A method and system for automatic learning of driver latched wafer position

Abstract

The application discloses an automatic learning method and system for driver latching wafer position, and relates to the field of wafer position. The method specifically discloses that normal state wafers are placed on the first layer and any selected multiple layers of a wafer box; wafer trigger signals of each layer of the wafer box are triggered through up-down reciprocating movement induction; the wafer trigger signals of each layer are taken as probe signals and are latched through a driver; the wafer trigger signals of each layer are regularly read; the wafer position of each layer is calculated according to the wafer trigger signals of the first layer; an up-down offset is applied to the wafer position of each layer as a normal wafer scanning interval of each layer; according to the wafer trigger signals of each layer, wafer thicknesses of corresponding layers of the wafer box are calculated, and the maximum wafer thickness and the minimum wafer thickness are obtained through comparison; the maximum wafer thickness to the minimum wafer thickness is taken as a normal wafer thickness interval; and the application can realize an automatic learning process of Mapping application.

Description

Technical Field

[0001] This invention relates to the field of wafer positioning, and more specifically to an automatic learning method and system for driver-latched wafer positioning. Background Technology

[0002] One function of wafer handling robots is to scan the wafer status of each layer in the wafer cassette. The CPU internally records the Z-axis position based on input signals from external sensors, thus enabling the robot to scan the wafers. Generally, there are four wafer states per layer: normal wafer, empty wafer, stacked wafer, and tilted wafer. The method for determining the state involves recording the Z-axis driver position when the sensor is OFF and when it is ON, based on the sensor's on / off signals during the robot's up-and-down movement. By comparing these two positions, the thickness of the wafer layer is determined, thus indicating the actual wafer status. Traditional mapping applications require personnel to input a series of numerical conditions, such as the minimum and maximum wafer thickness and interlayer spacing, to determine the wafer status within the cassette. This requires personnel with strong technical experience. Therefore, there is a need for an automatic learning method and system for driver-latched wafer positions, incorporating an automatic learning process for mapping to identify the necessary conditions in the algorithm. Summary of the Invention

[0003] The technical problem to be solved by this invention is that traditional mapping applications require relevant personnel to input a series of numerical conditions such as the minimum wafer thickness, maximum wafer thickness, and interlayer spacing of the scanned wafer in order to determine the state of the wafer in the wafer cassette. The purpose is to provide an automatic learning method and system for driver latching wafer position, so that it no longer requires input conditions, and the automatic learning process of mapping is added to identify the conditions required in the algorithm, thus solving the above-mentioned technical problem.

[0004] This invention is achieved through the following technical solution:

[0005] An automatic learning method for latching wafer positions by a driver includes: placing wafers in normal state on the first layer and arbitrarily selected multiple layers of a wafer cassette; sensing wafer trigger signals of each layer of the wafer cassette by reciprocating up and down movement; latching the wafer trigger signals of each layer as probe signals by a driver; periodically reading the wafer trigger signals of each layer; calculating the wafer position of each layer based on the read wafer trigger signals of the first layer; applying an up and down offset to the wafer position of each layer as the normal wafer scan interval for each layer; calculating the wafer thickness of the corresponding layer of the wafer cassette based on the wafer trigger signals of each layer, and obtaining the maximum wafer thickness and the minimum wafer thickness by comparison; and defining the range from the maximum wafer thickness to the minimum wafer thickness as the normal wafer thickness interval.

[0006] The above-mentioned sensing of the wafer trigger signal of each layer of the wafer cassette by reciprocating up and down specifically includes: when the robotic arm moves at a constant speed in the vertical direction of the wafer cassette, the sensors installed on the robotic arm sense the ON signal generated by the wafer trigger or the OFF signal generated when there is no wafer trigger in each layer.

[0007] The wafer trigger signals of each layer are latched as probe signals by the driver. Specifically, the driver latches the ON and OFF signals of each layer as probe signals to the position of the Z-axis motor encoder. The periodic reading of the wafer trigger signals of each layer specifically includes the CPU periodically reading a series of ON and OFF signals latched by the driver via the EtherCAT bus.

[0008] The above calculation of the wafer thickness of the corresponding layer of the wafer cassette based on the wafer trigger signal of each layer specifically includes: calculating the wafer thickness of the corresponding layer based on the time of each ON signal latched by the driver and the moving speed of the sensor.

[0009] The aforementioned automatic learning method for latching wafer positions by a driver further includes: acquiring the position of a wafer in an unknown state within a wafer cassette by reciprocating up and down using a reflective sensor; determining whether the wafer position in the unknown state is within the normal wafer scanning range of each layer; determining that the wafer is a normal wafer when it is within the normal wafer scanning range; simultaneously determining whether the wafer thickness is within the normal wafer thickness range, and determining that the wafer is a normal wafer when it is within the range; determining that the wafer is a stacked wafer when it is not within the range; and determining that the wafer is a cross-layer wafer when it is not within the normal wafer scanning range.

[0010] The above-mentioned method of obtaining the unknown wafer position in the wafer cassette by reciprocating up and down using a reflective sensor specifically includes: when the robotic arm moves at a constant speed in the vertical direction of the wafer cassette, the reflective sensor installed on the robotic arm senses the ON signal generated when triggered by the wafer, or the OFF signal generated when there is no wafer trigger, for each layer.

[0011] The above-mentioned method of obtaining the wafer position of an unknown state within the wafer cassette by reciprocating up and down using a reflective sensor also includes: the driver latching the ON and OFF signals of each layer as probe signals to the position of the Z-axis motor encoder; and the CPU periodically reading a series of ON and OFF signals latched by the driver via the EtherCAT bus.

[0012] An automatic learning system for latching wafer positions by a driver includes: a wafer placement module: placing wafers in normal state on the first layer and arbitrarily selected multiple layers of a wafer cassette; a probe signal module: sensing wafer trigger signals of each layer of the wafer cassette by reciprocating up and down; the wafer trigger signals of each layer are latched by a driver as probe signals; a wafer scanning module: periodically reading the wafer trigger signals of each layer; calculating the wafer position of each layer based on the read wafer trigger signals of the first layer; applying an up and down offset to the wafer position of each layer as the normal wafer scanning range for each layer; and a wafer thickness comparison module: calculating the wafer thickness of the corresponding layer of the wafer cassette based on the wafer trigger signals of each layer, and obtaining the maximum and minimum wafer thicknesses by comparison; the maximum wafer thickness to the minimum wafer thickness is defined as the normal wafer thickness range.

[0013] An electronic device includes a memory, a processor, and a computer program running on the processor, wherein the processor executes the computer program to implement the steps of an automatic learning method for latching wafer positions as described above.

[0014] A computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the automatic learning method for latching wafer positions as described above.

[0015] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0016] This invention provides an automatic learning method for latching wafer positions using a driver. Wafers in normal condition are placed on the first layer and arbitrarily selected multiple layers of a wafer cassette. The method uses a reciprocating motion sensor to detect the wafer trigger signals of each layer, which are then latched by a driver as probe signals. The method periodically reads the wafer trigger signals of each layer. Based on the read wafer trigger signals of the first layer, the wafer position of each layer is calculated. A normal wafer scanning range for determining the normal position of each layer is obtained based on the wafer position of each layer. Based on the wafer trigger signals of each layer, the wafer thickness of the corresponding layer in the wafer cassette is calculated. By comparing the maximum and minimum wafer thicknesses, a normal wafer thickness range for determining the normal state of the wafer is obtained. This invention eliminates the need for input conditions, incorporating an automatic learning process in mapping to identify the necessary conditions required by the algorithm. It solves the problem in traditional mapping applications where personnel need to input a series of numerical conditions such as the minimum and maximum wafer thicknesses and interlayer spacing to determine the state of the wafers in the wafer cassette, requiring personnel with strong technical experience. Using the high-speed probe function of the servo driver, the input signal of the external sensor is used as the probe signal. The position of the Z-axis motor encoder is latched at the moment the signal is triggered. Then, the CPU and the driver communicate via EtherCAT at a fixed cycle to read the information latched to the Z-axis encoder. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly described below. It should be understood that the following drawings only show some embodiments of the present invention and should not be considered as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort. In the drawings:

[0018] Figure 1 This is a flowchart of an automatic learning method for driver latching wafer position according to an embodiment of this application;

[0019] Figure 2 This is a schematic diagram of existing technology;

[0020] Figure 3 This is a schematic diagram of the automatic learning method for driver latching wafer position according to an embodiment of this application. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the embodiments and accompanying drawings. The illustrative embodiments and descriptions of the present invention are only used to explain the present invention and are not intended to limit the present invention.

[0022] Example

[0023] like Figure 1 As shown, this application provides an automatic learning method for latching wafer positions using a driver, comprising: placing wafers in normal state on the first layer and arbitrarily selected multiple layers of a wafer cassette; sensing wafer trigger signals of each layer of the wafer cassette by reciprocating up and down movement; latching the wafer trigger signals of each layer as probe signals using a driver; periodically reading the wafer trigger signals of each layer; calculating the wafer position of each layer based on the read wafer trigger signals of the first layer; applying an up and down offset to the wafer position of each layer as the normal wafer scanning interval for each layer; calculating the wafer thickness of the corresponding layer of the wafer cassette based on the wafer trigger signals of each layer, and obtaining the maximum wafer thickness and the minimum wafer thickness by comparison; and using the maximum wafer thickness to the minimum wafer thickness as the normal wafer thickness interval.

[0024] The above-mentioned sensing of the wafer trigger signal of each layer of the wafer cassette by reciprocating up and down specifically includes: when the robotic arm moves at a constant speed in the vertical direction of the wafer cassette, the sensors installed on the robotic arm sense the ON signal generated by the wafer trigger or the OFF signal generated when there is no wafer trigger in each layer.

[0025] The wafer trigger signals of each layer are latched as probe signals by the driver. Specifically, the driver latches the ON and OFF signals of each layer as probe signals to the position of the Z-axis motor encoder. The periodic reading of the wafer trigger signals of each layer specifically includes the CPU periodically reading a series of ON and OFF signals latched by the driver via the EtherCAT bus.

[0026] The above calculation of the wafer thickness of the corresponding layer of the wafer cassette based on the wafer trigger signal of each layer specifically includes: calculating the wafer thickness of the corresponding layer based on the time of each ON signal latched by the driver and the moving speed of the sensor.

[0027] The aforementioned automatic learning method for latching wafer positions by a driver further includes: acquiring the position of a wafer in an unknown state within a wafer cassette by reciprocating up and down using a reflective sensor; determining whether the wafer position in the unknown state is within the normal wafer scanning range of each layer; determining that the wafer is a normal wafer when it is within the normal wafer scanning range; simultaneously determining whether the wafer thickness is within the normal wafer thickness range, and determining that the wafer is a normal wafer when it is within the range; determining that the wafer is a stacked wafer when it is not within the range; and determining that the wafer is a cross-layer wafer when it is not within the normal wafer scanning range.

[0028] The above-mentioned method of obtaining the unknown wafer position in the wafer cassette by reciprocating up and down using a reflective sensor specifically includes: when the robotic arm moves at a constant speed in the vertical direction of the wafer cassette, the reflective sensor installed on the robotic arm senses the ON signal generated when triggered by the wafer, or the OFF signal generated when there is no wafer trigger, for each layer.

[0029] The above-mentioned method of obtaining the wafer position of an unknown state within the wafer cassette by reciprocating up and down using a reflective sensor also includes: the driver latching the ON and OFF signals of each layer as probe signals to the position of the Z-axis motor encoder; and the CPU periodically reading a series of ON and OFF signals latched by the driver via the EtherCAT bus.

[0030] The automatic learning process of TeachMapping is as follows:

[0031] Step 1 Placement Process: First, place several wafers in normal condition in the wafer box. The position of the wafers in the wafer box is arbitrarily selected, ensuring that there are wafers in the first layer of the wafer box.

[0032] Step 2 Movement Process: The robotic arm performs vertical movement. During the operation, the sensors installed on the robotic arm will sense the position of the wafer in the wafer box in real time, thereby generating a series of ON and OFF signals. This signal is sent to the driver as a probe signal, and the driver latches the position when the signal is triggered.

[0033] Step 3 Calculation Process: The CPU periodically reads the position information latched into the driver via the EtherCAT bus. Based on the position of the first layer wafer, it calculates the position of each layer in the wafer cassette. Based on a series of ON and OFF signals, it calculates the maximum and minimum wafer thickness placed in the wafer cassette at this time.

[0034] During the TeachMapping process, the robotic arm calculates the wafer thickness of the placed wafer in real time using existing algorithms, compares these wafer thicknesses, and automatically generates the minimum and maximum wafer thicknesses during the movement.

[0035] The mapping process is as follows:

[0036] Step 1 Placement Process: Place wafers in any state in the wafer box.

[0037] Step 2 Movement Process: The robotic arm performs vertical movement. During the operation, the sensors installed on the robotic arm will sense the position of the wafer in the wafer box in real time, thereby generating a series of ON and OFF signals. This signal is sent to the driver as a probe signal, and the driver latches the position when the signal is triggered.

[0038] Step 3 Calculation Process: The CPU periodically reads the position information latched into the driver via the EtherCAT bus. Based on the position of each wafer layer generated during the TeachMapping process, it adds upper and lower offset values ​​as the scanning interval. If a sensor is triggered within this scanning interval, it determines whether there is a wafer in each layer of the current wafer cassette. Based on the minimum and maximum wafer thickness generated during the TeachMapping process, it determines the wafer placement status of the wafer layers in the current wafer cassette.

[0039] The initial circuit structure of the prior art is as follows: Figure 2 As shown, when the sensor signal is connected to the remote I / O module as a normal input signal, the CPU needs at least two scan cycles to obtain the driver position when the sensor signal is triggered. At this point, the read position is significantly different from the position when the sensor signal is triggered. The schematic diagram of the latch circuit structure in this application is shown below. Figure 3 As shown in the improved scheme, when an external sensor signal is triggered, it is first sent to the driver as a high-speed probe signal. The driver records the exact position at the time of triggering. The CPU then reads the latched record position and uses it as the sensor trigger position in the program, which is more accurate.

[0040] Currently, the sensors used in robotic mapping are divided into through-beam sensors and reflective sensors. When using through-beam sensors, determining the wafer placement status by scanning and calculating the wafer thickness is not problematic. For multi-layer wafers, the wafer thickness scanned using this method is significant enough to distinguish it from stacked wafers. However, when using reflective sensors, the scanned multi-layer wafer thickness is almost identical to the single-layer wafer thickness, making it impossible to distinguish between multi-layer wafers and normal wafers. Therefore, when using reflective sensors to identify multi-layer wafers, first determine whether the sensor trigger position is within the normal wafer scanning range, and then determine the wafer thickness. If the sensor trigger position is not within the normal wafer scanning range, and the wafer thickness is normal, then this wafer is considered a multi-layer wafer.

[0041] In summary, this application provides an automatic learning method and system for latching wafer positions using a driver: wafers in normal condition are placed on the first layer and arbitrarily selected multiple layers of a wafer cassette; the wafer trigger signal of each layer of the wafer cassette is sensed by a reciprocating motion sensor and latched by a driver as a probe signal; the wafer trigger signal of each layer is read periodically; the wafer position of each layer is calculated based on the read wafer trigger signal of the first layer; a normal wafer scanning interval for determining the normal position of each layer is obtained based on the wafer position of each layer; the wafer thickness of the corresponding layer in the wafer cassette is calculated based on the wafer trigger signal of each layer, and the maximum and minimum wafer thicknesses are obtained by comparison, resulting in a normal wafer thickness interval for determining the normal state of the wafer. This invention eliminates the need for input conditions, incorporating an automatic learning process in mapping to identify the necessary conditions required in the algorithm. It solves the problem in traditional mapping applications where personnel need to input a series of numerical conditions such as the minimum and maximum wafer thicknesses and interlayer spacing to determine the state of the wafers in the wafer cassette, requiring personnel with strong technical experience. Using the high-speed probe function of the servo driver, the input signal of the external sensor is used as the probe signal. The position of the Z-axis motor encoder is latched at the moment the signal is triggered. Then, the CPU and the driver communicate via EtherCAT at a fixed cycle to read the information latched to the Z-axis encoder.

[0042] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. An automatic learning method for latching wafer positions by a driver, characterized in that, include: Wafers in normal condition are placed in the first layer of the wafer box and in arbitrarily selected multiple layers. The wafer trigger signal of each layer of the wafer cassette is sensed by reciprocating up and down. Specifically, this includes: when the robotic arm moves at a constant speed in the vertical direction of the wafer cassette, the sensor installed on the robotic arm senses the ON signal generated when the wafer is triggered, or the OFF signal generated when there is no wafer trigger. The wafer trigger signal of each layer is latched as a probe signal by the driver. Specifically, the driver latches the ON signal and the OFF signal of each layer as probe signals to the position of the Z-axis motor encoder. The process of periodically reading the wafer trigger signal of each layer specifically includes: the CPU periodically reading a series of ON and OFF signals latched by the driver via the EtherCAT bus; calculating the wafer position of each layer based on the read wafer trigger signal of the first layer, and calculating the vertical offset of the wafer in each layer; and applying the vertical offset to the wafer position of each layer as the normal wafer scan interval for each layer. Based on the wafer trigger signal of each layer, the wafer thickness of the corresponding layer of the wafer cassette is calculated. Specifically, this includes: calculating the wafer thickness of the corresponding layer based on the time of each ON signal latched by the driver and the moving speed of the sensor; obtaining the maximum wafer thickness and the minimum wafer thickness by comparison; and using the maximum wafer thickness to the minimum wafer thickness as the normal wafer thickness range.

2. The automatic learning method for latching wafer positions by a driver according to claim 1, characterized in that, Also includes: The position of the wafer in an unknown state within the wafer cassette is obtained by reciprocating up and down using a reflective sensor; Determine whether the position of the wafer in an unknown state is within the normal wafer scan range of each layer; When the wafer is within the normal wafer scanning range, it is determined that the wafer is a normal wafer; at the same time, it is determined whether the wafer thickness is within the normal wafer thickness range. If it is, the wafer is determined to be a normal wafer; if it is not, the wafer is determined to be a stacked wafer. If the wafer is not within the normal wafer scanning range, it is determined to be a cross-layer wafer.

3. The automatic learning method for driver latching wafer position according to claim 2, characterized in that, The method of obtaining the unknown wafer position within the wafer cassette by reciprocating up and down using a reflective sensor specifically includes: when the robotic arm moves at a constant speed in the vertical direction of the wafer cassette, the reflective sensor installed on the robotic arm senses the ON signal generated when triggered by a wafer, or the OFF signal generated when there is no wafer trigger, for each layer.

4. The automatic learning method for latching wafer positions by a driver according to claim 3, characterized in that, The method of obtaining the wafer position of an unknown state within the wafer cassette by reciprocating up and down using a reflective sensor further includes: the driver latching the ON and OFF signals of each layer as probe signals to the position of the Z-axis motor encoder; and the CPU periodically reading a series of ON and OFF signals latched by the driver via the EtherCAT bus.

5. An automatic learning system for latching wafer positions by a driver, characterized in that, include: Wafer placement module: Wafers in normal condition are placed on the first layer of the wafer box and on any selected multilayer layers respectively; Probe signal module: This module senses the wafer trigger signals of each layer of the wafer cassette by reciprocating up and down. Specifically, it involves the robotic arm reciprocating at a constant speed in the vertical direction of the wafer cassette, and sensors mounted on the robotic arm sensing the ON signal generated when the wafer is triggered, or the OFF signal generated when there is no wafer trigger, for each layer. The wafer trigger signals of each layer are latched as probe signals by a driver. Specifically, the driver latches the ON and OFF signals of each layer as probe signals to the position of the Z-axis motor encoder. Wafer scanning module: Periodically reads the wafer trigger signal of each layer, specifically including: the CPU periodically reads a series of ON and OFF signals latched by the driver through the EtherCAT bus; calculates the wafer position of each layer based on the read wafer trigger signal of the first layer, and counts the vertical offset of the wafer of each layer; applies the vertical offset to the wafer position of each layer as the normal wafer scanning interval of each layer; Wafer thickness comparison module: Based on the wafer trigger signal of each layer, calculate the wafer thickness of the corresponding layer of the wafer cassette. Specifically, this includes: calculating the wafer thickness of the corresponding layer based on the time of each ON signal latched by the driver and the moving speed of the sensor; obtaining the maximum wafer thickness and the minimum wafer thickness through comparison; the maximum wafer thickness to the minimum wafer thickness is taken as the normal wafer thickness range.

6. An electronic device comprising a memory, a processor, and a computer program running on the processor, characterized in that: When the processor executes the computer program, it implements the steps of the automatic learning method for driver latching wafer position as described in any one of claims 1 to 4.

7. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by the processor, it implements the steps of the automatic learning method for driver latching wafer position as described in any one of claims 1 to 4.

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