches, communications, sensors, etc. The combination of components may be general or specific components, depending on the user description provided in block 100. (e.g., "Battery" is a generic term; two 1.5V AAA batteries "is a specific term).
Block 106: optimizing a particular combination of components. At block 106, depending on electrical stability, efficiency, price, etc., for example: battery/rechargeable/Cn 18650, Cpu/Avr/Atmega644, sensor/temperature/DS 18B20, sensor/LED/5 mm, the system optimizes the combined request to the final specific component.
Block 107: an electrical scheme is generated. At block 107, the system retrieves the electrical schema for the given component combination from the database. Using this information, the connections between the schematic and the electronic part can be shown. The information obtained at this block is provided to a code module for optimizing the code according to the selected electrical and electronic components according to Natural Language Processing (NLP) according to the method described by the user.
And a block 108: automated electronic component placement. At block 108, according to: user conditions (specific location, grid size, etc.), given an electrical scheme, optimization rules, electrical rules, temperature, efficiency, price, etc., the system optimizes the electronic component placement on the grid.
Blocks 106, 107 and 108 may be repeated until the result is "satisfactory". Satisfactory definitions may be defined by the system or inferred from user input. For example, an input phrase such as "an inexpensive device for turning on an LED alarm at temperatures above 35 degrees celsius" orients the system to optimize the cost of the designed device.
Blocks 109 to 111 process the 3D model design, for example: a housing of the device. Block 109: a universal 3D shell assembly. At block 109, the system retrieves from the database the shell components and features, the combination of required components (door, engine, seat, etc.) and feature blocks (text, color, texture, etc.). For example: assembly of: 3D BOX module 110: optimizing 3D model components and features.
At block 110, the system optimizes the housing specific components and features based on housing stability, efficiency and housing attachment scheme. For example: PCB dimensions and features are optimized.
Block 111: automatic "evolution" of 3D models (shells). At block 111, the system optimizes the connection of the enclosure components on the 3D grid according to the user's situation and thereby learns the user's preferences, user style, user behavior, etc. (specific location, material, texture, etc.), given the enclosure connection scheme, optimization rules, material rules, temperature, efficiency and price using artificial intelligence.
Block 112: the best position is found for the PCB inside the 3D model (shell). At block 112, the system optimizes the position of the PCB inside the 3D housing model, i.e., finds its best position on the housing, while considering the physical peripherals and pivots applicable to the PCB. To achieve maximum efficiency, electronics (PCB size, number of PCBs, component size) and housing (size, material, component), the solution may repeat some steps related to electronics and 3D modeling.
Block 113: the PCB is automatically wired. At block 113, the system automatically routes to the final electronic part placement and connection scheme. If automatic routing is not possible, the optimization step is repeated (step 112).
Block 114: routing of electronic components to the PCB. At block 114, the system designs the wiring between the electronic components and the PCB due to the location of certain electronic components on the housing (batteries, lights, sensors, engines, etc.). At block 115, the system allows visualization (simulation) of the product.
At block 116, the system allows the user to edit the generated design, such as: one component is replaced with another. The user may command the system to continue the flow or repeat the previous stage.
Block 117: a Gerber file is generated. Block 118: an STL file is generated. And a block 119: the product is manufactured. The manufacturing ends at block 119 and the product is manufactured using the manufacturing files (Gerber file, STL file, code and library file) at block 119.
The Gerber format is a format of a 2D binary image. It is a de facto standard used by Printed Circuit Board (PCB) industry software to describe printed circuit board images: copper layer, solder mask, legend, etc.
The STL format is a widely used rapid prototyping, 3D printing, and computer aided manufacturing. Once the manufacturing files (code files, Gerber files, and STL files) are generated, they are sent to the automated manufacturing machine that manufactured the product.
FIG. 2 is a block diagram that schematically illustrates a system for manufacturing a product from its verbal description, in accordance with an embodiment of the present invention.
Reference numeral 10 designates an input device for inputting a description of a product by a user in a natural language, according to an embodiment of the present invention.
The output of the input device 10 is a text statement, but the input device need not necessarily be a keyboard. The microphone may be used for recording the user, the camera for inputting images, AR scanning (augmented reality scanning), etc. For example, a user may scan the coffee maker and specify particular characteristics, such as pressure, size of the water tank, and the like. The input device 10 has the ability to turn an input into a sentence. Of course, the user can edit the sentence. The input may be one or more products. For example, "a toy vehicle operated by a remote controller". Or "a network whose nodes have the ability to communicate with each other and an upper network". In this case, some of the elements involved are repeaters, gateways, and clouds.
Once the user provides a description of the product, the keyword analyzer 11 detects keywords related to three topics: code, electronic devices, and product housings.
Keywords 24 associated with the code are provided to the code module 12; keywords 25 related to the electronic device are provided to the electronic device module 13; and shell related keywords 26 are provided to the shell module 16.
The code module retrieves code components and combinations thereof from its database 13; the electronic device module retrieves the electronic components and combinations thereof from its database 15; and the shell module retrieves shell components and combinations thereof from its database 17.
The optimizer 18 optimizes the design previously made by the code, electronics and housing modules. If necessary, all or part of the code, the electronic device and the housing module are activated again based on the optimization result. During the optimization process, the product can be redesigned using augmented reality techniques.
The optimizer 18 then generates a manufacturing file that includes the code and library file 19, the Gerber file 20, and the STL file 21. These documents are directed to the manufacturing machine 22 that manufactures the product. The code, electronic device and housing modules, and optimizer are software tools.
In the drawings and/or the description herein, the following reference numerals (list of reference numerals) have been mentioned:
the numeral 10 denotes an input device;
numeral 11 denotes a keyword analyzer;
numeral 12 represents a code module;
the numeral 13 represents a code database;
numeral 14 represents an electronic device module;
numeral 15 represents an electronic device database;
numeral 16 denotes a housing module;
numeral 17 represents a shell database;
numeral 18 represents code, electronics and a housing optimizer;
numeral 19 represents a code and library file;
numeral 20 denotes a Gerber file;
numeral 21 represents an STL file; and
numeral 22 denotes a manufacturing machine.
In the description herein, the following references have been mentioned: US7233885B 1. The foregoing description and description of the embodiments of the invention have been presented for the purposes of illustration and description. It is not intended to be exhaustive or to limit the invention to the precise form disclosed.
Any terms defined above and used in the claims should be construed according to this definition.
Fig. 3 illustrates exemplary functional modules 300 of the proposed computing device, according to an aspect of the present disclosure. In one embodiment, the proposed computing device 302 may include at least one processor 304, an input/output (I/O) interface 306, a transceiver 308, and a memory 310. The at least one processor 304 may be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, state machines, logic circuitry, and/or any devices that operate on signals according to operational instructions. Among other capabilities, the at least one processor 304 is configured to retrieve and execute computer-readable instructions stored in the memory 310. The I/O interface 306 may include various software and hardware interfaces, such as a network interface, a graphical user interface, and the like. The I/O interface 306 may allow the proposed computing device 302 to interact with a user directly or through a client device. In addition, the I/O interfaces 306 may enable the computing device to communicate with other computing devices, such as web servers and external data servers (not shown). The I/O interface 306 may facilitate a variety of communications within a variety of networks and protocol types, including wired networks, such as LANs, cables, and the like, and wireless networks, such as WLANs, cellular, or satellite. The I/O interface 306 may include one or more ports for connecting multiple devices to each other or to another server.
The memory 310 may include any computer-readable medium known in the art, including, for example: volatile memory, such as Static Random Access Memory (SRAM) and Dynamic Random Access Memory (DRAM), and/or non-volatile memory, such as Read Only Memory (ROM), erasable programmable ROM, flash memory, hard disks, optical disks, and magnetic tape. The memory 310 may include modules, routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types.
In an aspect, the computing device 302 generates a manufacturing process to manufacture at least one hardware component. The computing device 302 includes: an input/output (I/O) interface 306 for retrieving input from a user via a communication interface adapted to interact with the user through a communication link or transceiver 308, the input being associated with a description of the at least one hardware component; a parser 312 for parsing the input to generate one or more keywords corresponding to the description; a combination identifier 314 for identifying at least one or a combination of components from a pre-stored list of components; a composition optimizer 316 for optimizing a composition of the identified one or more components; a manufacturing file generator 318 for generating at least one manufacturing file having at least one of software code, a library file, a Stereolithography (STL) file, or a Gerber file from the optimized combination.
In one aspect, the combination of one or more components is identified by matching the one or more generated keywords to at least one description associated with each of the components available in the pre-stored list of components.
In an aspect, the at least one manufacturing file is associated with the manufacturing process used to manufacture the at least one hardware component.
In an exemplary embodiment, the parser 312, the composition identifier 314, the composition optimizer 316, and the manufactured file generator 318 may reside in the memory 310 of the computing device and may be executed (form)/execute (execute) by the processor 304.
FIG. 4 illustrates an exemplary flow diagram of a present system for generating a manufacturing flow for manufacturing at least one hardware component, according to an embodiment of the disclosure.
In step 402, input from a user is retrieved via a communication interface adapted to interact with the user over a communication link. The input is associated with a description of the at least one hardware component.
At step 404, the input is parsed by a processor of the computing device to generate one or more keywords corresponding to the description.
At step 406, at the processor, at least one or a combination of components from a pre-stored list of components is identified. The combination of one or more components is identified by matching the one or more generated keywords to at least one description associated with each of the components available in the pre-stored list of components.
At step 408, at the processor, the combination of the identified one or more components is optimized.
At step 410, at the processor, at least one manufacturing file having at least one of software code, a library file, a Stereolithography (STL) file, or a Gerber file is generated from the optimized combination. The at least one manufacturing file is associated with the manufacturing process for manufacturing the at least one hardware component.
In an aspect, the computer-implemented method may transmit, by the processor, the generated at least one manufacturing file to one or more manufacturing machines of the manufacturing process used to manufacture the at least one hardware component.
In an aspect, the computer-implemented method may optimize, at the processor, a location of one or more sub-components associated with the at least one hardware component available in the at least one manufacturing file, as presented on a display of the computing device.
In an aspect, the computer-implemented method may automatically route, at the processor, as presented on a display of the computing device, to a final electronic part placement and connection scheme available in the at least one manufacturing file.
In an aspect, the computer-implemented method may redesign the wiring available in the at least one manufacturing file as presented on a display of the computing device.
In an aspect, the identifying, optimizing, and generating are implemented by a pre-stored artificial intelligence algorithm executed by the processor of the computing device.
In an aspect, the steps of identifying, optimizing, and generating are implemented by a pre-stored machine learning algorithm executed by the processor of the computing device.
In one aspect, the method may modify the manufacturing process using one or more pre-stored augmented reality techniques.
In one aspect, the input is received in the form of any content or combination of content selected from text, images, audio, video or animation.
Various terms used herein are shown below. To the extent that a term used in a claim is not defined below, it should be given the broadest definition persons in the pertinent art have given that term as reflected in printed publications and issued patents at the time of filing.
It will be apparent to those skilled in the art that many more modifications besides those already described are possible without departing from the inventive concepts herein. Moreover, in interpreting both the specification and the claims, all terms should be interpreted in the broadest possible manner consistent with the context. In particular, the terms "comprises" and "comprising" should be interpreted as referring to elements, components, or steps in a non-exclusive manner, indicating that the referenced elements, components, or steps may be present, or utilized, or combined with other elements, components, or steps that are not expressly referenced.
When the specification and claims refer to at least one substance selected from a, B, c. The foregoing description of the specific embodiments will so fully reveal the general nature of the embodiments herein that others can, by applying current knowledge, readily modify and/or adapt for various applications such specific embodiments without departing from the generic concept, and, therefore, such adaptations and modifications should and are intended to be comprehended within the meaning and range of equivalents of the disclosed embodiments. It is to be understood that the phraseology or terminology employed herein is for the purpose of description and not of limitation. Thus, while the embodiments herein have been described in terms of preferred embodiments, those skilled in the art will recognize that the embodiments herein can be practiced with modification within the scope of the appended claims.
While embodiments of the present disclosure have been shown and described, it will be clear that the disclosure is not limited to these embodiments only. Numerous modifications, changes, variations, substitutions and equivalents will be apparent to those skilled in the art without departing from the scope of the present disclosure as described in the claims.
In the present invention, the terms "mounted," "connected," "secured," and other terms are to be construed broadly, unless expressly defined or limited otherwise, such as: can be fixedly connected, can also be detachably connected, and can also be integrally connected; the connection can be mechanical connection or electrical connection; either directly or indirectly through intervening, two internal communication elements or an interaction between two elements. It will be understood by those of ordinary skill in the art that the above terms are intended to have the meanings provided herein as appropriate.
In the description herein, reference is made to the terms "one embodiment," "an example," "an instance" or "some examples," and this description is intended to include a particular feature (feature), structure, material, or characteristic (characteristic), at least one embodiment or example, in connection with the described embodiment or example. In this specification, the terms schematically indicated above are not necessarily used for the same embodiment or example. Furthermore, the particular features, materials, or characteristics described in any one or more of the embodiments or examples are in any suitable manner. Moreover, those of skill in the art may describe or incorporate the examples and combinations thereof in the specification of the various embodiments.
All of the features disclosed in this specification (including any accompanying claims, abstract and drawings), and/or all of the steps of any method or process so disclosed, may be combined in any combination, except combinations where at least some of such features and/or steps are mutually exclusive.
Each feature disclosed in this specification (including any accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise. Thus, unless expressly stated otherwise, each feature disclosed is one example only of a generic series of equivalent or similar features.
While the foregoing is directed to various embodiments of the present invention, other and further embodiments of the invention may be devised without departing from the basic scope thereof. The scope of the invention is determined by the appended claims. The invention is not limited to the embodiments, versions or examples described which are included to enable a person having ordinary skill in the art to make and use the invention, when combined with the information and knowledge available to those having ordinary skill in the art.