JP2004356510A - Device and method of signal processing - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a device and a method for correctly extracting and summarizing signal data which show states of a semiconductor manufacturing device through a most appropriate filtering and making it available in a semiconductor manufacturing step. <P>SOLUTION: Signal data in each manufacturing step of the semiconductor manufacturing device 20 are obtained from a plurality of sensors 30-1, 30-2, to 30-m by a sensor information obtaining part 11. A filtering part 12 filters at least either of signal data immediately after a switching of the manufacturing step or signal data immediately before a switching to the next manufacturing step obtained out of each manufacturing step. Further the summarizing part 13 summarizes the filtered signal data. <P>COPYRIGHT: (C)2005,JPO&NCIPI

Description

[0001]
TECHNICAL FIELD OF THE INVENTION
The present invention relates to a signal processing device and a signal processing method, and more particularly to a signal processing device and a signal processing method for processing signal data from a plurality of sensors for detecting a device state of a semiconductor manufacturing device.
[0002]
[Prior art]
2. Description of the Related Art In recent years, in a semiconductor device manufacturing process, a MES (Manufacturing Execution System) for managing manufacturing, a CC (Cell Controller) system for online automation of a device, and an APC ( Various systems using computers have been used, such as an advanced process control (YMS) system, a yield management system (YMS) that manages the yield, and an EES (equipment engineering system) that manages the state of a semiconductor manufacturing apparatus.
[0003]
An FDC (Fault Detection and Classification) system is one of them.
The FDC system obtains real-time signal data from a plurality of sensors that detect the device state (pressure, temperature, flow rate, voltage, etc.) of the semiconductor manufacturing device during wafer processing, and detects a process failure.
[0004]
However, in such an FDC system, data from a large number of sensors is acquired in real time, so that the data capacity becomes extremely large. Therefore, when the signal data obtained by the FDC system is used in another system as described above, the signal data is converted into a maximum value, a minimum value, an average value, and a standard deviation for each manufacturing step such as a wafer unit or a process recipe step. It was necessary to summarize (hereinafter called "summary") data and pass it.
[0005]
However, in this case, there was a problem in the reliability of data at the time of summarization.
Although processing by a semiconductor manufacturing apparatus is usually performed using a plurality of manufacturing steps, an overshoot may occur when the manufacturing steps are switched.
[0006]
Further, when the manufacturing steps are switched, the manufacturing apparatus switches the processing state or sends event information to a host computer, so that the load on the CPU (Central Processing Unit) of the manufacturing apparatus increases. Therefore, there is a case where there is no response to a data request from the FDC system or a case where a timing delay occurs, and there is a case where data is lost or a data acquisition interval is shifted.
[0007]
As described above, data at the time of switching between manufacturing steps may be unstable and lacks reliability.
Conventionally, if there is a filtering function that filters the data immediately after the switching of the manufacturing step, or if there is a transient change when the processing state is switched, all the signals sampled at that time are invalidated and the analysis data due to the transient change There is a technique for preventing the disturbance of the image (see Patent Document 1).
[0008]
[Patent Document 1]
JP-A-8-25447 (paragraph numbers [0030] to [0031])
[0009]
[Problems to be solved by the invention]
However, in the above-described related art, there are many cases where only filtering can be performed only on the start portion of the manufacturing step, or only one of the number of samples and time can be performed. Further, when it is determined that the signal is in the transient state, all the signals sampled are simply invalidated. That is, meaningful data indicating the state of the apparatus cannot be accurately selected and extracted. For this reason, conventionally, there is a problem in that the data subjected to the filtering process does not always accurately represent the state of the apparatus, and therefore, the correlation with the processing result or the like cannot be obtained in many cases.
[0010]
The present invention has been made in view of such a point, and a signal processing apparatus and a signal processing method for accurately extracting and summarizing signal data indicating a device state and making it available in various systems in a semiconductor manufacturing process. The purpose is to provide.
[0011]
[Means for Solving the Problems]
According to the present invention, in order to solve the above-described problems, in a signal processing apparatus for processing signal data from a plurality of sensors for detecting an apparatus state of a semiconductor manufacturing apparatus, as shown in FIG. A sensor information acquisition unit 11 for acquiring the signal data at predetermined time intervals, and among the signal data in each manufacturing step, the signal data immediately after the switching of the manufacturing step and the signal data immediately before the switching to the next manufacturing step There is provided a signal processing device 10 having a filtering unit 12 for filtering at least one of them and a summarizing unit 13 for summarizing the filtered signal data.
[0012]
According to the above configuration, the sensor information acquiring unit 11 acquires signal data of each manufacturing step in the semiconductor manufacturing apparatus 20 from the plurality of sensors 30-1, 30-2, ..., 30-m. The filtering unit 12 filters at least one of the signal data immediately after the switching of the manufacturing step and the signal data immediately before the switching to the next manufacturing step among the acquired signal data of the respective manufacturing steps. Further, the summarizing section 13 summarizes the filtered signal data.
[0013]
BEST MODE FOR CARRYING OUT THE INVENTION
Hereinafter, embodiments of the present invention will be described with reference to the drawings.
FIG. 1 is a principle configuration diagram showing the principle of a signal processing device according to an embodiment of the present invention.
[0014]
The signal processing device 10 includes a sensor information acquisition unit 11, a filtering unit 12, a summarization unit 13, and a multivariate analysis unit 14.
.., 30-m for detecting the device state (pressure, temperature, flow rate, voltage, etc.) of the semiconductor manufacturing device 20, the signal of each manufacturing step. Data is acquired at predetermined time intervals.
[0015]
The filtering unit 12 filters at least one of the signal data immediately after the switching of the manufacturing step and the signal data immediately before the switching to the next manufacturing step among the acquired signal data in each manufacturing step. At this time, a filtering range is selected for a predetermined time or a predetermined number of samples.
[0016]
The summarizing unit 13 summarizes the signal data filtered by the filtering unit 12 into a maximum value, a minimum value, an average value, a standard deviation, and the like.
The multivariate analysis unit 14 performs a multivariate analysis on the filtered signal data of the plurality of sensors 30-1, 30-2,..., 30-m.
[0017]
Hereinafter, the operation of the signal processing device 10 will be described.
When the sensor information obtaining unit 11 obtains the signal data at each manufacturing step in the semiconductor manufacturing apparatus 20 from the plurality of sensors 30-1, 30-2,..., 30-m, the filtering unit 12 , At least one of the signal data immediately after the switching of the manufacturing step and the signal data immediately before the switching to the next manufacturing step is filtered.
[0018]
FIG. 2 is a first example of filtering.
This is an example of filtering in which N samples immediately after the switching of the manufacturing steps (switching from Step 1 to Step 2) and M samples immediately before the switching to the next manufacturing step (Step 3) are cut. As shown in the drawing, a portion excluding N rising edges and M falling edges is extracted from the data of the manufacturing step (Step 2). In this case, the number of samples to be extracted varies due to a shift in sampling time.
[0019]
FIG. 3 is a second example of filtering.
This is an example of filtering in which N samples have been cut immediately after the switching of the manufacturing steps (switching from Step 1 to Step 2). In this case, by setting the number of samples to be extracted to M or the like, the number of samples used for calculating the summary can be kept constant.
[0020]
FIG. 4 is a third example of the filtering.
This is an example of filtering in which data is cut for N seconds immediately after the switching of the manufacturing step (switching from Step 1 to Step 2) and for M seconds immediately before the switching to the next manufacturing step (Step 3). As shown in the drawing, of the data in the manufacturing step, a portion excluding the data for the rising N seconds and the data for the falling M seconds is extracted. By such filtering, the range of data to be cut can be fixed. In this case, the number of samples to be extracted fluctuates due to a difference in sampling time.
[0021]
FIG. 5 is a fourth example of filtering.
This is an example of filtering in which data for N seconds is cut immediately after the switching of the manufacturing steps (switching from Step 1 to Step 2). In this case, by setting the data range to be extracted to data for M seconds or the like, the range of data used for calculating the summary can be fixed.
[0022]
Although illustration is omitted in the above description, filtering for cutting only the part immediately before switching to the next step may be performed.
Such filtering is selected in accordance with the stability of the manufacturing recipe and sampling state.
[0023]
Next, the filtering section 13 summarizes the filtered signal data into a maximum value, a minimum value, an average value, a standard deviation, and the like for each of the sensors 30-1, 30-2,. Become
[0024]
Further, the filtered signal data of the sensors 30-1, 30-2,..., 30-m may be input to the multivariate analysis unit 14 to perform multivariate analysis. By performing the multivariate analysis, the abnormality of the semiconductor manufacturing apparatus 20 can be more comprehensively detected. The result of the multivariate analysis processing is input to the summarizing unit 13 and is similarly summarized in units of manufacturing steps.
[0025]
In this way, by performing a filtering process by selecting a filtering method in accordance with the stability of a manufacturing recipe or a sampling state and summarizing the data, highly reliable and meaningful data can be obtained from an APC system, YMS, EES, or the like. Can be handed over to other systems. As a result, productivity can be improved, such as reduction in process variation and improvement in yield and equipment operation rate.
[0026]
Next, embodiments of the present invention will be specifically described.
Hereinafter, a case where the signal processing device according to the embodiment of the present invention is applied to a manufacturing system that manages the manufacturing of a semiconductor device will be described.
[0027]
FIG. 6 is a schematic configuration diagram of the manufacturing system.
As shown in the figure, the manufacturing system includes a plurality of systems such as an MES 100, a C / C (Cell Controller) system 110, an APC system 120, a YMS 130, and an EES 140, which are arranged on a LAN (Local Area Network).
[0028]
MES100 is a manufacturing management system that manages and analyzes all the processes, equipment, conditions, and work data of each product flowing on the production line with a computer, and is more efficient in improving quality, improving yield, and reducing work errors. It is a system that supports efficient production.
[0029]
The C / C system 110 is a device online automation system.
The APC system 120 is a system that performs advanced process control proposed in the SEMATECH guidelines. It has a function of monitoring whether or not the semiconductor manufacturing apparatus 500 has deviated from a good state during wafer processing, and determining processing conditions for the next wafer or lot based on the processing result of the previous wafer or lot.
[0030]
YMS 130 is a yield management system.
The EES 140 monitors the state of the semiconductor manufacturing apparatus 500 and predicts a maintenance time.
[0031]
Although not shown, a TCAD (Technology Computer Aided Design) system for simulating device characteristics and a facility system for managing device states such as temperature, pressure, gas flow rate, and supply voltage are provided on the same LAN. It may be arranged.
[0032]
The signal processing device 10 according to the embodiment of the present invention illustrated in FIG. 1 functions as an FDC controller 200, and includes an FDC server 210 connected via routers 301 and 302, and a data collection device 400 that collects various data. An FDC system is configured.
[0033]
The data collection device 400 includes an input port 401 for inputting signal data from the external sensor unit 600, a LAN port 402 for connecting to a LAN, a semiconductor manufacturing apparatus 500, and a SCS (SEMI (SEMI)). (Semiconductor Equipment and Materials International) There are COM ports 403 and 404 for performing communication using an Equipment Communication Standards (Communications Standards) communication protocol. Signal data from an internal sensor of the semiconductor manufacturing apparatus 500 is input from the COM port 403.
[0034]
Such an FDC system collects signal data from the external sensor unit 600 in real time together with the internal sensor of the semiconductor manufacturing apparatus 500 and performs a multivariate analysis to determine whether the semiconductor manufacturing apparatus 500 has deviated from a good state. Monitor.
[0035]
The semiconductor manufacturing apparatus 500 includes a dry etching apparatus, a stepper, a CVD (Chemical Vapor Deposition) apparatus, a diffusion furnace, a CMP (Chemical Mechanical Polishing) apparatus, a cleaning apparatus, and the like. The C / C system 110 controls the C / C system 110 online through a COM port 501. Is done.
[0036]
FIG. 7 is a hardware configuration example of the FDC controller.
The FDC controller 200 includes a CPU (Central Processing Unit) 201, a ROM (Read Only Memory) 202, a RAM (Random Access Memory) 203, a hard disk 204, a graphic processing unit 205, an input I / F (Interface) 206, and a communication I / F 207. These are connected to each other via a bus 208.
[0037]
Here, the CPU 201 controls each unit according to a program stored in the hard disk 204. Further, various calculations described above are performed.
The ROM 202 stores basic programs and data executed by the CPU 201.
[0038]
The RAM 203 temporarily stores programs being executed by the CPU 201 and data being operated on.
The hard disk 204 stores an OS executed by the CPU 201, an application program for filtering, summarizing, and performing multivariate analysis.
[0039]
A display device 205a such as a display is connected to the graphic processing unit 205, and displays an image on the screen of the display device 205a in accordance with a drawing command from the CPU 201.
[0040]
A mouse 206a and a keyboard 206b are connected to the input I / F 206. For example, the input I / F 206 receives information input by a user of the FDC controller 200 and transmits the information to the CPU 201 via the bus 208.
[0041]
The communication I / F 207 acquires various sensor information via the data collection device 400 in real time.
The processing of the embodiment of the present invention is realized by the hardware configuration as described above.
[0042]
Each system shown in FIG. 6 includes a plurality of computers functioning as a server, a database server, and the like.
Hereinafter, the operation of the FDC system when acquiring signal data from the external sensor unit 600 together with the internal sensor of the semiconductor manufacturing apparatus 500 and transferring it to another system in the manufacturing system as shown in FIG. 6 will be described.
[0043]
The device state of the semiconductor manufacturing apparatus 500 is detected by the internal sensor and the external sensor unit 600, and is input to the communication I / F 207 of the FDC controller 200 at predetermined time intervals (for example, one second intervals) via the data collection device 400. .
[0044]
The input signal data of the various sensors is subjected to signal processing as follows by a program which is taken out and executed from the hard disk 204 under the control of the CPU 201 of the FDC controller 200.
[0045]
First, filtering processing as shown in FIGS. 2 to 5 is performed on input signal data of various sensors in units of manufacturing steps.
At the time of the filtering process, the user of the FDC controller 200 may display the screen on the display device 205a so that a desired filtering range can be set.
[0046]
FIG. 8 is an example of a filtering setting screen.
As illustrated, on the filtering setting screen 700, a manufacturing step in a certain manufacturing process is set in a Step Setting column 701. The Raw Data Count column 702 displays the total number of samples in a step for a plurality of wafers (for example, several lots). Further, whether to perform filtering for a predetermined time or for a predetermined sampling number is designated by selecting either the Sec check box 703a or the Sampling check box 703b. Further, the number of samples (or time range) immediately after the step switching in the Start_t column 704, the number of samples (or time range) to be extracted in the Main_t column 705, and the number of samples (or time range) immediately before the next step switching in the End_t column 706. specify. In the figure, designation is made such that filtering is performed with 12 samples immediately after switching and 5 samples immediately before switching in the next step. When both immediately after switching and immediately before switching to the next step are specified, the Main_t column 705 becomes “0”.
[0047]
FIG. 9 is an example of signal data before being filtered.
In the figure, for a plurality of wafers (for example, several lots) in the same manufacturing step in the same process, signal data from the sensors are superimposed and displayed in a graph.
[0048]
The user looks at this data and sets a part to be cut and a filtering method suitable for the cut on the setting screen as shown in FIG.
FIG. 10 is an example of signal data after filtering.
[0049]
The user confirms by looking at the filtering result as shown in FIG. If necessary, the screen returns to the setting screen of FIG. 8, changes the filtering setting value, and performs filtering again. It should be noted that sampling accuracy can be improved by filtering signal data for either a predetermined time or a predetermined number of samples according to the waveform of the signal.
[0050]
Next, the FDC controller 200 calculates a maximum value, a minimum value, an average value, a standard deviation, and the like of the filtered data. Then, data summarized for each sensor is created for each manufacturing step.
[0051]
Alternatively, multivariate analysis may be performed on the filtered signal data of various sensors, and the results may be summarized. Note that the multivariate analysis includes a k-nearest neighbor method, a Mahalanobis distance, PCA (principal component analysis), a neural network, and other methods.
[0052]
By performing the multivariate analysis, it is possible to accurately diagnose a correlation between many sensors and the like, and it is possible to comprehensively determine a device abnormality and the like.
Next, under the control of the CPU 201, the data is transferred to another system such as the APC system 120. Instead of transferring the summarized data of all the manufacturing steps, only the data of important steps related to the change of the process state may be transferred.
[0053]
Also, the summarized data is registered in the database of the FDC server 210 together with the key information, and the key information is added when the data is delivered.
The key information means information necessary for managing and identifying data, such as a product type, a process, an apparatus, a recipe, a lot, a wafer, a step, and a lot processing start or end time.
[0054]
Since the MES 100 has various databases related to semiconductor manufacturing, all of these key information are managed. On the other hand, since the data collection device 400 of the FDC system exchanges data with only the semiconductor manufacturing device 500, information (device, recipe, lot, wafer, step, lot processing start or end time) managed by the semiconductor manufacturing device is used. ) Can be collected, but information (type, process, etc.) managed only by the MES 100 cannot be directly collected. In order to use the data of the FDC system in another system such as the APC system 120, the FDC system needs to directly link to the database of the MES 100 to obtain the missing information.
[0055]
As a specific linking method, the FDC system makes up for the missing information by searching the database of the MES 100 using the items of key information that can be collected from the semiconductor manufacturing apparatus. For example, using the lot processing start time, the MES 100 searches for information on the lot for which the lot processing was started at that time. Since the MES 100 also manages other various key information together with the lot processing start time information, it is possible to extract key information such as a product type and a process therefrom. When registering data collected by the FDC system in the database of the FDC server 210, these key information items are added.
[0056]
Finally, the above signal processing is summarized in a flowchart.
FIG. 11 is a flowchart illustrating a processing flow of the signal processing method according to the embodiment of the present invention.
[0057]
S1: The FDC controller 200 acquires signal data from various sensors via the data collection device 400.
S2: With respect to the obtained signal data, at least one of the signal data immediately after the switching of the manufacturing step and the signal data immediately before the switching to the next manufacturing step among the signal data in each manufacturing step is filtered.
[0058]
S3: Summarize the filtered data.
S4: The summarized data is delivered to another system such as an APC system. At this time, the various key information described above is added.
[0059]
In this manner, by transferring the filtered and summarized high-reliability data to the APC system 120, the data can be used for a run-to-run recipe calculation, and process variations can be reduced. In addition, by cooperating with the YMS 130, it is possible to detect a decrease in yield due to the device at an early stage and to investigate the cause in a short time, so that the yield can be improved. Further, by cooperating with the EES 140, it can be used for PM (Preventive Maintainance) scheduling and prediction of parts replacement time, so that the apparatus operation rate can be improved. Thus, the productivity in semiconductor manufacturing can be improved by cooperating with another system.
[0060]
(Supplementary Note 1) In a signal processing device that processes signal data from a plurality of sensors that detect a device state of a semiconductor manufacturing device,
A sensor information acquisition unit that acquires the signal data of each manufacturing step in the semiconductor manufacturing apparatus at predetermined time intervals,
Of the signal data in each of the manufacturing steps, the signal data immediately after switching to the manufacturing step, and a filtering unit that filters at least one of the signal data immediately before switching to the next manufacturing step,
A summarizing unit for summarizing the filtered signal data;
A signal processing device comprising:
[0061]
(Supplementary note 2) The signal processing device according to supplementary note 1, wherein the filtering unit filters the signal data for a predetermined time or a predetermined number of samples.
[0062]
(Supplementary note 3) The signal processing device according to supplementary note 1, further comprising a multivariate analysis unit that performs a multivariate analysis on the signal data of the plurality of filtered sensors.
[0063]
(Supplementary note 4) The signal processing device according to supplementary note 3, wherein the summarizing unit summarizes the result of the multivariate analysis for each of the manufacturing steps.
(Supplementary Note 5) The signal processing device according to Supplementary Note 1, wherein data management information including information on a manufacturing process is added to the summarized signal data, and the data is delivered to various systems in a semiconductor manufacturing process.
[0064]
(Supplementary Note 6) In a signal processing method for processing signal data from a plurality of sensors for detecting an apparatus state of a semiconductor manufacturing apparatus,
Acquiring the signal data of each manufacturing step in the semiconductor manufacturing apparatus at predetermined time intervals,
Of the signal data in each of the manufacturing steps, the signal data immediately after the switching of the manufacturing step, filtering at least one of the signal data immediately before switching to the next manufacturing step,
Summarizing the filtered signal data;
A signal processing method characterized by the above-mentioned.
[0065]
【The invention's effect】
As described above, according to the present invention, signal data from a plurality of sensors for detecting the device state of a semiconductor manufacturing device is obtained at predetermined time intervals, and the signal data immediately after the switching of the manufacturing step and the next manufacturing step are performed. Since at least one of the signal data immediately before the switching is filtered and summarized, the signal data indicating the device state can be accurately extracted and summarized.
[0066]
In this way, by adding data including information on a manufacturing process to the summarized data and transferring the data to various systems such as an APC system, it is possible to improve productivity in semiconductor manufacturing.
[Brief description of the drawings]
FIG. 1 is a principle configuration diagram showing the principle of a signal processing device according to an embodiment of the present invention.
FIG. 2 is a first example of filtering.
FIG. 3 is a second example of filtering.
FIG. 4 is a third example of filtering.
FIG. 5 is a fourth example of filtering.
FIG. 6 is a schematic configuration diagram of a manufacturing system.
FIG. 7 is a hardware configuration example of an FDC controller.
FIG. 8 is an example of a filtering setting screen.
FIG. 9 is an example of signal data before being filtered.
FIG. 10 is an example of signal data after filtering.
FIG. 11 is a flowchart illustrating a processing flow of a signal processing method according to an embodiment of the present invention.
[Explanation of symbols]
Reference Signs List 10 signal processing device 11 sensor information acquisition unit 12 filtering unit 13 summarization unit 14 multivariate analysis unit 20 semiconductor manufacturing devices 30-1, 30-2, ..., 30-m sensor

Claims (5)

In a signal processing device that processes signal data from a plurality of sensors that detect a device state of a semiconductor manufacturing device,
A sensor information acquisition unit that acquires the signal data of each manufacturing step in the semiconductor manufacturing apparatus at predetermined time intervals,
Of the signal data in each of the manufacturing steps, the signal data immediately after switching to the manufacturing step, and a filtering unit that filters at least one of the signal data immediately before switching to the next manufacturing step,
A summarizing unit for summarizing the filtered signal data;
A signal processing device comprising: The signal processing device according to claim 1, wherein the filtering unit filters the signal data for a predetermined time or a predetermined number of samples. The signal processing device according to claim 1, further comprising a multivariate analysis unit that performs a multivariate analysis on the filtered signal data of the plurality of sensors. 2. The signal processing apparatus according to claim 1, wherein data management information including information on a manufacturing process is added to the summarized signal data, and the signal data is transferred to various systems in a semiconductor manufacturing process. In a signal processing method for processing signal data from a plurality of sensors for detecting an apparatus state of a semiconductor manufacturing apparatus,
Acquiring the signal data of each manufacturing step in the semiconductor manufacturing apparatus at predetermined time intervals,
Of the signal data in each of the manufacturing steps, the signal data immediately after the switching of the manufacturing step, filtering at least one of the signal data immediately before switching to the next manufacturing step,
Summarizing the filtered signal data;
A signal processing method characterized by the above-mentioned.

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