CN110808222A - Control method and device of manufacturing equipment - Google Patents
Control method and device of manufacturing equipment Download PDFInfo
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- CN110808222A CN110808222A CN201911120220.7A CN201911120220A CN110808222A CN 110808222 A CN110808222 A CN 110808222A CN 201911120220 A CN201911120220 A CN 201911120220A CN 110808222 A CN110808222 A CN 110808222A
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- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01L—SEMICONDUCTOR DEVICES NOT COVERED BY CLASS H10
- H01L21/00—Processes or apparatus adapted for the manufacture or treatment of semiconductor or solid state devices or of parts thereof
- H01L21/67—Apparatus specially adapted for handling semiconductor or electric solid state devices during manufacture or treatment thereof; Apparatus specially adapted for handling wafers during manufacture or treatment of semiconductor or electric solid state devices or components ; Apparatus not specifically provided for elsewhere
- H01L21/67005—Apparatus not specifically provided for elsewhere
- H01L21/67242—Apparatus for monitoring, sorting or marking
- H01L21/67253—Process monitoring, e.g. flow or thickness monitoring
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- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01L—SEMICONDUCTOR DEVICES NOT COVERED BY CLASS H10
- H01L22/00—Testing or measuring during manufacture or treatment; Reliability measurements, i.e. testing of parts without further processing to modify the parts as such; Structural arrangements therefor
- H01L22/10—Measuring as part of the manufacturing process
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- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01L—SEMICONDUCTOR DEVICES NOT COVERED BY CLASS H10
- H01L22/00—Testing or measuring during manufacture or treatment; Reliability measurements, i.e. testing of parts without further processing to modify the parts as such; Structural arrangements therefor
- H01L22/10—Measuring as part of the manufacturing process
- H01L22/12—Measuring as part of the manufacturing process for structural parameters, e.g. thickness, line width, refractive index, temperature, warp, bond strength, defects, optical inspection, electrical measurement of structural dimensions, metallurgic measurement of diffusions
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- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01L—SEMICONDUCTOR DEVICES NOT COVERED BY CLASS H10
- H01L22/00—Testing or measuring during manufacture or treatment; Reliability measurements, i.e. testing of parts without further processing to modify the parts as such; Structural arrangements therefor
- H01L22/10—Measuring as part of the manufacturing process
- H01L22/14—Measuring as part of the manufacturing process for electrical parameters, e.g. resistance, deep-levels, CV, diffusions by electrical means
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- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01L—SEMICONDUCTOR DEVICES NOT COVERED BY CLASS H10
- H01L22/00—Testing or measuring during manufacture or treatment; Reliability measurements, i.e. testing of parts without further processing to modify the parts as such; Structural arrangements therefor
- H01L22/20—Sequence of activities consisting of a plurality of measurements, corrections, marking or sorting steps
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- Engineering & Computer Science (AREA)
- Manufacturing & Machinery (AREA)
- Computer Hardware Design (AREA)
- Microelectronics & Electronic Packaging (AREA)
- Power Engineering (AREA)
- Physics & Mathematics (AREA)
- Condensed Matter Physics & Semiconductors (AREA)
- General Physics & Mathematics (AREA)
- Electroluminescent Light Sources (AREA)
- Devices For Indicating Variable Information By Combining Individual Elements (AREA)
Abstract
The invention provides a method and a device for controlling manufacturing equipment, wherein the method comprises the following steps: acquiring a first process parameter of the process equipment at the current process stage, and training the first process parameter to obtain first prediction data; judging whether the display panel meets a preset condition or not according to the first prediction data; and when the display panel does not meet the preset condition, performing exception handling on the processing equipment or the display panel. The control method and the control device of the processing equipment can improve the product yield.
Description
[ technical field ] A method for producing a semiconductor device
The invention relates to the technical field of display, in particular to a control method and a control device of manufacturing equipment.
[ background of the invention ]
One manufacturing equipment can prepare a plurality of display panels, and the plurality of display panels are also display panels in the same batch. At present, the display panels of the same batch are processed by adopting preset processing parameters.
However, at present, the display panel is only detected after the manufacturing process is finished to determine whether the panel is qualified, so that the detected display panel cannot be repaired once being unqualified, the production cost is increased, and the product yield is reduced.
Therefore, it is necessary to provide a method and an apparatus for controlling a manufacturing device to solve the problems of the prior art.
[ summary of the invention ]
The invention aims to provide a method and a device for controlling manufacturing equipment, which can improve the product yield and reduce the production cost.
In order to solve the above technical problems, the present invention provides a method for controlling a manufacturing apparatus, wherein the manufacturing apparatus is used for manufacturing a display panel;
acquiring a first process parameter of the process equipment at the current process stage, and training the first process parameter to obtain first prediction data;
judging whether the display panel meets a preset condition or not according to the first prediction data;
and when the display panel does not meet the preset condition, performing exception handling on the processing equipment or the display panel.
The invention also provides a control device of the manufacturing equipment, wherein the manufacturing equipment is used for preparing the display panel; the device comprises:
the first training module is used for acquiring a first process parameter of the process equipment at the current process stage and training the first process parameter to obtain first prediction data;
the judging module is used for judging whether the display panel meets a preset condition or not according to the first prediction data;
and the processing module is used for performing exception handling on the processing equipment or the display panel when the display panel does not meet the preset condition.
The control method and the control device of the manufacturing equipment comprise the steps of obtaining a first manufacturing process parameter of the manufacturing equipment at the current manufacturing process stage, and training the first manufacturing process parameter to obtain first prediction data; judging whether the display panel meets a preset condition or not according to the first prediction data; when the display panel does not meet the preset condition, performing exception handling on the processing equipment or the display panel; the estimated measurement data can be obtained before the manufacturing process to predict whether the display panel is abnormal or not in advance, so that unqualified products obtained by subsequent preparation are avoided, the waste of materials is avoided, the product yield is improved, and the production cost is reduced.
[ description of the drawings ]
FIG. 1 is a flow chart illustrating a method for controlling a processing tool according to one embodiment of the present invention;
FIG. 2 is a flow chart of a method for controlling a second processing apparatus according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a control apparatus of the manufacturing apparatus of the present invention;
FIG. 4 is a schematic diagram of a preferred structure of a control device of the manufacturing apparatus of the present invention.
[ detailed description ] embodiments
The following description of the embodiments refers to the accompanying drawings for illustrating the specific embodiments in which the invention may be practiced. In the present invention, directional terms such as "up", "down", "front", "back", "left", "right", "inner", "outer", "side", etc. refer to directions of the attached drawings. Accordingly, the directional terms used are used for explanation and understanding of the present invention, and are not used for limiting the present invention. In the drawings, elements having similar structures are denoted by the same reference numerals.
The terms "first," "second," and the like in the description and claims of the present application and in the above-described drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions.
The processing equipment is used for manufacturing the display panel. The processing equipment comprises a plurality of types, and each type of processing equipment processes different film layers of the display panel.
As shown in fig. 1, the method for controlling a processing apparatus of the present embodiment includes:
s101, obtaining a first process parameter of the process equipment at the current process stage, and training the first process parameter to obtain first prediction data;
for example, before the current process stage begins, the process parameters of the processing equipment are set, and then the process parameters are directly obtained to obtain the first process parameters, where the process parameters include necessary parameters for manufacturing each film layer in the display panel, such as exposure time, illumination intensity, illumination time, etching depth, and developing time.
And then, training the process parameters of the current process stage to obtain first prediction data. In one embodiment, a first process parameter of the manufacturing tool at the current process stage may be input into a target training model for training to obtain the first prediction data, wherein the first prediction data is also the predicted test data, and may include measured values of film thickness, resistance, and the like.
S102, judging whether the display panel meets a preset condition or not according to the first prediction data;
for example, in an embodiment, the first prediction data may be compared with a preset threshold to determine whether the display panel meets the process requirement, if the display panel does not meet the process requirement, step S103 is executed, otherwise, no processing is performed.
Of course, it is understood that in other embodiments, an average of the first prediction data may be obtained, and whether the average is within a preset range may be determined to determine whether the display panel satisfies a preset condition.
S103, when the display panel does not meet the preset condition, performing exception handling on the processing equipment or the display panel.
For example, when the display panel does not satisfy the predetermined condition, the display panel or the processing equipment is processed in time, such as repairing the current display panel or reworking the current display panel in time, or adjusting the processing parameters of the processing equipment, checking whether the processing equipment needs to be maintained, and the like.
The control method of the manufacturing equipment comprises the steps of obtaining a first manufacturing process parameter of the manufacturing equipment at the current manufacturing process stage, and training the first manufacturing process parameter to obtain first prediction data; judging whether the display panel meets a preset condition or not according to the first prediction data; when the display panel does not meet the preset condition, performing exception handling on the processing equipment or the display panel; the estimated measurement data can be obtained before the manufacturing process to predict whether the display panel is abnormal or not in advance, so that unqualified products obtained by subsequent preparation are avoided, the waste of materials is avoided, the product yield is improved, and the production cost is reduced.
As shown in fig. 2, the method for controlling a processing apparatus of the present embodiment includes:
s201, obtaining initial process parameters of the processing equipment in the previous processing stage;
for example, the process parameters of the processing equipment in the previous processing stage are obtained, and then the process parameters are directly obtained to obtain the initial process parameters, wherein the process parameters include necessary parameters for manufacturing each film layer in the display panel, and the process parameters include, for example, exposure time, light intensity, light time, etching depth, developing time, and the like.
S202, training the initial process parameters through a plurality of preset training models respectively to obtain a plurality of initial prediction data;
for example, a plurality of training models are preset, wherein the training models may be neural networks.
In one embodiment, each training model is used to train the process parameters obtained in step S201, and a plurality of prediction data is obtained, wherein each training model obtains one prediction data.
S203, selecting one preset training model from a plurality of preset training models as a target training model according to the plurality of initial prediction data and preset measurement data;
for example, the predetermined measurement data is measurement data of a display panel prepared by the processing equipment in a previous process stage, such as the measurement data obtained by the measurement module in one embodiment.
In an embodiment, one of the preset training models is selected as a target training model from a plurality of preset training models according to the prediction data and the preset measurement data obtained in step S202, where the target training model is also an optimal training model.
In an embodiment, the step of selecting one of the plurality of preset training models as the target training model according to the plurality of initial prediction data and the preset measurement data includes:
s2031, selecting initial prediction data matched with the preset measurement data from the plurality of initial prediction data to obtain matched prediction data;
for example, the initial prediction data closest to the preset measurement data is selected from the plurality of initial prediction data, and the closest initial prediction data is used as the matching prediction data, so that the estimated test data is closest to the actually measured data.
S2032, taking a preset training model corresponding to the matching prediction data as a target training model.
For example, a training model corresponding to the initial prediction data closest to the preset measurement data is used as a target training model, and the target training model is used for estimating the measurement data of the display panel prepared by the processing equipment in the current processing stage.
S204, obtaining a first process parameter of the processing equipment at the current process stage, and inputting the first process parameter of the processing equipment at the current process stage into a target training model for training;
for example, before the current process stage begins, the process parameters of the processing equipment are set, and then the process parameters are directly obtained to obtain the first process parameters, where the process parameters include necessary parameters for manufacturing each film layer in the display panel, such as exposure time, illumination intensity, illumination time, etching depth, and developing time.
And then, training the process parameters of the current process stage to obtain first prediction data. In one embodiment, a first process parameter of the manufacturing tool at the current process stage may be input into a target training model for training to obtain the first prediction data, wherein the first prediction data is also the predicted test data, and may include measured values of film thickness, resistance, and the like.
S205, judging whether the display panel meets a preset condition or not according to the first prediction data;
for example, in an embodiment, the first prediction data may be compared with a preset threshold to determine whether the display panel meets the process requirement, and if the display panel does not meet the process requirement, step S206 is executed, otherwise, no processing is performed.
In one embodiment, the step of determining whether the display panel satisfies a preset condition according to the first prediction data includes:
s2051, comparing the first prediction data with a preset threshold value;
and S2052, when the first prediction data exceeds the preset threshold, determining that the display panel does not meet the preset condition.
For example, whether the first prediction data exceeds a preset threshold is judged, if yes, the display panel is determined not to meet preset conditions, the preset threshold includes a maximum of film thickness and a maximum of resistance, and when the first prediction data exceeds the preset threshold, the produced panel is indicated to be unqualified, so that the processing equipment or the current display panel is determined not to meet preset production requirements.
Of course, it is understood that in other embodiments, an average of the first prediction data may be obtained, and whether the average is within a preset range may be determined to determine whether the display panel satisfies a preset condition.
And S206, when the display panel does not meet the preset condition, performing exception handling on the processing equipment.
For example, when the display panel does not satisfy the predetermined condition, the display panel or the processing equipment is processed in time, such as repairing the current display panel or reworking the current display panel in time, or adjusting the processing parameters of the processing equipment, checking whether the processing equipment needs to be maintained, and the like.
The control method of the processing equipment of the invention also obtains the initial processing parameters of the processing equipment in the previous processing stage on the basis of the previous embodiment; respectively training the initial process parameters through a plurality of preset training models to obtain a plurality of initial prediction data; selecting one preset training model from a plurality of preset training models according to the plurality of initial prediction data and preset measurement data as a target training model, and inputting a first process parameter of the process equipment at the current process stage into the target training model for training; because the optimal training model is determined through the prediction data of the display panel of the previous manufacturing process so as to obtain the predicted measurement data of the display panel of the current manufacturing process, the accuracy of the predicted measurement data is improved, and misoperation is avoided.
The invention also provides a control device of the manufacturing equipment, which comprises a first training module 21, a judging module 22 and a processing module 23.
The first training module 21 is configured to obtain a first process parameter of the manufacturing equipment at the current process stage, and train the first process parameter to obtain first prediction data;
a judging module 22, configured to judge whether the display panel meets a preset condition according to the first prediction data;
the processing module 23 is configured to perform exception handling on the manufacturing equipment or the display panel when the display panel does not meet a preset condition.
In an embodiment, the determining module 23 is specifically configured to: comparing the first prediction data to a preset threshold; and when the first prediction data exceeds the preset threshold value, determining that the display panel does not meet a preset condition.
In an embodiment, the first training module 21 is specifically configured to: and inputting the first process parameter of the process equipment at the current process stage into a target training model for training.
As shown in fig. 4, the apparatus may further include: an acquisition module 31, a second training module 32 and a determination module 33.
An obtaining module 31, configured to obtain an initial process parameter of the processing apparatus in a previous process stage;
the second training module 32 is configured to train the initial process parameters through a plurality of preset training models, respectively, to obtain a plurality of initial prediction data;
and the determining module 33 is configured to select one of the preset training models as a target training model according to the plurality of initial prediction data and preset measurement data.
In an embodiment, the determining module 33 is specifically configured to select initial prediction data matched with the preset measurement data from the plurality of initial prediction data to obtain matched prediction data; and taking a preset training model corresponding to the matching prediction data as a target training model.
The control device of the manufacturing equipment comprises a first manufacturing parameter of the manufacturing equipment at the current manufacturing stage, and a first prediction data is obtained by training the first manufacturing parameter; judging whether the display panel meets a preset condition or not according to the first prediction data; when the display panel does not meet the preset condition, performing exception handling on the processing equipment or the display panel; the estimated measurement data can be obtained before the manufacturing process to predict whether the display panel is abnormal or not in advance, so that unqualified products obtained by subsequent preparation are avoided, the waste of materials is avoided, the product yield is improved, and the production cost is reduced.
In summary, although the present invention has been described with reference to the preferred embodiments, the above-described preferred embodiments are not intended to limit the present invention, and those skilled in the art can make various changes and modifications without departing from the spirit and scope of the present invention, therefore, the scope of the present invention shall be determined by the appended claims.
Claims (10)
1. The control method of a processing device is characterized in that the processing device is used for preparing a display panel; the method comprises the following steps:
acquiring a first process parameter of the process equipment at the current process stage, and training the first process parameter to obtain first prediction data;
judging whether the display panel meets a preset condition or not according to the first prediction data;
and when the display panel does not meet the preset condition, performing exception handling on the processing equipment or the display panel.
2. The method as claimed in claim 1, wherein the step of determining whether the display panel satisfies a predetermined condition according to the first prediction data comprises:
comparing the first prediction data to a preset threshold;
and when the first prediction data exceeds the preset threshold value, determining that the display panel does not meet a preset condition.
3. The method as claimed in claim 1, wherein the step of training the first process parameter of the manufacturing tool at the current stage of the manufacturing process to obtain the first predicted data comprises:
and inputting the first process parameter of the process equipment at the current process stage into a target training model for training.
4. The method as claimed in claim 3, wherein before the step of inputting the first process parameter of the manufacturing tool at the current manufacturing stage into the target training model for training, the method further comprises:
acquiring initial process parameters of the processing equipment in the previous processing stage;
respectively training the initial process parameters through a plurality of preset training models to obtain a plurality of initial prediction data;
and selecting one preset training model from a plurality of preset training models as a target training model according to the plurality of initial prediction data and preset measurement data.
5. The method of claim 4, wherein the step of selecting one of a plurality of pre-set training models as the target training model according to the plurality of initial prediction data and pre-set metrology data comprises:
selecting initial prediction data matched with the preset measurement data from the plurality of initial prediction data to obtain matched prediction data;
and taking a preset training model corresponding to the matching prediction data as a target training model.
6. The control device of the processing equipment is characterized in that the processing equipment is used for preparing a display panel; the device comprises:
the first training module is used for acquiring a first process parameter of the process equipment at the current process stage and training the first process parameter to obtain first prediction data;
the judging module is used for judging whether the display panel meets a preset condition or not according to the first prediction data;
and the processing module is used for performing exception handling on the processing equipment or the display panel when the display panel does not meet the preset condition.
7. The apparatus of claim 6, wherein the determining module is specifically configured to:
comparing the first prediction data to a preset threshold; and when the first prediction data exceeds the preset threshold value, determining that the display panel does not meet a preset condition.
8. The apparatus of claim 6, wherein the first training module is specifically configured to:
and inputting the first process parameter of the process equipment at the current process stage into a target training model for training.
9. The apparatus of claim 8, further comprising:
the obtaining module is used for obtaining initial process parameters of the processing equipment in the previous processing stage;
the second training module is used for respectively training the initial process parameters through a plurality of preset training models to obtain a plurality of initial prediction data;
and the determining module is used for selecting one preset training model from a plurality of preset training models as a target training model according to the plurality of initial prediction data and preset measurement data.
10. The control apparatus of claim 9, wherein the determination module is configured to,
selecting initial prediction data matched with the preset measurement data from the plurality of initial prediction data to obtain matched prediction data; and taking a preset training model corresponding to the matching prediction data as a target training model.
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| CN201911120220.7A CN110808222A (en) | 2019-11-15 | 2019-11-15 | Control method and device of manufacturing equipment |
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| CN201911120220.7A CN110808222A (en) | 2019-11-15 | 2019-11-15 | Control method and device of manufacturing equipment |
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| US20110112999A1 (en) * | 2009-11-06 | 2011-05-12 | Inotera Memories, Inc. | Method for predicting and warning of wafer acceptance test value |
| US20120016643A1 (en) * | 2010-07-16 | 2012-01-19 | National Tsing Hua University | Virtual measuring system and method for predicting the quality of thin film transistor liquid crystal display processes |
| CN101963802B (en) * | 2010-08-25 | 2012-08-15 | 江苏大学 | Virtual measurement method in batch manufacture procedure and system therefor |
| CN110399996A (en) * | 2018-04-25 | 2019-11-01 | 深圳富桂精密工业有限公司 | Processing procedure abnormality pre-judging method and anticipation system |
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2019
- 2019-11-15 CN CN201911120220.7A patent/CN110808222A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20110112999A1 (en) * | 2009-11-06 | 2011-05-12 | Inotera Memories, Inc. | Method for predicting and warning of wafer acceptance test value |
| US20120016643A1 (en) * | 2010-07-16 | 2012-01-19 | National Tsing Hua University | Virtual measuring system and method for predicting the quality of thin film transistor liquid crystal display processes |
| CN101963802B (en) * | 2010-08-25 | 2012-08-15 | 江苏大学 | Virtual measurement method in batch manufacture procedure and system therefor |
| CN110399996A (en) * | 2018-04-25 | 2019-11-01 | 深圳富桂精密工业有限公司 | Processing procedure abnormality pre-judging method and anticipation system |
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Application publication date: 20200218 |