阅读说明：本技术 用于基于设备可靠性指数控制基于批次风险分数的动态批次测量的方法和系统 (Method and system for controlling dynamic batch measurement based on batch risk score based on equipment reliability index ) 是由 洪兑荣 朴珍佑 于 2018-05-25 设计创作，主要内容包括：提供了一种用于基于设备可靠性指数控制基于批次风险分数的动态批次测量的方法和系统。根据本发明的实施例的用于控制测量的方法：计算半导体制造中用于特定工艺的特定设备的设备可靠性指数；基于设备可靠性指数,计算用于特定工艺的特定设备的风险分数；和基于风险分数,确定是否测量由用于特定工艺的特定设备处理的半导体产品。因此,根据设备可靠性指数进行差异化质量监控和管理是可行的,测量仪器可被有效地使用,质量和产量可通过及时地测量被提高,并且管理便利性可通过自动的和动态的批次测量控制被增加。(A method and system for controlling a batch risk score based dynamic batch measurement based on an equipment reliability index is provided. A method for controlling measurements according to an embodiment of the invention: calculating a device reliability index for a specific device used for a specific process in semiconductor manufacturing; calculating a risk score for a particular piece of equipment for a particular process based on the equipment reliability index; and determining whether to measure the semiconductor product processed by the particular equipment for the particular process based on the risk score. Therefore, it is possible to perform differentiated quality monitoring and management according to the equipment reliability index, the measuring instrument can be effectively used, quality and yield can be improved by timely measurement, and management convenience can be increased by automatic and dynamic batch measurement control.)

1. A measurement control method comprising:

calculating a device reliability index for a specific device used for a specific process in semiconductor manufacturing;

calculating a risk score for a particular piece of equipment for a particular process based on the equipment reliability index; and

based on the risk score, it is determined whether to measure a semiconductor product being processed in a particular apparatus for a particular process.

2. The method of claim 1, wherein the step of calculating a device reliability index comprises:

calculating the process stability of the specific process;

calculating device stability for the particular device; and

the equipment reliability index is calculated by using the operation of process stability and equipment stability.

3. The method of claim 2, wherein the device reliability index is calculated by using the following equation:

the equipment reliability index is the process stability x the equipment stability.

4. The method of claim 2, wherein the step of calculating process stability comprises: the process stability S was calculated by using the following equation_op：

S_op＝Min(Cpk,1)

Cpk＝Min{(USL-m)/3σ,(m-LSL)/3σ}

Where Min is the minimum of the listed values, m is the target value according to the process specification, USL is the upper specification limit, LSL is the lower specification limit, and σ is the standard deviation.

5. The method of claim 2, wherein the step of computing device stability comprises: device stability is calculated based on the frequency of occurrence of fault detection and classification chaining during a particular period.

6. The method of claim 1, further comprising: the offset of the risk score is calculated,

wherein the step of calculating a risk score comprises: calculating a risk score based on the device reliability index and the offset.

7. The method of claim 6, wherein the offset has a value that varies according to the number of semiconductor products processed after the measurement.

8. The method of claim 7, wherein the step of calculating the offset comprises: the offset is calculated by an operation using the number of semiconductor products processed after the measurement and a reference measurement period.

9. The method of claim 8, wherein the reference measurement period is an average measurement period calculated by using the number of semiconductor products processed and the number of measured semiconductor products during a specific period.

10. The method of claim 6, wherein the step of calculating a risk score comprises: the risk score is calculated by using the following equation:

risk score 1-device reliability index x offset.

11. The method of claim 1, wherein the step of determining comprises: the measurement is determined to be taken when the risk score reaches a reference value.

12. The method of claim 1, wherein the step of calculating a device reliability index comprises: periodically calculating device reliability; and is

Wherein the step of calculating a risk score and the step of determining comprise: the calculations and determinations are made in real time each time the semiconductor product is processed in a particular facility.

13. A measurement control system comprising:

an obtaining unit configured to obtain data on a specific apparatus used for a specific process in semiconductor manufacturing; and

a processor configured to: the method includes calculating a device reliability index for a particular device for a particular process by using obtained data, calculating a risk score for the particular device for the particular process based on the device reliability index, and determining whether to measure a semiconductor product processed in the particular device for the particular process based on the risk score.

Technical Field

The present disclosure relates to semiconductor measurement related art, and more particularly, to a method and system for controlling lot (lot) measurements during semiconductor manufacturing.

Background

In semiconductor manufacturing, measurements may be performed to monitor whether there is a quality problem in a process or equipment. However, not all products are measured, and some of the products are selected and measured according to the measurement period.

In some cases, the engineer may decide to measure according to a manual. For example, an engineer may decide to measure when there is a change in manufacturing/technology (such as a change in equipment, materials, or processes), when a process or equipment does not meet specifications and therefore issues an alarm, or when manufacturing is interrupted.

Measurements performed at fixed periods are not valid because the quality of the process or the equipment is not taken into account, and measurements by engineers according to manuals are only performed restrictively in certain cases.

Disclosure of Invention

Technical problem

The present disclosure has been developed to address the above-discussed deficiencies of the prior art, and it is an object of the present disclosure to provide a method and system for dynamically controlling batch measurements based on batch risk scores based on equipment reliability index of a particular equipment used for a particular process in semiconductor manufacturing.

Technical scheme

According to an embodiment of the present disclosure for achieving the above object, a measurement control method includes: calculating a device reliability index for a specific device used for a specific process in semiconductor manufacturing; calculating a risk score for a particular piece of equipment for a particular process based on the equipment reliability index; and determining whether to measure the semiconductor product processed in the particular equipment for the particular process based on the risk score.

Further, the step of calculating the device reliability index may comprise: calculating the process stability of the specific process; calculating device stability for the particular device; and calculating an equipment reliability index by using the operation of the process stability and the equipment stability.

Further, the device reliability index may be calculated by using the following equation:

equipment reliability index (process stability x equipment stability)

Further, the step of calculating the process stability may include: the process stability (S) was calculated by using the following equation_op)：

S_op＝Min(Cpk,1)

Cpk＝Min{(USL-m)/3σ,(m-LSL)/3σ}

Min: minimum value of the listed values

m: target value according to process specification

And (3) USL: upper limit of specification

LSL: lower limit of specification

σ: standard deviation.

Further, the step of computing device stability may comprise: device stability is calculated based on the frequency of occurrence of Fault Detection and Classification (FDC) chaining during a particular period.

Further, the measurement control method according to an embodiment of the present disclosure may further include: the offset of the risk score is calculated, and the step of calculating the risk score may comprise: calculating a risk score based on the device reliability index and the offset.

Further, the offset may have a value that varies according to the number of semiconductor products processed after the measurement.

Further, the step of calculating the offset may comprise: the offset is calculated by an operation using the number of semiconductor products processed after the measurement and a reference measurement period.

Further, the reference measurement period may be an average measurement period calculated by using the number of semiconductor products processed during a specific period and the measured number of semiconductor products.

Further, the step of calculating a risk score may comprise: the risk score is calculated by using the following equation:

risk score of 1-equipment reliability index x offset

Further, the step of determining may include: the measurement is determined to be taken when the risk score reaches a reference value.

Further, the step of calculating the device reliability index may comprise: periodically calculating device reliability; and the step of calculating a risk score and the step of determining may comprise: the calculations and determinations are made in real time each time the semiconductor product is processed in a particular facility.

According to another embodiment of the present disclosure, a measurement control system includes: an obtaining unit configured to obtain data on a specific apparatus for a specific process in semiconductor manufacturing; and a processor configured to calculate an equipment reliability index of a specific equipment for a specific process by using the obtained data, calculate a risk score of the specific equipment for the specific process based on the equipment reliability index, and determine whether to measure a semiconductor product processed in the specific equipment for the specific process based on the risk score.

Advantageous effects

According to embodiments of the present disclosure as described above, batch measurements may be dynamically controlled based on a batch risk score based on a device reliability index for a particular device used for a particular process in semiconductor manufacturing. Therefore, batch measurement is frequently performed when the equipment reliability index is low, and batch measurement is intermittently performed when the equipment reliability index is high, so that quality monitoring/management according to the difference of the equipment reliability indexes is possible.

Therefore, according to the embodiments of the present disclosure, a measuring apparatus can be effectively used, quality/yield can be improved by timely measuring, and management convenience can be increased by automatic/dynamic batch measurement control.

Drawings

FIG. 1 is a flow chart provided to explain a method for dynamically controlling batch measurements according to an embodiment of the present disclosure;

FIG. 2 is a view showing S_op×S_eq×L_exA view of the curve of (a);

FIG. 3 is a graph showing a batch risk score curve; and

fig. 4 is a block diagram of a measurement control system according to another embodiment of the present disclosure.

Detailed Description

Hereinafter, the present disclosure will be described in detail with reference to the accompanying drawings.

Fig. 1 is a flow chart provided to explain a method for dynamically controlling batch measurements according to an embodiment of the present disclosure.

A method for dynamically controlling batch measurement according to an embodiment of the present disclosure is a method for calculating a batch risk score based on an equipment reliability index and dynamically determining whether to measure a batch based on the batch risk score.

Thus, it is dynamically determined whether to measure a lot removed from a device, and the determination is made with reference to a lot risk score based on the device reliability index.

The lot risk score is an index that indicates the risk that a quality issue that may occur when a lot removed from the equipment is not measured is not identified.

When the equipment reliability index is low, the method for dynamically controlling the batch measurement according to the embodiment of the present disclosure sets the batch risk score to be calculated high so that the batch measurement is frequently performed. On the other hand, when the equipment reliability index is high, the method sets the lot risk score to be calculated low so that the lot measurement is performed intermittently. Thus, the quality may be monitored/managed differently according to the device reliability index.

Methods for dynamically controlling batch measurements according to embodiments of the present disclosure are performed according to process and equipment, respectively. That is, the algorithm shown in fig. 1 is respectively performed for each specific apparatus (e.g., a third apparatus among 20 pieces of apparatuses for an etching process) (hereinafter, referred to as "process _ apparatus") for a specific process (e.g., an etching process corresponding to the 11 th process among 100 processes).

In one embodiment of the present disclosure, it is assumed that semiconductor products are measured on a batch basis, but this is merely an example, and embodiments in which semiconductor products are measured in other units fall within the scope of the present disclosure.

The method shown in fig. 1 is performed by a dynamic batch measurement control system (hereinafter, referred to as "measurement control system") as a kind of computing system.

As shown in fig. 1, the measurement control system obtains process _ equipment data required for calculating an equipment reliability index (S110). The data obtained in step S110 includes the following data on process _ equipment:

1) m: target value according to process specification

2) USL (Upper limit of specification)

3) LSL (lower specification)

4) σ: standard deviation of

5)L_cnt: number of batches that have been processed in the past two weeks

6)L_fdc: number of times that FDC interlock (interlock) has occurred in the past two weeks

7)L_mes: number of batches that have been measured in the past two weeks

Next, the measurement control system calculates process stability by using the data obtained in step S110 (S120). Stability of the Process S_opCan be calculated according to equation 1 below:

[ equation 1]

S_op＝Min(Cpk,1)

Cpk＝Min{(USL-m)/3σ,(m-LSL)/3σ}

Where Min is the minimum of the listed values. Thus, process stability S_opWith a maximum value of 1.

Further, the measurement control system calculates the device stability by using the data obtained in step S110 (S130). Device stability S_eqCan be calculated by using the following equation 2:

[ equation 2]

S_eq＝exp(-3×L_fdc/L_cnt)

From equation 2 above, it can be seen that the device stability S_eqDetermined by the frequency of occurrence of FDC interlocks over the past two weeks.

Next, the measurement control system measures the process stability S by using the process stability S calculated in step S120_opAnd the device stability S calculated in step S130_eqTo calculate a device reliability index (S140). The device reliability index may be calculated by using the following equation 3:

[ equation 3]

Equipment reliability index is S_op×S_eq

Thereafter, the measurement control system calculates a Lot Risk offset (Lot Risk extension) (S150). Batch risk offset L_exCan be calculated by using the following equation 4:

[ equation 4]

L_ex＝exp(-30×L_m/o/L_avg)

Wherein L is_m/oIs the number of lots processed and removed after the measurement in the ProcessToolSet. For example, the 10 th lot processed and removed in the ProcessToolSet is measured, then the 11 th lot, the 12 th lot, and the 13 th lot are processed and removed in the ProcessToolSet, and then the measurement is not performed, "L_m/o＝3”。

Furthermore, L_avgIs an average measurement period of the process _ equipment over the past two weeks, and can be calculated according to the following equation 5 by using the data obtained in step S110:

[ equation 5]

L_avg＝L_mes/L_cnt

L_avgIt may not be calculated according to equation 5 but may be determined by an administrator by considering device characteristics and a manufacturing environment. The considered device characteristics may include the degree of degradation of the device and the past failure rate/accident history, and the manufacturing environment may include the number of products/manufacturing speed.

Next, the metrology control system bases the equipment reliability index calculated in step S140 and the lot risk offset L calculated in step S150_exTo calculate a lot risk score (S160).

As described above, the lot risk score represents an index that indicates the risk that quality problems that may occur when a lot removed from the equipment is not measured are not identified. Batch Risk score L_riskCan be calculated by the following equation 6:

[ equation 6]

L_risk1-device reliability index × L_ex＝1-S_op×S_eq×L_ex

Stability of the Process S_opDevice stability S as an exponential function with a maximum value of 1_eqAnd batch risk offset L_exWith a maximum value of 1. Thus, a batch risk score L is formed_riskIs represented by the normalized probability value (0-1), and the batch risk score L in equation 6 above_riskIs calculated as a probability value (0-1).

Thereafter, the measurement control system determines whether to measure the lot processed and removed in the process _ equipment based on the lot risk score calculated in step S160 (S170).

In particular, when the batch risk score exceeds 0.95, the batch is measured, but when the batch risk score is less than or equal to 0.95, the batch is not measured and the measurement is skipped.

For detailed explanation, FIG. 2 shows "S_op×S_eq×L_ex"and figure 3 shows a batch risk score curve.

As shown in fig. 2, S_op×S_eq×L_exHeight (maximum) of p (x) is determined by process stability (S)_op) X apparatus stability (S)_eq) It doesThen, and the slope is offset from the batch risk (L)_ex) And (4) determining multiplication.

Furthermore, as shown in fig. 3, the batch risk score curve p (y) and the curve p (x) [ ═ S_op×S_eq×L_ex]Point symmetry in the case where y is 0.5.

Further, as shown in fig. 2 and 3, when the batch risk score p (y) is 0.95 (i.e., when p (x) [ ═ S)_op×S_eq×L_ex]0.05) the measurement is performed and L_m/oBecomes "0". Therefore, p (y) becomes the minimum value and p (x) becomes the maximum value.

So far, a dynamic batch measurement method based on a batch risk score based on an equipment reliability index has been described with reference to preferred embodiments.

The dynamic batch measurement method according to an embodiment of the present disclosure includes a process of calculating a device reliability index (steps S110 to S140), and a process of calculating a batch risk score and dynamically measuring according to the batch risk score (steps S150 to S170).

The process of calculating the lot risk score and dynamically measuring based on the lot risk score (steps S150-S170) should be performed in real time each time a lot is processed and moved out of the process _ tool. However, the process of calculating the device reliability index (steps S110 to S140) may be performed at a certain cycle (e.g., every 8 hours).

A measurement control system that performs a dynamic batch measurement control method according to an embodiment of the present disclosure will be described in detail with reference to fig. 4. Fig. 4 is a block diagram of a measurement control system according to another embodiment of the present disclosure.

As shown in fig. 4, the measurement control system according to the embodiment of the present disclosure includes a communication unit 210, a display 220, a processor 230, an input unit 240, and a storage device 250.

The communication unit 210 is a device for communicating with an external device or a connection of an external network and transmitting data, and obtains/extracts process _ equipment data for calculating an equipment reliability index and a batch risk offset.

The display 220 is a device for displaying information, and displays a lot risk score, i.e., information on whether a measurement is performed. The input unit 240 is a means for inputting information and may be used to input process _ equipment data and/or settings of a manager.

The display 220 and the input unit 240 may be integrated into a touch screen, and this is more useful when the measurement control system is of the mobile type.

Since the above process _ equipment data may be received from the process _ equipment or the network through the communication unit 210 or may be input and collected through the input unit 240, the communication unit 210 and the input unit 240 may serve as data obtaining means.

The processor 230 executes the dynamic batch measurement control algorithm shown in fig. 1 by using the obtained process _ equipment data, and may display the executed result on the display 220 or may transmit the result to an external device/network through the communication unit 210.

The memory device 250 provides the memory space required by the processor 230 to execute the dynamic batch measurement control algorithm.

The technical idea of the present disclosure is applicable to a computer-readable recording medium recording a computer program for executing the functions of the apparatus and method according to the present embodiment. Also, the technical idea according to various embodiments of the present disclosure may be implemented in the form of computer readable codes recorded on a computer readable recording medium. The computer readable recording medium may be any data storage device that can be read by a computer and can store data. For example, the computer-readable recording medium may be Read Only Memory (ROM), Random Access Memory (RAM), CD-ROMs, magnetic tapes, floppy disks, optical disks, hard disk drives, etc. The computer-readable code or program stored in the computer-readable recording medium can be transmitted via a network connected between computers.

Furthermore, while preferred embodiments of the present disclosure have been illustrated and described, the present disclosure is not limited to the specific embodiments described above. Various changes may be made by those skilled in the art without departing from the scope of the present disclosure claimed in the claims, and further, the changed embodiments should not be construed as being separated from the technical idea or expectation of the present disclosure.