CN114661000A - Production method based on edge calculation, edge calculation equipment and system - Google Patents
Production method based on edge calculation, edge calculation equipment and system Download PDFInfo
- Publication number
- CN114661000A CN114661000A CN202011540553.8A CN202011540553A CN114661000A CN 114661000 A CN114661000 A CN 114661000A CN 202011540553 A CN202011540553 A CN 202011540553A CN 114661000 A CN114661000 A CN 114661000A
- Authority
- CN
- China
- Prior art keywords
- production
- data
- parameters
- processing platform
- product
- Prior art date
- Legal status (The legal status 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 status listed.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS], computer integrated manufacturing [CIM]
- G05B19/41865—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS], computer integrated manufacturing [CIM] characterised by job scheduling, process planning, material flow
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/30—Nc systems
- G05B2219/32—Operator till task planning
- G05B2219/32252—Scheduling production, machining, job shop
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
Abstract
The embodiment of the disclosure relates to a production method based on edge calculation, an edge calculation device and a system, wherein the production method based on edge calculation is implemented by the edge calculation device, and the method comprises the following steps: acquiring a production process and product parameters corresponding to the production process; controlling the processing platform to produce according to the production process and the product parameters to obtain a target product; acquiring production data of the processing platform; and inputting the production procedures, the product parameters and the production data into a preset first analysis model for analysis, and adjusting the production parameters of the processing platform according to an analysis result.
Description
Technical Field
Embodiments of the present disclosure relate to the field of smart manufacturing technologies, and more particularly, to an edge calculation-based production method, an edge calculation device, an edge calculation-based production system, and a computer-readable storage medium.
Background
In traditional production line, set up station and production line beat according to production technology, this kind of production line arrangement mode has the problem of station discretization to lead to producing the line beat and be difficult to adjust, can not adjust according to the change flexibility of producing the product. In addition, when the performance of a product is tested, detection data of each station needs to be acquired respectively, the calculation force is not aggregated, and the requirements of low delay and quick response on a production line side cannot be met. Therefore, it is necessary to propose a production method based on edge calculation.
Disclosure of Invention
It is an object of embodiments of the present disclosure to provide an edge calculation-based production method, an edge calculation device, an edge calculation-based production system, and a computer-readable storage medium, to improve flexibility of a production line.
According to a first aspect of the present disclosure, there is provided an edge calculation-based production method, implemented by an edge calculation apparatus, the method comprising:
acquiring a production process and product parameters corresponding to the production process;
controlling the processing platform to produce according to the production process and the product parameters to obtain a target product;
acquiring production data of the processing platform;
and inputting the production procedures, the product parameters and the production data into a preset first analysis model for analysis, and adjusting the production parameters of the processing platform according to an analysis result.
Optionally, the processing platform comprises a plurality of production execution machines and industrial cameras;
the production data comprises production parameters of a production execution machine corresponding to the production process and a product picture which is shot by the industrial camera and corresponds to the production process.
Optionally, the product parameters include processing parameters of the part;
the processing platform includes a plurality of production execution machines;
before controlling the processing platform to perform production according to the production process and the product parameters, the method further comprises:
acquiring detection data of the part detection platform on the part, wherein the detection data of the part at least comprises geometric data of the part;
and inputting the detection data of the parts and the processing parameters of the parts into a preset second analysis model for analysis so as to select a proper production execution machine for the production process related to the parts.
Optionally, the geometry data of the part comprises at least one of:
shape information of the part;
dimensional information of the part.
Optionally, the product parameter comprises standard data of the part;
before controlling the processing platform to perform production according to the production process and the product parameters, the method further comprises:
acquiring detection data of the part detection platform on the part;
and inputting the detection data of the parts and the standard data of the parts into a preset third analysis model for analysis so as to filter out unqualified parts.
Optionally, the product parameter comprises standard data of a target product;
after controlling the processing platform to perform production according to the production process and the product parameters, the method further comprises:
acquiring detection data of a target product by a complete machine test platform;
and inputting the detection data of the target product and the standard data of the target product into a preset fourth analysis model for analysis so as to filter out unqualified target products.
Optionally, after controlling the processing platform to perform the production according to the production process and the product parameters, the method further includes:
acquiring detection data of a target product by a complete machine test platform;
the step of inputting the production process, the product parameters and the production data into a preset first analysis model for analysis, and adjusting the production parameters of the processing platform according to an analysis result comprises the following steps:
and inputting the detection data of the target product, the production process, the product parameters and the production data into a preset first analysis model for analysis, and adjusting the production parameters of the processing platform according to an analysis result.
According to a second aspect of the present disclosure, there is provided an edge computing device comprising:
the system comprises a first acquisition module, a second acquisition module and a control module, wherein the first acquisition module is used for acquiring production procedures and product parameters corresponding to the production procedures;
the control module is used for controlling the processing platform to produce according to the production procedures and the product parameters so as to obtain a target product;
the second acquisition module is used for acquiring the production data of the processing platform;
the adjusting module is used for inputting the production procedures, the product parameters and the production data into a preset first analysis model for analysis and adjusting the production parameters of the processing platform according to an analysis result;
alternatively, the first and second electrodes may be,
the edge computing device comprises a processor and a memory, wherein the memory stores computer instructions, and the computer instructions are executed by the processor to execute the method provided by the first aspect of the disclosure.
According to a third aspect of the present disclosure, there is provided an edge calculation-based production system, comprising:
a processing platform;
a component detection platform;
a complete machine testing platform;
the edge computing equipment comprises a visual detection analysis system which is respectively connected with the processing platform, the part detection platform and the complete machine test platform and is used for acquiring production data of the processing platform, detection data of parts and detection data of target products and respectively analyzing the production data of the processing platform, the detection data of the parts and the detection data of the target products to obtain analysis results.
According to a fourth aspect of the present disclosure, computer instructions are stored thereon, which, when executed by a processor, perform the method provided by the first aspect of the present disclosure.
The production method provided by the embodiment of the disclosure can acquire the production data of the processing platform in real time, and adjust the production parameters of the processing platform according to the production procedures, the product parameters corresponding to the production procedures and the production data of the processing platform, so that the processing process is controlled, and the problem of discrete production procedures of the existing production line is solved.
The production method provided by the embodiment of the disclosure can adjust the production parameters of the processing platform according to the production procedures, the product parameters corresponding to the production procedures and the production data of the processing platform, so as to be suitable for processing different production procedures and different target products, thereby completing the processing of different products based on the same production system and solving the problem of poor flexibility of the existing production line.
Features of embodiments of the present specification and advantages thereof will become apparent from the following detailed description of exemplary embodiments thereof, which proceeds with reference to the accompanying drawings.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the specification and together with the description, serve to explain the principles of the embodiments of the specification.
FIG. 1 is a diagram of a hardware configuration of a production system that can be used to implement one embodiment;
FIG. 2 is a schematic flow diagram of a method of edge computation based production according to one embodiment of the present disclosure;
FIG. 3 is a functional block diagram of an edge computing device according to one embodiment of the present disclosure;
FIG. 4 is a functional block diagram of an edge computing device according to one embodiment of the present disclosure;
FIG. 5 is a functional block diagram of an edge computing based production system according to one embodiment of the present disclosure.
Detailed Description
Various exemplary embodiments of the present specification will now be described in detail with reference to the accompanying drawings.
The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the embodiments, their application, or uses.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, further discussion thereof is not required in subsequent figures.
< production System >
Fig. 1 is a schematic diagram of a configuration of a production system to which a production method based on edge calculation according to an embodiment of the present disclosure can be applied.
As shown in fig. 1, the production system 100 of the present embodiment includes an edge computing apparatus 1000, a processing platform 2000, a component inspection platform 3000, and a complete machine testing platform 4000. The edge computing device 1000 is in communication connection with the machining platform 2000, the edge computing device 1000 is in communication connection with the part detection platform 3000, and the edge computing device 1000 is in communication connection with the complete machine test platform 4000 through a network 5000. The network 5000 may be a wireless network or a wired network, and may be a local area network or a wide area network.
The production system provided by the embodiment can be suitable for assembling electronic products. The electronic product can be, for example, a smart speaker, a wireless headset, a wearable device, a mobile terminal, and the like.
Edge computing refers to an open platform integrating network, computing, storage and application core capabilities on one side close to an object or a data source, a nearest-end service is provided nearby, an application program is initiated on the edge side, a faster network service response is generated, and basic requirements of the industry on real-time business, application intelligence, safety, privacy protection and the like are met.
In one embodiment of the present disclosure, the edge computing device may be disposed on the production line side. The edge computing device 1000 may be configured to obtain production data of the processing platform, detection data of the component, and detection data of the target product, and analyze the production data of the processing platform, the detection data of the component, and the detection data of the target product, respectively, so as to implement control of a production process of an electronic product.
In one embodiment of the present disclosure, the edge computing device 1000 may be as shown in fig. 1, including a processor 1100, a memory 1200, an interface apparatus 1300, a communication apparatus 1400, a display apparatus 1500, an input apparatus 1600. The processor 1100 may include, but is not limited to, a central processing unit CPU, a microprocessor MCU, or the like. The memory 1200 includes, for example, a ROM (read only memory), a RAM (random access memory), a nonvolatile memory such as a hard disk, and the like. The interface device 1300 includes, for example, various bus interfaces such as a serial bus interface (including a USB interface), a parallel bus interface, and the like. Communication device 1400 is capable of wired or wireless communication, for example. The display device 1500 is, for example, a liquid crystal display, an LED display, a touch display, or the like. The input device 1600 may include, for example, a touch screen, a keyboard, a mouse, and the like.
The edge computing device 1000 includes a visual inspection analysis system. The edge computing device 1000 may be, for example, a raspberry pi platform based device with learning analysis capabilities.
In this embodiment, the memory 1200 of the edge computing device 1000 is configured to store instructions for controlling the processor 1100 to operate to implement or support the implementation of the edge computing based production method according to any of the embodiments. The skilled person can design the instructions according to the solution disclosed in the present specification. How the instructions control the operation of the processor is well known in the art and will not be described in detail here.
Those skilled in the art will appreciate that although a plurality of means of the edge computing device 1000 are shown in fig. 1, the edge computing device 1000 of the present specification may refer to only some of the means therein, for example, only the processor 1100, the memory 1200, the communication means 1400, and the like.
The processing platform 2000 may be used for processing electronic products.
In one embodiment of the present disclosure, the processing platform 2000 may be as shown in fig. 1, including a processor 2100, a memory 2200, an interface device 2300, a communication device 2400, a camera device 2500, and an actuator 2600. The processor 2100 may include, but is not limited to, a central processing unit CPU, a microprocessor MCU, and the like. The memory 2200 includes, for example, a ROM (read only memory), a RAM (random access memory), a nonvolatile memory such as a hard disk, and the like. The interface device 2300 includes, for example, various bus interfaces, such as a serial bus interface (including a USB interface), a parallel bus interface, and the like. Communication device 2400 is capable of wired or wireless communication, for example. The camera arrangement 2500 comprises at least one camera for taking images, the camera arrangement 2500 may be, for example, an industrial camera. The actuator 2600 is used to assemble an electronic product, and the actuator 2600 may include, for example, a clamp, a cutter, and the like. For example, the actuator 2600 comprises a multi-degree of freedom robotic arm.
In this embodiment, the memory 2200 of the processing platform 2000 is configured to store instructions for controlling the processor 2100 to operate to implement or support the implementation of an edge-computing based production method according to any of the embodiments. The skilled person can design the instructions according to the solution disclosed in the present specification. How the instructions control the operation of the processor is well known in the art and will not be described in detail herein.
It should be understood by those skilled in the art that although a plurality of devices of the processing platform 2000 are illustrated in fig. 1, the processing platform 2000 of the present embodiments may refer to only some of the devices therein.
The component inspection platform 3000 may be used to inspect whether components used to compose an electronic product are qualified.
In one embodiment of the present disclosure, the part inspection platform 3000 may include a processor 3100, a memory 3200, an interface device 3300, a communication device 3400, an image capture device 3500, and an inspection mechanism 3600, as shown in fig. 1. The processor 3100 may include, but is not limited to, a central processing unit CPU, a microprocessor MCU, etc. The memory 3200 includes, for example, a ROM (read only memory), a RAM (random access memory), a nonvolatile memory such as a hard disk, and the like. The interface device 3300 includes, for example, various bus interfaces such as a serial bus interface (including a USB interface), a parallel bus interface, and the like. The communication device 3400 can perform wired or wireless communication, for example. The camera 3500 comprises at least one camera for taking images, the camera 3500 may be, for example, an industrial camera. The detecting mechanism 3600 is used for detecting whether the parts are qualified.
The complete machine test platform 4000 may be used to test the performance of an electronic product.
In an embodiment of the present disclosure, the complete machine testing platform 4000 may have a hardware structure similar to that of the component detecting platform 3000, for example, the complete machine testing platform 4000 may include a processor, a memory, an interface device, a communication device, a camera device, a detecting mechanism, and the like, which are not described herein again.
The production system 100 shown in fig. 1 is merely illustrative and is in no way intended to limit the present specification, its application, or uses. For example, although fig. 1 shows only one edge computing device 1000, one processing platform 2000, one part inspection platform 3000, and one complete machine test platform 4000, the number of each is not meant to be limiting, and the production system 100 may include a plurality of edge computing devices 1000, a plurality of processing platforms 2000, a plurality of part inspection platforms 3000, and/or a plurality of complete machine test platforms 4000.
< method examples >
FIG. 2 illustrates an edge calculation based production method of one embodiment of the present disclosure, which may be implemented, for example, by the production system 100 shown in FIG. 1.
The edge calculation-based production method provided by this embodiment may include the following steps S2100 to S2400.
S2100, obtaining the production process and the product parameters corresponding to the production process.
The production process of electronic products comprises a plurality of production processes, such as a feeding process, a processing process, an assembling process, a blanking process, a part detection process, a product testing process and the like.
The product parameters may include parameters of the component, parameters of the target product. Wherein, the parameters of the part may include: pre-or post-machining geometric parameters of the component, such as the size and shape of the component; processing parameters of the part, such as opening, position, shape, size and depth of the part; assembly parameters between parts, for example, assembly gap between parts. The parameters of the target product may include: geometric parameters of the target product, for example, the shape and size of the target product; the appearance of the target product; the performance parameters of the target product, such as an intelligent sound box, frequency response, sensitivity, sound pressure level and the like.
The product parameters correspond to the production process. For example, for a machining process, the product parameters may include pre-machining or post-machining geometric parameters of the part, part machining parameters, and the like; for the assembly process, the product parameters may include the machined geometric parameters of the parts, the assembly gaps between the parts, the assembly process requirements of the parts, and the like; for a product testing procedure, the product parameters may include performance parameters of the target product.
S2200, controlling the processing platform to produce according to the production process and the product parameters to obtain the target product.
The processing platform comprises a plurality of production execution machines, and the production execution machines are machines directly performing production processing. The production execution machine may include, for example, a robotic arm, a tool, a fixture, and the like. The robot arms may include, for example, a grabbing robot arm, a welding robot arm, a dispensing robot arm, etc., wherein the grabbing robot arm may further include a two-finger robot arm, a three-finger robot arm, and a four-finger robot arm. In this embodiment, an appropriate production execution machine can be selected for any production process according to actual production requirements. The production execution machine includes, for example, the aforementioned execution mechanism 2600. The production requirement may be, for example, a processing parameter of the component.
In an embodiment of the present disclosure, the product parameter may include a processing parameter of the component, and before controlling the processing platform to perform the production according to the production process and the product parameter, the production method further includes: steps S3100 to S3200.
S3100, acquiring detection data of the part detection platform on the part, wherein the detection data of the part at least comprises geometric data of the part.
In this embodiment, the geometry data of the part includes at least one of: shape information of the component, and size information of the component.
In one embodiment, the inspection data of the part further includes material data. The material data includes at least one of: the material, physical properties and chemical properties of the parts.
And S3200, inputting the detection data of the parts and the processing parameters of the parts into a preset second analysis model for analysis so as to select a proper production execution machine for the production process related to the parts.
The second analysis model is used for outputting a production execution machine corresponding to a production process related to the part according to the input detection data of the part and the processing parameter of the part.
By taking the feeding process as an example, a proper grabbing mechanical arm can be selected according to the geometric data of the parts. For example, for regular-shaped and smaller-sized parts, a two-finger robot arm may be selected. For parts with irregular shapes and larger sizes, a four-finger mechanical arm can be selected.
Taking the machining process as an example, a suitable cutter can be selected according to the detection data and the machining parameters of the part, for example, a suitable cutter can be selected according to the material of the part and the size of the opening, so that the machining efficiency can be improved, and the cutter can be prevented from being damaged in the machining process.
Taking the assembly process as an example, a suitable production execution machine can be selected according to the connection mode of the parts. For example, when the component is connected by bonding, the dispenser arm is selected. For example, when the connection mode of the parts is a welding mode, the welding mechanical arm is selected.
In this embodiment, before the processing platform is controlled to perform production according to the production process and the product parameters, the method further includes a step of detecting the components, so as to filter out the unqualified components before production, thereby improving the yield of production.
In one embodiment of the present disclosure, the product parameters include standard data for the part. Before controlling the processing platform to produce according to the production process and the product parameters, the production method further comprises the following steps: steps S4100 to S4200.
S4100, acquiring detection data of the parts by the parts detection platform.
The part detection platform can be used for detecting whether parts for forming the electronic product are qualified or not.
And S4200, inputting the detection data of the parts and the standard data of the parts into a preset third analysis model for analysis so as to filter out unqualified parts.
The inspection data of the component part may include, for example, inspection dimensions and inspection performance parameters.
The standard data of the parts includes standard dimensions and standard performance parameters of the parts. The standard performance parameter may be determined according to the type of the component part.
In a specific implementation, the detected size of the component may be input into the third analysis model, and the detected size of the component may be compared with the standard size based on the third analysis model. And outputting a prompt message that the part is qualified when the difference value between the detection size and the standard size is not larger than a first threshold value. And under the condition that the difference value between the detection size and the standard size is larger than a first threshold value, outputting prompt information that the part is unqualified, and controlling the part detection platform to remove the unqualified part.
In specific implementation, the detection performance parameters of the component may be input into the third analysis model, and the detection performance parameters of the component may be compared with the standard performance parameters based on the third analysis model. And outputting qualified prompt information of the part under the condition that the difference value between the detection performance parameter and the standard performance parameter is not greater than a second threshold value. And under the condition that the difference value between the detection performance parameter and the standard performance parameter is larger than a second threshold value, outputting prompt information that the part is unqualified, and controlling the part detection platform to remove the unqualified part.
During specific implementation, the detection size and the detection performance parameters of the part can be input into the third analysis model, and the detection size and the standard size of the part and the detection performance parameters and the standard performance parameters of the part are respectively compared to filter out unqualified parts.
In one embodiment, the production execution machine further includes an industrial camera, the inspection data of the part may further include an inspection picture of the part, and the standard data of the part may further include a standard picture of the part. The standard picture may include one or more pictures of the part.
In specific implementation, the detection picture of the part may be input into the third analysis model, and based on the third analysis model, the detection picture and the standard picture are compared to identify whether the part is a target part, where the target part is a part required by the current production process.
According to the embodiment of the disclosure, before the processing platform is controlled to produce according to the production process and the product parameters, the parts can be detected in advance to filter out unqualified parts and parts which do not correspond to the production process, so that the problems in the production process can be found in time, the process is saved, and the production efficiency is improved.
In this embodiment, after the processing platform is controlled to produce according to the production process and the product parameters, the method further includes a step of detecting the target product, so as to filter out the unqualified target product after production, and improve the qualification rate of the target product.
In one embodiment of the present disclosure, after controlling the processing platform to perform production according to the production process and the product parameters, the production method further includes: and S5100-S5200.
S5100, detection data of the complete machine test platform on the target product are obtained.
The complete machine test platform 4000 may be used to test the performance of an electronic product.
The detection data of the target product may include, for example, a complete machine picture of the target product, a complete machine size of the target product, and a complete machine performance parameter of the target product.
S5200, inputting the detection data of the target product and the standard data of the target product into a preset fourth analysis model for analysis so as to filter out unqualified target products.
The standard data of the target product can comprise a complete machine reference picture of the target product, a complete machine reference size of the target product and a complete machine reference performance parameter of the target product.
In specific implementation, the whole machine picture, the whole machine size and the whole machine performance parameters of the target product are input into the fourth analysis model, and the whole machine picture and the whole machine reference picture, the whole machine size and the whole machine reference size, the whole machine performance parameters and the whole machine reference performance parameters are respectively compared based on the fourth analysis model to filter out unqualified target products.
According to the embodiment of the disclosure, after the processing platform is controlled to produce according to the production procedures and the product parameters, the target product can be detected in advance to filter out unqualified target products, and the qualification rate of the products is improved.
And S2300, acquiring production data of the processing platform.
In this embodiment, the processing platform includes a production execution machine and an industrial camera.
In one embodiment, the production data may include production parameters of a production execution machine corresponding to the production process.
The production parameter of the production execution machine may be, for example, an operating parameter of the production execution machine.
Taking the machining process as an example, an appropriate tool may be selected according to the detection data and machining parameters of the component, for example, an appropriate tool may be selected according to the material of the component and the size of the hole, and the feeding amount of the tool including the feeding amount in the X direction, the feeding amount in the Y direction, and the feeding amount in the Z direction and the machining route may be determined according to the position, shape, and size of the hole.
Taking the assembly process as an example, a suitable production execution machine can be selected according to the connection mode of the parts. For example, when the connection mode of the parts is the bonding mode, the dispensing mechanical arm is selected, and further, the moving parameters of the dispensing mechanical arm are determined according to the assembly position and the assembly gap of the parts, and the dispensing amount of the dispensing mechanical arm is determined according to the shape of the parts. For example, when the connection mode of the parts is the welding mode, the welding mechanical arm is selected, and further, the moving parameters of the welding mechanical arm are determined according to the assembly position and the assembly gap of the parts.
In another embodiment, the production data may also include a product picture taken by the industrial camera corresponding to the production process.
The product picture comprises a picture of an intermediate product in the execution process of a production procedure and a picture of a final product after the production procedure is finished.
And S2400, inputting the production process, the product parameters and the production data into a preset first analysis model for analysis, and adjusting the production parameters of the processing platform according to the analysis result.
In the embodiment, an appropriate production execution machine is selected for the production process according to the product parameters, the production execution machine is controlled to work, and production data of the production execution machine and a product image shot by an industrial camera are acquired during the working process. And then, the production process, the product parameters and the production data are input into a preset first analysis model, and based on the preset first analysis model, the production data of the production execution machine can be analyzed to determine whether the production process has faults or not in the execution process, and whether the production process is correct or not is judged according to the product image, so that the production parameters of the processing platform are adjusted, and the production of unqualified products is avoided.
The production method provided by the embodiment of the disclosure can acquire the production data of the processing platform in real time, and adjust the production parameters of the processing platform according to the production procedures, the product parameters corresponding to the production procedures and the production data of the processing platform, so that the processing process is controlled, and the problem of discrete production procedures of the existing production line is solved.
The production method provided by the embodiment of the disclosure can adjust the production parameters of the processing platform according to the production procedures, the product parameters corresponding to the production procedures and the production data of the processing platform, so as to be suitable for processing different production procedures and different target products, thereby completing the processing of different products based on the same production system and solving the problem of poor flexibility of the existing production line.
In one embodiment of the present disclosure, after controlling the processing platform to perform production according to the production process and the product parameters, the production method further includes: and acquiring detection data of the whole machine test platform on the target product.
In this embodiment, step S2400 may further include: and inputting the detection data, the production process, the product parameters and the production data of the target product into a preset first analysis model for analysis, and adjusting the production parameters of the processing platform according to the analysis result.
In this embodiment, an appropriate production execution machine is selected for the production process according to the product parameters, and the production execution machine is controlled to operate. After the processing platform produces according to the production process and the product parameters, the detection data, the production process, the product parameters and the production data of the target product are obtained, and the detection data, the production process, the product parameters and the production data of the target product are input into the first analysis model. Therefore, when the target product is unqualified, the production process with problems and the reason for causing the target product to be unqualified can be determined according to the detection data of the target product, the product parameters corresponding to the production process and the production data of the processing platform. Furthermore, according to the embodiment of the disclosure, the production parameters of the processing platform can be adjusted in time according to the detection data of the target product, the product parameters corresponding to the production process, and the production data of the processing platform, so as to avoid the same problem occurring in the subsequent processing process, thereby improving the qualification rate of the product.
< first embodiment of the apparatus >
FIG. 3 illustrates a functional block diagram of an edge computing device, according to one embodiment.
In this embodiment, the edge computing device 3000 may include a first acquisition module 3100, a control module 3200, a second acquisition module 3300, and an adjustment module 3400.
The first acquisition module 3100 is configured to acquire a production process and a product parameter corresponding to the production process.
The control module 3200 is used for controlling the processing platform to produce according to the production procedures and the product parameters so as to obtain a target product.
In one embodiment, the processing platform includes a plurality of production execution machines and an industrial camera;
the production data comprises production parameters of a production execution machine corresponding to the production process and a product picture corresponding to the production process and shot by the industrial camera.
The second obtaining module 3300 is configured to obtain production data of the processing platform.
The adjusting module 3400 is configured to input the production process, the product parameters, and the production data into a preset first analysis model for analysis, and adjust the production parameters of the processing platform according to an analysis result.
In one embodiment, the product parameters include processing parameters of the part; the processing platform includes a plurality of production execution machines; the edge computing apparatus 3000 further includes a third acquisition module and a first analysis module.
And the third acquisition module is used for acquiring the detection data of the part detection platform on the part, wherein the detection data of the part at least comprises the geometric data of the part.
In one example, the geometry data of the part includes at least one of:
shape information of the part;
dimensional information of the part.
And the first analysis module is used for inputting the detection data of the parts and the processing parameters of the parts into a preset second analysis model for analysis so as to select a proper production execution machine for the production process related to the parts.
In one embodiment, the product parameters include standard data for the part; the edge computing device 3000 further comprises a fourth acquisition module and a second analysis module.
And the fourth acquisition module is used for acquiring the detection data of the part detection platform on the part.
And the second analysis module is used for inputting the detection data of the parts and the standard data of the parts into a preset third analysis model for analysis so as to filter out unqualified parts.
In one embodiment, the product parameters include standard data for a target product; the edge computing apparatus 3000 further includes a fifth obtaining module and a third analyzing module.
And the fifth acquisition module is used for acquiring the detection data of the complete machine test platform on the target product.
And the third analysis module is used for inputting the detection data of the target product and the standard data of the target product into a preset fourth analysis model for analysis so as to filter out unqualified target products.
In one embodiment, the first obtaining module 3100 is further configured to obtain detection data of the complete testing platform on the target product.
The adjusting module 3400 is further configured to input the detection data of the target product, the production process, the product parameters, and the production data into a preset first analysis model for analysis, and adjust the production parameters of the processing platform according to an analysis result.
< example II of the apparatus >
FIG. 4 illustrates a functional block diagram of an edge computing device, according to one embodiment.
In this embodiment, the edge computing device 4000 may include a memory 4100 and a processor 4200.
The memory 4100 is used for storing executable commands. The processor 4200 is configured to perform the methods described in any of the method embodiments under the control of executable commands stored in the memory 4100.
The edge computing equipment provided by the embodiment of the disclosure can acquire the production data of the processing platform in real time, and adjust the production parameters of the processing platform according to the production procedures, the product parameters corresponding to the production procedures and the production data of the processing platform, so that the processing process is controlled, and the problem of discrete production procedures of the existing production line is solved.
The edge calculating equipment provided by the embodiment of the disclosure can adjust the production parameters of the processing platform according to the production procedures, the product parameters corresponding to the production procedures and the production data of the processing platform, so that the edge calculating equipment is suitable for processing different production procedures and different target products, can complete the processing of different products based on the same production system, and solves the problem of poor flexibility of the existing production line.
< System embodiment >
FIG. 5 illustrates a functional block diagram of a production system based on edge computing according to one embodiment. The production system 5000 may be the production system 100 as shown in fig. 1.
In this embodiment, the production system 5000 may include a processing platform 5100, a component inspection platform 5200, a complete machine test platform 5300, and an edge computing device 5400.
The edge computing device 5400 includes a visual inspection analysis system, which is connected to the processing platform 5100, the component inspection platform 5200, and the complete machine test platform 5300, respectively, and is configured to acquire production data of the processing platform, inspection data of the component, and inspection data of the target product, and analyze the production data of the processing platform, the inspection data of the component, and the inspection data of the target product, respectively, to obtain an analysis result, so as to adjust production parameters of the processing platform according to the analysis result.
In one embodiment, the edge computing device 5400 can be the edge computing device 1000 as shown in fig. 1.
The production system provided by the embodiment of the disclosure can acquire the production data of the processing platform in real time, and adjust the production parameters of the processing platform according to the production procedures, the product parameters corresponding to the production procedures and the production data of the processing platform, so that the processing process can be controlled, and the problem of discrete production procedures of the existing production line is solved.
The production system provided by the embodiment of the disclosure can adjust the production parameters of the processing platform according to the production procedures, the product parameters corresponding to the production procedures and the production data of the processing platform, so as to be suitable for processing different production procedures and different target products, thereby completing the processing of different products based on the same production system, and solving the problem of poor flexibility of the existing production line.
< computer-readable storage Medium >
Embodiments of the present disclosure also provide a computer-readable storage medium having stored thereon computer instructions that, when executed by a processor, perform the edge computing-based production method of any one of the preceding embodiments.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, as for the device and apparatus embodiments, since they are substantially similar to the method embodiments, the description is relatively simple, and reference may be made to some descriptions of the method embodiments for relevant points.
The foregoing description has been directed to specific embodiments of this disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
Embodiments of the present description may be an apparatus, method, and/or computer program product. The computer program product may include a computer-readable storage medium having computer-readable program instructions embodied thereon for causing a processor to implement aspects of embodiments of the specification.
The computer-readable storage medium may be a tangible device that can hold and store the instructions for use by the instruction execution device. The computer readable storage medium may be, for example, but not limited to, an electronic memory device, a magnetic memory device, an optical memory device, an electromagnetic memory device, a semiconductor memory device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include 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 Disc (DVD), a memory stick, a floppy disk, a mechanical coding device, such as punch cards or in-groove projection structures having instructions stored thereon, and any suitable combination of the foregoing. Computer-readable storage media as used herein is not to be construed as transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission medium (e.g., optical pulses through a fiber optic cable), or electrical signals transmitted through electrical wires.
The computer-readable program instructions described herein may be downloaded from a computer-readable storage medium to a respective computing/processing device, or to an external computer or external storage device via a network, such as the internet, a local area network, a wide area network, and/or a wireless network. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. The 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 in the respective computing/processing device.
The computer program instructions for carrying out operations for embodiments of the present description may be assembly instructions, Instruction Set Architecture (ISA) instructions, machine related instructions, microcode, firmware instructions, state setting data, or 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. In the case of a remote computer, 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). In some embodiments, an electronic circuit, such as a programmable logic circuit, a Field Programmable Gate Array (FPGA), or a Programmable Logic Array (PLA), can execute computer-readable program instructions to implement various aspects of embodiments of the present specification by utilizing state information of the computer-readable program instructions to personalize the electronic circuit.
Aspects of embodiments of the present specification are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (devices) and computer program products according to embodiments of the specification. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer-readable program instructions.
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, programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer-readable medium storing the instructions comprises an article of manufacture including instructions which implement 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 devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer, other programmable apparatus or other devices implement the functions/acts specified in the flowchart and/or block diagram block or blocks.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present description. In this regard, 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). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, 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. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions. It is well known to those skilled in the art that implementation by hardware, by software, and by a combination of software and hardware are equivalent.
The foregoing description of the embodiments of the present specification has been presented for purposes of illustration and description, but is not intended to be exhaustive or limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope of the described embodiments. The terms used herein were chosen in order to best explain the principles of the embodiments, the practical application, or technical improvements to the techniques in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.
Claims (10)
1. A method of edge-computing-based production, implemented by an edge computing device, the method comprising:
acquiring a production process and product parameters corresponding to the production process;
controlling the processing platform to produce according to the production process and the product parameters to obtain a target product;
acquiring production data of the processing platform;
and inputting the production procedures, the product parameters and the production data into a preset first analysis model for analysis, and adjusting the production parameters of the processing platform according to an analysis result.
2. The method of claim 1, wherein the processing platform comprises a plurality of production execution machines and industrial cameras;
the production data comprises production parameters of a production execution machine corresponding to the production process and a product picture which is shot by the industrial camera and corresponds to the production process.
3. The method of claim 1, wherein the product parameters include processing parameters of the part;
the processing platform includes a plurality of production execution machines;
before controlling the processing platform to perform production according to the production process and the product parameters, the method further comprises:
acquiring detection data of the part detection platform on the part, wherein the detection data of the part at least comprises geometric data of the part;
and inputting the detection data of the parts and the processing parameters of the parts into a preset second analysis model for analysis so as to select a proper production execution machine for the production process related to the parts.
4. The method of claim 3, wherein the part geometry data comprises at least one of:
shape information of the part;
dimensional information of the part.
5. The method of claim 1, wherein the product parameters include standard data for parts;
before controlling the processing platform to perform production according to the production process and the product parameters, the method further comprises:
acquiring detection data of the part detection platform on the part;
and inputting the detection data of the parts and the standard data of the parts into a preset third analysis model for analysis so as to filter out unqualified parts.
6. The method of claim 1, wherein the product parameters include standard data for a target product;
after controlling the processing platform to perform production according to the production process and the product parameters, the method further comprises:
acquiring detection data of a target product by a complete machine test platform;
and inputting the detection data of the target product and the standard data of the target product into a preset fourth analysis model for analysis so as to filter out unqualified target products.
7. The method of claim 1, wherein after controlling the processing platform to produce according to the production sequence and the product parameters, the method further comprises:
acquiring detection data of a target product by a complete machine test platform;
the step of inputting the production process, the product parameters and the production data into a preset first analysis model for analysis, and adjusting the production parameters of the processing platform according to an analysis result comprises the following steps:
and inputting the detection data of the target product, the production process, the product parameters and the production data into a preset first analysis model for analysis, and adjusting the production parameters of the processing platform according to an analysis result.
8. An edge computing device, comprising:
the system comprises a first acquisition module, a second acquisition module and a control module, wherein the first acquisition module is used for acquiring production procedures and product parameters corresponding to the production procedures;
the control module is used for controlling the processing platform to produce according to the production procedures and the product parameters so as to obtain a target product;
the second acquisition module is used for acquiring the production data of the processing platform;
the adjusting module is used for inputting the production procedures, the product parameters and the production data into a preset first analysis model for analysis and adjusting the production parameters of the processing platform according to an analysis result;
alternatively, the first and second electrodes may be,
the edge computing device comprising a processor and a memory having stored therein computer instructions that, when executed by the processor, perform the method of any of claims 1-7.
9. An edge-computing-based production system comprising:
a processing platform;
a component detection platform;
a complete machine testing platform;
the edge computing equipment comprises a visual detection and analysis system, wherein the visual detection and analysis system is respectively connected with the processing platform, the part detection platform and the complete machine test platform, and is used for acquiring production data of the processing platform, detection data of parts and detection data of target products, and respectively analyzing the production data of the processing platform, the detection data of the parts and the detection data of the target products to obtain analysis results.
10. A computer readable storage medium having stored thereon computer instructions which, when executed by a processor, perform the method of any of claims 1-7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011540553.8A CN114661000A (en) | 2020-12-23 | 2020-12-23 | Production method based on edge calculation, edge calculation equipment and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011540553.8A CN114661000A (en) | 2020-12-23 | 2020-12-23 | Production method based on edge calculation, edge calculation equipment and system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114661000A true CN114661000A (en) | 2022-06-24 |
Family
ID=82024228
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011540553.8A Pending CN114661000A (en) | 2020-12-23 | 2020-12-23 | Production method based on edge calculation, edge calculation equipment and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114661000A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115808911A (en) * | 2023-02-02 | 2023-03-17 | 成都秦川物联网科技股份有限公司 | Industrial Internet of things regulation and control method and system for producing defective products in production line |
-
2020
- 2020-12-23 CN CN202011540553.8A patent/CN114661000A/en active Pending
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115808911A (en) * | 2023-02-02 | 2023-03-17 | 成都秦川物联网科技股份有限公司 | Industrial Internet of things regulation and control method and system for producing defective products in production line |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Pilati et al. | Learning manual assembly through real-time motion capture for operator training with augmented reality | |
| TW201947451A (en) | Interactive processing method, apparatus and processing device for vehicle loss assessment and client terminal | |
| CN111757098B (en) | Debugging method and device after installation of intelligent face monitoring camera, camera and medium | |
| US9519570B2 (en) | Progressive snapshots in automated software testing | |
| CN111784663A (en) | Method and device for detecting parts, electronic equipment and storage medium | |
| CN106791804B (en) | For the smear detecting method and device of camera module | |
| CN113537374B (en) | Method for generating countermeasure sample | |
| CN110941942A (en) | Method, device and system for checking circuit schematic diagram | |
| CN111080633A (en) | Screen defect detection method and device, terminal equipment and storage medium | |
| CN114080590A (en) | Robotic bin picking system and method using advanced scanning techniques | |
| CN114661000A (en) | Production method based on edge calculation, edge calculation equipment and system | |
| US11055207B2 (en) | Automatic generation of integration tests from unit tests | |
| CN108646679B (en) | distributed visual detection system and industrial personal computer | |
| US20190080858A1 (en) | System and method for providing functional safety monitoring of relay contacts | |
| US10525599B1 (en) | Automatic detection of screen area and camera assisted movement of robotic arm | |
| CN111486790A (en) | Full-size detection method and device for battery | |
| US20190383698A1 (en) | Automatic analysis of a set of optical fibers of an optical cable | |
| CN103634545A (en) | Method for processing event of projector using pointer and an electronic device thereof | |
| US20180089822A1 (en) | Automated diagnostics for device display and camera | |
| CN109186471B (en) | Lead height detection method and device | |
| CN114088349A (en) | Method, device and system for testing color-combination prism | |
| CN113269106A (en) | Method and device for detecting state of conveyor belt of conveying tool | |
| KR101194367B1 (en) | Inspection apparatus and methode for user interface | |
| CN108536220B (en) | Wearable device and maintenance processing method | |
| Ramler et al. | What you see is what you test-augmenting software testing with computer vision |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |