CN118656271B - IC substrate manufacturing data monitoring method, system and medium based on cloud computing - Google Patents
IC substrate manufacturing data monitoring method, system and medium based on cloud computing Download PDFInfo
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- CN118656271B CN118656271B CN202411131895.2A CN202411131895A CN118656271B CN 118656271 B CN118656271 B CN 118656271B CN 202411131895 A CN202411131895 A CN 202411131895A CN 118656271 B CN118656271 B CN 118656271B
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Abstract
The application discloses an IC carrier plate manufacturing data monitoring method, system and medium based on cloud computing, which mainly relate to the technical field of carrier plate manufacturing monitoring and are used for solving the problem that the existing scheme mainly focuses on self-monitoring of a single flow and cannot realize comprehensive analysis of integral data. The method comprises the steps of determining a first fog computing server and a second fog computing server, uploading manufacturing data, equipment data, purchasing data and result data to the first fog computing server, uploading the manufacturing data, the equipment data and the purchasing data to the second fog computing server in real time, uploading the manufacturing data, the equipment data and the purchasing data to a cloud computing terminal through the first fog computing server to obtain model parameters of a trained neural network model, and sending the model parameters to the second fog computing server to enable the second fog computing server to update the internal neural network model through the model parameters to obtain predicted result data.
Description
Technical Field
The present application relates to the field of IC carrier manufacturing technologies, and in particular, to a cloud computing-based IC carrier manufacturing data monitoring method, system, and medium.
Background
An IC carrier board (INTEGRATED CIRCUIT integrated circuit), also known as an IC package substrate or package substrate, is a highly technically difficult product in the PCB (Printed Circuit Board printed circuit board) industry. The semiconductor IC chip is used as a connecting bridge between the chip and the PCB to realize signal transmission connection. Protect, fix, support IC chip to provide the heat dissipation passageway, ensure the normal work and the stability of chip. Compared with the common PCB, the IC carrier board has the advantages of thinner board body, finer line width and line distance, smaller aperture and the like, so that more precise alignment technology, electroplating technology and the like are required.
The existing monitoring scheme of the IC carrier plate manufacturing process is that a high-precision sensor or a vision system is used for realizing real-time monitoring of manufacturing speed, manufacturing time, manufacturing quantity and defect rate of plate processing. And the qualification rate and the dimensional accuracy of parameters such as the position, the direction, the size and the like of the components in the mounting process are monitored through a machine vision system. Automatic test equipment or manual inspection is used to achieve comprehensive inspection of the finished circuit board.
However, the above solution mainly focuses on self-monitoring of a single process and cannot realize comprehensive analysis of overall data, so that a method, a system and a medium for monitoring manufacturing data of an IC carrier based on cloud computing are needed, and the problem that the existing solution mainly focuses on self-monitoring of a single process and cannot realize comprehensive analysis of overall data is solved.
Disclosure of Invention
Aiming at the defects in the prior art, the application provides a cloud computing-based method, a cloud computing-based system and a cloud computing-based medium for monitoring manufacturing data of an IC carrier, which are used for solving the problem that the existing scheme mainly focuses on self-monitoring of a single flow and cannot realize comprehensive analysis of integral data.
According to a first aspect, the application provides a cloud computing-based method for monitoring manufacturing data of an IC carrier, the method comprises the steps of acquiring manufacturing data of the IC carrier through a preset sensor on a manufacturing line, determining corresponding first fog computing servers and second fog computing servers based on the type of the IC carrier, the manufacturing speed, the manufacturing time and the manufacturing quantity, acquiring equipment data, purchase data and result data of manufacturing equipment corresponding to the IC carrier through an IC carrier data recording server, wherein the equipment data at least comprise working states, operation parameters and fault information, the purchase data at least comprise purchase raw material types, supplier names and purchase dates, the result data at least comprise defect types, defect rates, qualification rates and dimensional accuracy, determining corresponding first fog computing servers and second fog computing servers based on the position information of the preset sensor and the position information of the IC carrier data recording server, uploading the manufacturing data, the equipment data, the purchase data and the result data to the second fog computing servers in real time, uploading the manufacturing data, the equipment data and the purchase data to the first fog computing servers, transmitting the corresponding to the first fog computing servers through the preset time, acquiring the data in a neural network model, training the cloud computing model, and obtaining the result data in the cloud computing model by the cloud computing model, and training the cloud computing model by the cloud computing model, and inputting the manufacturing data, the equipment data and the purchase data obtained in real time into the neural network model to obtain the prediction result data.
The method comprises the steps of acquiring equipment data, purchase data and result data of manufacturing equipment corresponding to an IC carrier through an IC carrier data recording server, acquiring the equipment data of the manufacturing equipment corresponding to the IC carrier through an equipment data uploading interface of the IC carrier data recording server, acquiring the purchase data through a purchase uploading terminal which is in communication connection with the IC carrier data recording server, and acquiring the result data through a detection terminal which is in communication connection with the IC carrier data recording server.
The method comprises the steps of obtaining a plurality of mist computing servers from an idle mist computing server set based on the type of an IC carrier plate, and further selecting two mist computing servers with a linear distance between the position information of a preset sensor and the position information of an IC carrier plate data recording server being smaller than a preset distance range from the mist computing servers based on the position information of the mist computing servers, wherein the position information is longitude and latitude information, and one of the two mist computing servers is determined to be the first mist computing server and the other is determined to be the second mist computing server.
Further, the first fog calculation server and the second fog calculation server both comprise a newly-added data uploading interface for acquiring newly-added participation data of the IC carrier board, the newly-added participation data, manufacturing data, equipment data, purchasing data and result data are uploaded to the cloud calculation terminal together after the newly-added participation data are acquired by the first fog calculation server, then an initial neural network model is trained again to acquire model parameters of the trained neural network model, the neural network model is updated after model parameters corresponding to the newly-added participation data are acquired by the second fog calculation server, and the newly-added participation data, the manufacturing data, the equipment data and the purchasing data are taken as input data after the neural network model is updated, and the neural network model is input.
Further, after inputting the manufacturing data, the equipment data and the purchase data obtained in real time into the neural network model to obtain the prediction result data, the method further comprises the step of sending the prediction result data to a preset detection terminal.
The application provides a cloud computing-based Integrated Circuit (IC) carrier manufacturing data monitoring system, which comprises a sensor preset on a manufacturing line and used for acquiring manufacturing data of an IC carrier, wherein the manufacturing data at least comprise an IC carrier type, a manufacturing speed, manufacturing time and manufacturing quantity, an IC carrier data recording server is used for acquiring equipment data, purchase data and result data of manufacturing equipment corresponding to the IC carrier, the equipment data at least comprise working states, operation parameters and fault information, the purchase data at least comprise purchase raw material types, supplier names and purchase dates, the result data at least comprise defect types, defect rates and qualification rates, dimensional accuracy, a determining module is used for determining corresponding first fog computing servers and second fog computing servers based on the IC carrier type, position information of the preset sensor and position information of the IC carrier data recording server, uploading the manufacturing data, the equipment data, the purchase data and the result data to the second fog computing servers in real time, uploading the manufacturing data, the equipment data and the purchase data to the first fog computing servers, the first fog computing servers and the first cloud computing servers and obtaining the result data through a cloud computing model, training the cloud computing model by using the first cloud computing servers and the cloud computing servers in the cloud computing model, and obtaining the result data through a cloud computing model, and inputting the manufacturing data, the equipment data and the purchasing data obtained in real time into the neural network model to obtain the prediction result data.
The IC carrier plate data recording server further comprises an equipment data uploading interface and a communication connection component, wherein the equipment data uploading interface is used for acquiring equipment data of manufacturing equipment corresponding to the IC carrier plate, the communication connection component is used for establishing communication connection with a purchase uploading terminal to acquire purchase data, and the communication connection with a detection terminal to acquire result data.
The method comprises the steps of acquiring a plurality of mist computing servers from a set of idle mist computing servers based on the type of an Integrated Circuit (IC) carrier of the IC carrier, selecting two mist computing servers with the linear distance between the position information of the preset sensor and the position information of a data recording server of the IC carrier being smaller than a preset distance range from the mist computing servers based on the position information of the mist computing servers, wherein the position information is longitude and latitude information, and determining any one of the two mist computing servers as the first mist computing server and the other as the second mist computing server.
The first fog calculation server is further used for uploading the new participation data, manufacturing data, equipment data, purchasing data and result data to the cloud calculation terminal after the new participation data are acquired by the first fog calculation server, further training the initial neural network model again to acquire model parameters of the trained neural network model, the second fog calculation server is further used for updating the neural network model after the model parameters corresponding to the new participation data are acquired, and inputting the new participation data, the manufacturing data, the equipment data and the purchasing data into the neural network model after the neural network model is updated.
In a third aspect, the present application provides a non-volatile computer storage medium having stored thereon computer instructions that, when executed, implement a cloud computing based IC carrier manufacturing data monitoring method as in any of the above.
As will be appreciated by those skilled in the art, the present application has at least the following beneficial effects:
According to the application, the manufacturing data, the equipment data, the purchasing data and the result data are obtained through the sensor and the IC carrier plate data recording server which are preset on the manufacturing line, so that the neural network model is trained, and the trained neural network model is obtained. As the result data is uploaded subsequently and has hysteresis, the result data corresponding to the current manufacturing data, the equipment data and the purchasing data is predicted through the trained neural network model, the result data can be obtained through the comprehensive analysis of the Integrated Circuit (IC) carrier plate through the whole data, and the problem that the comprehensive analysis of the whole data cannot be realized due to the fact that the existing scheme mainly focuses on self-monitoring of a single process is solved.
In addition, the application relates to two fog calculation servers, wherein one fog calculation server performs data acquisition of a preset IC carrier plate type, updates and trains a neural network model of a cloud calculation terminal, and sends model parameters to the other fog calculation server, so that the neural network model in the other fog calculation server can always adapt to data change, and has higher detection precision.
Drawings
Some embodiments of the present disclosure are described below with reference to the accompanying drawings, in which:
fig. 1 is a flowchart of a method for monitoring IC carrier board manufacturing data based on cloud computing according to an embodiment of the present application.
Fig. 2 is a schematic diagram of an internal structure of an IC carrier manufacturing data monitoring system based on cloud computing according to an embodiment of the present application.
Detailed Description
It should be understood by those skilled in the art that the embodiments described below are only preferred embodiments of the present disclosure, and do not represent that the present disclosure can be realized only by the preferred embodiments, which are merely for explaining the technical principles of the present disclosure, not for limiting the scope of the present disclosure. Based on the preferred embodiments provided by the present disclosure, all other embodiments that may be obtained by one of ordinary skill in the art without inventive effort shall still fall within the scope of the present disclosure.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises an element.
The following describes the technical scheme provided by the embodiment of the application in detail through the attached drawings.
The embodiment of the application provides a cloud computing-based method for monitoring manufacturing data of an IC carrier plate, which mainly comprises the following steps:
step 110, acquiring manufacturing data of the IC carrier by a sensor preset on a manufacturing line.
The manufacturing data includes at least an IC carrier type, a manufacturing speed, a manufacturing time, and a manufacturing number.
And 120, acquiring equipment data, purchase data and result data of manufacturing equipment corresponding to the IC carrier through the IC carrier data recording server.
The equipment data at least comprises working state, operation parameters and fault information, the purchase data at least comprises purchase raw material types, supplier names and purchase dates, and the result data at least comprises defect types, defect rates, qualification rates and dimensional accuracy. In addition, the result data is uploaded by the detection terminal of the subsequent test and has hysteresis.
The method comprises the following steps:
The method comprises the steps of obtaining equipment data of manufacturing equipment corresponding to an IC carrier through an equipment data uploading interface of an IC carrier data recording server, obtaining purchase data through a purchase uploading terminal which is in communication connection with the IC carrier data recording server, and obtaining result data through a detection terminal which is in communication connection with the IC carrier data recording server.
Step 130, determining a first fog calculation server and a second fog calculation server corresponding to the type of the IC carrier plate, the position information of a preset sensor and the position information of the IC carrier plate data recording server, uploading manufacturing data, equipment data, purchasing data and result data to the first fog calculation server, and uploading the manufacturing data, the equipment data and the purchasing data to the second fog calculation server in real time.
It should be noted that there are a preset number of fog calculating servers, the preset number is greater than 100, and the first fog calculating server and the second fog calculating server both have preset service types, and the preset service types and the IC carrier plate types have a one-to-one relationship. The fog computing server may be any feasible server capable of transmitting data and supporting network model operations.
The determining, based on the type of the IC carrier, the position information of the preset sensor and the position information of the IC carrier data recording server, the corresponding first fog calculating server and second fog calculating server may specifically be:
Based on the type of the IC carrier plate, acquiring a plurality of fog calculation servers from an idle fog calculation server set, further based on the position information of the fog calculation servers, selecting two fog calculation servers with the linear distance between the position information of a preset sensor and the position information of the data recording server of the IC carrier plate smaller than a preset distance range from the fog calculation servers, wherein the position information is longitude and latitude information, and determining that any one of the two fog calculation servers is a first fog calculation server and the other is a second fog calculation server.
And 140, uploading manufacturing data, equipment data, purchasing data and result data corresponding to the IC carrier plate in a preset time period to the cloud computing terminal through the first fog computing server, and training an initial neural network model in the cloud computing terminal through the manufacturing data, the equipment data, the purchasing data and the result data in the preset time period to obtain a trained neural network model and further obtain model parameters of the trained neural network model.
In addition, in order to realize compatibility with newly added parameter data, the first fog calculation server and the second fog calculation server related to the application both comprise newly added data uploading interfaces for acquiring newly added participation data of the IC carrier plate.
The method comprises the steps of obtaining newly added participation data by a first fog calculation server, uploading the newly added participation data, manufacturing data, equipment data, purchasing data and result data to a cloud calculation terminal, further training an initial neural network model again to obtain model parameters of a trained neural network model, updating the neural network model after obtaining model parameters corresponding to the newly added participation data by a second fog calculation server, and taking the newly added participation data, the manufacturing data, the equipment data and the purchasing data as input data after finishing updating the neural network model, and inputting the newly added participation data, the manufacturing data, the equipment data and the purchasing data into the neural network model.
And 150, issuing model parameters to a second fog calculation server through the cloud calculation terminal, enabling the second fog calculation server to update an internal neural network model through the model parameters, and inputting manufacturing data, equipment data and purchase data obtained in real time into the neural network model to obtain prediction result data.
After inputting the manufacturing data, the equipment data and the procurement data obtained in real time into the neural network model to obtain the prediction result data, the method further comprises:
And sending the predicted result data to a preset detection terminal.
In addition, the person skilled in the art can send the prediction result data to any feasible terminal according to the actual requirements.
In addition, fig. 2 is a schematic diagram of an IC carrier manufacturing data monitoring system based on cloud computing according to an embodiment of the present application. As shown in fig. 2, the system provided by the embodiment of the present application mainly includes:
The sensor 210 is preset on the manufacturing line and is used for acquiring manufacturing data of the IC carrier.
The manufacturing data includes at least an IC carrier type, a manufacturing speed, a manufacturing time, and a manufacturing number.
The IC carrier data recording server 220 is configured to obtain equipment data, purchase data, and result data of manufacturing equipment corresponding to the IC carrier.
The equipment data at least comprises working state, operation parameters and fault information, the purchase data at least comprises purchase raw material types, supplier names and purchase dates, and the result data at least comprises defect types, defect rates, qualification rates and dimensional accuracy.
The IC carrier data recording server 220 comprises an equipment data uploading interface and a communication connection component, wherein the equipment data uploading interface is used for acquiring equipment data of manufacturing equipment corresponding to the IC carrier, the communication connection component is used for establishing communication connection with a purchase uploading terminal to acquire purchase data, and the communication connection with a detection terminal to acquire result data.
The determining module 230 is configured to determine the corresponding first fog calculating server 240 and second fog calculating server 260 based on the type of the IC carrier board, the preset position information of the sensor and the position information of the IC carrier board data recording server 220, upload the manufacturing data, the equipment data, the purchasing data and the result data to the first fog calculating server 240, and upload the manufacturing data, the equipment data and the purchasing data to the second fog calculating server 260 in real time.
It should be noted that there are a preset number of fog calculating servers, the preset number is greater than 100, and the first fog calculating server 240 and the second fog calculating server 260 each have a preset service type, and the preset service type and the IC carrier plate type have a one-to-one relationship.
The determining module 230 includes a determining unit, configured to obtain a plurality of fog calculating servers from an idle fog calculating server set based on an IC carrier type of the IC carrier, and further select two fog calculating servers with a linear distance between the position information of the sensor and the position information of the IC carrier data recording server 220 smaller than a preset distance range from the fog calculating servers based on the position information of the fog calculating servers, where the position information is longitude and latitude information, and determine any one of the two fog calculating servers as the first fog calculating server 240 and the other as the second fog calculating server 260.
The first fog calculating server 240 is configured to upload manufacturing data, equipment data, purchase data and result data corresponding to the IC carrier board in a preset period of time to the cloud calculating terminal 250.
The cloud computing terminal 250 is configured to train an initial neural network model in the cloud computing terminal 250 through manufacturing data, equipment data, purchase data and result data in a preset time period, further obtain a trained neural network model, further obtain model parameters of the trained neural network model, and send the model parameters to the second mist computing server 260 through the cloud computing terminal 250.
And a second mist calculating server 260 for updating the internal neural network model by the model parameters, and inputting the manufacturing data, the equipment data and the purchase data obtained in real time into the neural network model to obtain the prediction result data.
In addition, the first fog calculating server 240 and the second fog calculating server 260 each include a new data uploading interface for acquiring new participation data of the IC carrier board.
The first fog calculating server 240 is further configured to upload the newly added participation data, the manufacturing data, the equipment data, the purchasing data and the result data to the cloud computing terminal 250 after the newly added participation data is acquired by the first fog calculating server 240, and further train the initial neural network model again to obtain model parameters of the trained neural network model.
The second fog calculating server 260 is further configured to update the neural network model after obtaining the model parameters corresponding to the newly added participation data, and input the newly added participation data, the manufacturing data, the equipment data and the purchasing data together as input data into the neural network model after completing the update of the neural network model.
In addition, the embodiment of the application also provides a nonvolatile computer storage medium, on which executable instructions are stored, and when the executable instructions are executed, the method for monitoring the manufacturing data of the IC carrier board based on cloud computing is realized.
Thus far, the technical solution of the present disclosure has been described in connection with the foregoing embodiments, but it is easily understood by those skilled in the art that the protective scope of the present disclosure is not limited to only these specific embodiments. The technical solutions in the above embodiments may be split and combined by those skilled in the art without departing from the technical principles of the present disclosure, and equivalent modifications or substitutions may be made to related technical features, which all fall within the scope of the present disclosure.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN113660336A (en) * | 2018-03-30 | 2021-11-16 | 北京忆芯科技有限公司 | Cloud computing and fog computing system using KV storage device |
| CN115443641A (en) * | 2020-03-26 | 2022-12-06 | 斯纳普公司 | Combine first UI content into second UI |
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| CN204155126U (en) * | 2014-09-26 | 2015-02-11 | 广东电网有限责任公司佛山供电局 | A kind of intelligent substation supervising device |
| CN116996577A (en) * | 2023-08-14 | 2023-11-03 | 南方电网数字平台科技(广东)有限公司 | Mist computing resource pre-allocation method, device, equipment and medium for electric power system |
| CN118409713B (en) * | 2024-07-01 | 2024-09-13 | 清河电子科技(山东)有限责任公司 | IC carrier production information processing method, system, electronic equipment and medium |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN113660336A (en) * | 2018-03-30 | 2021-11-16 | 北京忆芯科技有限公司 | Cloud computing and fog computing system using KV storage device |
| CN115443641A (en) * | 2020-03-26 | 2022-12-06 | 斯纳普公司 | Combine first UI content into second UI |
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