CN113687764A - Semiconductor product processing machine and processing method - Google Patents
Semiconductor product processing machine and processing method Download PDFInfo
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- CN113687764A CN113687764A CN202111056163.8A CN202111056163A CN113687764A CN 113687764 A CN113687764 A CN 113687764A CN 202111056163 A CN202111056163 A CN 202111056163A CN 113687764 A CN113687764 A CN 113687764A
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- 239000004065 semiconductor Substances 0.000 title claims abstract description 81
- 238000003672 processing method Methods 0.000 title claims abstract description 11
- 238000000034 method Methods 0.000 claims description 19
- 230000002452 interceptive effect Effects 0.000 claims description 17
- 230000001960 triggered effect Effects 0.000 claims description 7
- 238000004519 manufacturing process Methods 0.000 abstract description 14
- 238000005516 engineering process Methods 0.000 abstract description 6
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
- G06F3/048—Interaction techniques based on graphical user interfaces [GUI]
- G06F3/0487—Interaction techniques based on graphical user interfaces [GUI] using specific features provided by the input device, e.g. functions controlled by the rotation of a mouse with dual sensing arrangements, or of the nature of the input device, e.g. tap gestures based on pressure sensed by a digitiser
- G06F3/0488—Interaction techniques based on graphical user interfaces [GUI] using specific features provided by the input device, e.g. functions controlled by the rotation of a mouse with dual sensing arrangements, or of the nature of the input device, e.g. tap gestures based on pressure sensed by a digitiser using a touch-screen or digitiser, e.g. input of commands through traced gestures
- G06F3/04883—Interaction techniques based on graphical user interfaces [GUI] using specific features provided by the input device, e.g. functions controlled by the rotation of a mouse with dual sensing arrangements, or of the nature of the input device, e.g. tap gestures based on pressure sensed by a digitiser using a touch-screen or digitiser, e.g. input of commands through traced gestures for inputting data by handwriting, e.g. gesture or text
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/44—Arrangements for executing specific programs
- G06F9/451—Execution arrangements for user interfaces
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
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- G—PHYSICS
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/70—Determining position or orientation of objects or cameras
- G06T7/73—Determining position or orientation of objects or cameras using feature-based methods
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30108—Industrial image inspection
- G06T2207/30148—Semiconductor; IC; Wafer
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Abstract
The application relates to the technical field of semiconductor processing, in particular to a semiconductor product processing machine and a processing method, wherein the processing machine comprises: the image recognition device is used for acquiring a current image of the processed workpiece; the correlation sensor is used for detecting the actual coordinate of the position of the tip of the cutter; the full-automatic tuning and teaching machine table is used for generating a target processing action based on a preset zero coordinate, raising the position of a spindle, controlling a processed workpiece to execute the target processing action, and re-tuning and teaching the position of the processed workpiece to a position corresponding to the zero coordinate based on a current image and/or an actual coordinate after the processing of a semiconductor product is completed. Therefore, the problems that in the related technology, the precision, the yield and the production efficiency of semiconductor products are low and the like caused by manually processing the semiconductor products and adjusting the main shaft deviation are solved.
Description
Technical Field
The present disclosure relates to semiconductor processing technologies, and more particularly, to a semiconductor product processing machine and a semiconductor product processing method.
Background
With the increasing development of the semiconductor industry, the requirements on the production efficiency and the machining precision of the semiconductor material processing process in the industry are higher and higher. However, in the related art, the servo driver is usually manually controlled to drive the motor for semiconductor product processing and spindle deviation adjustment, which results in low precision and yield of semiconductor product processing and greatly reduced production efficiency.
Content of application
The application provides a semiconductor product processing machine and a processing method, which aim to solve the problems of low precision, yield and production efficiency of semiconductor products and the like caused by manual processing of the semiconductor products and adjustment of spindle deviation in the related technology.
An embodiment of a first aspect of the present application provides a semiconductor product processing machine, including: the image recognition device is used for acquiring a current image of the processed workpiece; the correlation sensor is used for detecting the actual coordinate of the position of the tip of the cutter; the full-automatic tuning and teaching machine is used for generating a target processing action based on a preset zero coordinate, raising the position of a spindle, controlling the processing workpiece to execute the target processing action, and re-tuning the position of the processing workpiece to a position corresponding to the zero coordinate based on the current image and/or the actual coordinate after the processing of a semiconductor product is completed.
Further, the full-automatic debugging machine platform is specifically configured to calculate a first debugging offset of an X axis and a Y axis according to the current image, generate a first coordinate debugging value based on the first debugging offset and the zero coordinate, and/or calculate a second debugging offset of a Z axis according to the actual coordinate, and generate a second coordinate debugging value based on the second debugging offset and the zero coordinate.
Further, still include: the system comprises an interactive interface and a control unit, wherein the interactive interface is provided with a display area and a plurality of function keys, the display area displays the current parameters and the current working mode of the semiconductor product processing machine, and the function keys comprise on-off function keys.
Further, still include: and the controller is used for controlling the full-automatic teaching machine to enter a working mode corresponding to the gesture action according to the gesture action input by the user after judging that the power-on and power-off function key is triggered.
Further, the gesture motion is in contact with or not in contact with the interactive interface.
In a second aspect of the present application, a method for processing a semiconductor product is provided, where the method is applied to the semiconductor product processing machine of the above embodiments, and includes the following steps: acquiring a current image of a processing workpiece acquired by an image recognition device; acquiring actual coordinates of the position of the tool tip detected by the correlation sensor; generating a target processing action based on a preset zero coordinate, raising the position of a spindle, controlling the processing workpiece to execute the target processing action, and re-teaching the position of the processing workpiece to a position corresponding to the zero coordinate based on the current image and/or the actual coordinate after the processing of the semiconductor product is completed.
Further, re-teaching the position of the processing workpiece to a position corresponding to the zero position coordinate based on the current image and the actual coordinate comprises: calculating a first debugging deviation of an X axis and a Y axis according to the current image, and generating a first coordinate debugging value based on the first debugging deviation and the zero position coordinate; and/or calculating a second debugging deviation of the Z axis according to the actual coordinate, and generating a second coordinate debugging value based on the second debugging deviation and the zero position coordinate.
Further, still include: and displaying the current parameters and the current working mode of the semiconductor product processing machine through an interactive interface.
Further, still include: and after judging that the startup and shutdown function key is triggered through the controller, entering a corresponding working mode according to the gesture action input by the user.
Further, the gesture motion is in contact with or not in contact with the interactive interface.
Therefore, the application has at least the following beneficial effects:
utilize processing semiconductor product that image recognition and location and high accuracy sensor can be accurate, and can full-automatic the teaching board main shaft direction, realize the full-automatic processing of semiconductor product and the full automatically regulated of main shaft deviation to can effectively improve the precision and the yields of semiconductor product processing, promote the production efficiency of semiconductor product. Therefore, the technical problems that precision, yield and production efficiency of semiconductor products are low and the like caused by manual processing of the semiconductor products and adjustment of spindle deviation in the related technology are solved.
Additional aspects and advantages of the present application will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the present application.
Drawings
The foregoing and/or additional aspects and advantages of the present application will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
FIG. 1 is a block schematic diagram of a semiconductor product processing machine according to an embodiment of the present application;
FIG. 2 is a schematic diagram of a procedure for calculating the deviation of a new tool or a new sample according to an embodiment of the present application;
FIG. 3 is a schematic diagram of a procedure for automatically inputting a deviation value to recover due coordinates according to an embodiment of the present disclosure;
FIG. 4 is a process flow diagram of a semiconductor product processing machine according to an embodiment of the present application;
fig. 5 is a flowchart of a method for processing a semiconductor product according to an embodiment of the present application.
Detailed Description
Reference will now be made in detail to embodiments of the present application, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are exemplary and intended to be used for explaining the present application and should not be construed as limiting the present application.
The semiconductor product processing machine and the processing method according to the embodiment of the present application are described below with reference to the drawings. To the problem that the precision, the yields and the production efficiency of semiconductor products are lower due to the fact that the semiconductor products are manually processed and the spindle deviation is adjusted in the related technology mentioned in the background technology center, the application provides a semiconductor product processing machine, in the processing machine, the semiconductor products can be accurately processed by means of image recognition, positioning and high-precision sensors, the direction of a machine table spindle can be fully automatically adjusted, full-automatic processing of the semiconductor products and automatic full-automatic adjustment of the spindle deviation are achieved, the precision and the yields of semiconductor product processing can be effectively improved, and the production efficiency of the semiconductor products is improved. Therefore, the technical problems that precision, yield and production efficiency of semiconductor products are low and the like caused by manual processing of the semiconductor products and adjustment of spindle deviation in the related technology are solved.
Specifically, fig. 1 is a block diagram of a semiconductor product processing machine according to an embodiment of the present disclosure.
As shown in fig. 1, the semiconductor product processing machine 10 includes: the image recognition device 100, the correlation sensor 200 and the fully automatic teaching machine 300.
The image recognition device 100 is used for acquiring a current image of a processed workpiece; the correlation sensor 200 is used for detecting the actual coordinate of the position of the tool tip; the full-automatic tuning machine 300 is used for generating a target processing action based on a preset zero coordinate, raising the position of a spindle, controlling a processed workpiece to execute the target processing action, and re-tuning the position of the processed workpiece to a position corresponding to the zero coordinate based on a current image and/or an actual coordinate after the processing of a semiconductor product is completed.
The preset zero coordinates can be specifically calibrated or set according to the requirements of semiconductor product processing, and are not specifically limited. The image recognition apparatus 100 may employ an industrial camera in order to precisely lock the zero coordinates of the workpiece being machined.
In this embodiment, the fully automatic teaching machine 300 is specifically configured to calculate a first debugging offset of the X axis and the Y axis according to the current image, generate a first coordinate teaching value based on the first debugging offset and the zero coordinate, and/or calculate a second debugging offset of the Z axis according to the actual coordinate, and generate a second coordinate teaching value based on the second debugging offset and the zero coordinate.
It can be understood that this application embodiment can utilize image recognition and location and the accurate processing semiconductor product of high accuracy sensor, and full-automatic tuning and teaching board main shaft X Y Z direction realizes full-automatic tuning and teaching board X axle and Y axle debugging deviation.
Specifically, the spindle of the fully automatic teaching machine 300 is detected by using the correlation sensor 200, the processing precision can reach 5um, the tip of the tool is sensed under the micron precision, and the coordinate is stored to the Z coordinate of the specified variable. After different cutters are replaced, the coordinates of the workpiece to be machined of the product are taught in a full-automatic mode, and the problems that the efficiency and the precision are low and the like caused by manual re-debugging of the zero coordinates of the product are solved.
Can use the industry camera when full-automatic debugging board 300's X axle and Y axle debugging deviation to accurately lock work piece zero position coordinate. After the product is replaced, the full-automatic tuning machine 300 can fully automatically tune the coordinates of the workpiece to be machined of the product, and the problems that the efficiency and the precision are low and the like caused by the deviation of the X axis and the Y axis of the zero position coordinate of the product are manually debugged again are solved.
In practical applications, the embodiment of the present application may automatically calculate the coordinate deviation amount through a program shown in fig. 2, and specifically, the fully automatic tuning machine 300 may apply the program shown in fig. 2, and automatically calculate and tune the deviation generated by a new tool or a new sample according to the zero coordinate and the deviation coordinate stored inside. The full-automatic teaching machine 300 inevitably generates coordinate deviation when the nth product starts to be generated, and can restore the corresponding coordinate by inputting the deviation amount according to the program shown in fig. 3, and then continue to work, so as to improve the processing precision and yield and the processing efficiency of the semiconductor product.
In some embodiments, further comprising: and (6) an interactive interface. The interactive interface is provided with a display area and a plurality of function keys, the display area displays the current parameters and the current working mode of the semiconductor product processing machine, and the function keys comprise on-off function keys.
It can be understood that the interactive interface is a humanized user application software interface designed in the embodiment of the application, and the interactive interface can enable an operator to conveniently use keys, simplify the complexity of the original interface and screen appropriate and common functions; therefore, the targeted software user interface designed by the embodiment of the application can conveniently use related keys, and the production efficiency is indirectly improved.
In some embodiments, further comprising: and a controller. The controller is used for controlling the full-automatic tuning and teaching machine to enter a working mode corresponding to the gesture action according to the gesture action input by the user after judging that the startup and shutdown function key is triggered.
The operation mode may include a manual operation mode, an automatic operation mode, and the like.
It can be understood that the gesture action is in contact with or not in contact with the interactive interface to conveniently select to enter the corresponding working mode, so that operators at different posts can enter the function of operation specificity under the option distribution of the homepage, the operation experience is improved, and the production efficiency is indirectly improved.
The processing flow of the semiconductor product processing machine will be described with reference to fig. 4, specifically as follows:
step 1: after the startup and shutdown function key is triggered, selecting a manual operation mode, setting a zero coordinate, loading a G code after setting, and lifting the position of a main shaft;
step 2: detecting whether the sample disc or the drill bit is replaced or not after the processing and production of the semiconductor product are finished, and entering a step 3 if the sample disc or the drill bit is detected to be replaced; if bit replacement is detected, go to step 4;
and step 3: after the product is replaced, automatically teaching the X axis and the Y axis of the full-automatic teaching machine table to automatically teach the coordinates of the processed workpiece of the product;
and 4, step 4: after different cutters are replaced, automatic training of the Z axis of the full-automatic training machine table is carried out, and the coordinates of the processed workpiece of the product are trained in a full-automatic mode.
According to the semiconductor product processing machine provided by the embodiment of the application, the processed semiconductor product can be accurately processed by utilizing image recognition, positioning and a high-precision sensor, the direction of the main shaft of the machine table can be fully automatically taught, full-automatic processing of the semiconductor product and automatic full-automatic adjustment of the deviation of the main shaft are realized, the processing precision and yield of the semiconductor product can be effectively improved, and the production efficiency of the semiconductor product is improved. .
Next, a method of processing a semiconductor product according to an embodiment of the present application will be described with reference to the drawings.
Fig. 5 is a flowchart of a semiconductor product processing method according to an embodiment of the present application.
As shown in fig. 5, the semiconductor product processing method applied to the semiconductor product processing machine of the above embodiment includes the steps of:
in step S101, a current image of the processing workpiece acquired by the image recognition device is acquired;
in step S102, acquiring actual coordinates of a position where the tool tip is located, which is detected by the correlation sensor;
in step S103, a target processing action is generated based on the preset zero coordinates, the spindle position is raised, the processing workpiece is controlled to execute the target processing action, and after the processing of the semiconductor product is completed, the position of the processing workpiece is re-taught to the position corresponding to the zero coordinates based on the current image and/or the actual coordinates.
Further, re-teaching the position of the processing workpiece to the position corresponding to the zero position coordinate based on the current image and the actual coordinate comprises: calculating a first debugging deviation of an X axis and a Y axis according to the current image, and generating a first coordinate training value based on the first debugging deviation and the zero position coordinate; and/or calculating a second debugging deviation of the Z axis according to the actual coordinate, and generating a second coordinate debugging value based on the second debugging deviation and the zero position coordinate.
Further, still include: and displaying the current parameters and the current working mode of the semiconductor product processing machine through the interactive interface.
Further, still include: and after the controller judges that the startup and shutdown function key is triggered, entering a corresponding working mode according to the gesture action input by the user.
Further, the gesture motion is in contact with or not in contact with the interactive interface.
It should be noted that the above explanation of the embodiment of the semiconductor product processing machine is also applicable to the semiconductor product processing method of the embodiment, and is not repeated herein.
According to the semiconductor product processing method provided by the embodiment of the application, the semiconductor product can be accurately processed by utilizing image recognition and positioning and a high-precision sensor, the direction of the main shaft of the machine table can be fully automatically taught, full-automatic processing of the semiconductor product and automatic full-automatic adjustment of the deviation of the main shaft are realized, the processing precision and yield of the semiconductor product can be effectively improved, and the production efficiency of the semiconductor product is improved.
In the description herein, reference to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or N embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present application, "N" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more N executable instructions for implementing steps of a custom logic function or process, and alternate implementations are included within the scope of the preferred embodiment of the present application in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of implementing the embodiments of the present application.
It should be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. If implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.
Claims (10)
1. A semiconductor product processing machine, comprising:
the image recognition device is used for acquiring a current image of the processed workpiece;
the correlation sensor is used for detecting the actual coordinate of the position of the tip of the cutter; and
the full-automatic tuning and teaching machine is used for generating a target processing action based on a preset zero coordinate, raising the position of a spindle, controlling the processing workpiece to execute the target processing action, and re-tuning the position of the processing workpiece to a position corresponding to the zero coordinate based on the current image and/or the actual coordinate after the processing of a semiconductor product is completed.
2. The semiconductor product processing machine of claim 1, wherein the fully automatic teach station is specifically configured to calculate a first debug offset for an X-axis and a Y-axis from the current image, generate a first coordinate teach value based on the first debug offset and the zero coordinate, and/or calculate a second debug offset for a Z-axis from the actual coordinate, and generate a second coordinate teach value based on the second debug offset and the zero coordinate.
3. The semiconductor product processing machine of claim 1, further comprising:
the system comprises an interactive interface and a control unit, wherein the interactive interface is provided with a display area and a plurality of function keys, the display area displays the current parameters and the current working mode of the semiconductor product processing machine, and the function keys comprise on-off function keys.
4. The semiconductor product processing machine of claim 3, further comprising:
and the controller is used for controlling the full-automatic teaching machine to enter a working mode corresponding to the gesture action according to the gesture action input by the user after judging that the power-on and power-off function key is triggered.
5. The semiconductor product handler of claim 4, wherein the gestural action is in contact with or not in contact with the interactive interface.
6. A semiconductor product processing method applied to the semiconductor product processing machine according to any one of claims 1 to 5, comprising the steps of:
acquiring a current image of a processing workpiece acquired by an image recognition device;
acquiring actual coordinates of the position of the tool tip detected by the correlation sensor;
generating a target processing action based on a preset zero coordinate, raising the position of a spindle, controlling the processing workpiece to execute the target processing action, and re-teaching the position of the processing workpiece to a position corresponding to the zero coordinate based on the current image and/or the actual coordinate after the processing of the semiconductor product is completed.
7. The method of claim 6, wherein re-teaching the position of the machined workpiece to a position corresponding to the zero position coordinate based on the current image and the actual coordinates comprises:
calculating a first debugging deviation of an X axis and a Y axis according to the current image, and generating a first coordinate debugging value based on the first debugging deviation and the zero position coordinate; and/or
And calculating a second debugging deviation of the Z axis according to the actual coordinate, and generating a second coordinate training value based on the second debugging deviation and the zero position coordinate.
8. The method of claim 6, further comprising:
and displaying the current parameters and the current working mode of the semiconductor product processing machine through an interactive interface.
9. The method of claim 6, further comprising:
and after judging that the startup and shutdown function key is triggered through the controller, entering a corresponding working mode according to the gesture action input by the user.
10. The method of claim 9, wherein the gesture motion is in contact with or non-contact with the interactive interface.
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