Wafer particle prediction method and prediction system, and furnace tube particle risk control method

Abstract

The invention provides a wafer particle prediction method and system and a furnace tube particle risk control method. Monitoring pieces are placed at the upper end, the middle end and the lower end of a wafer boat, and the number of particles on the monitoring pieces is predicted according to the particle behavior rule in the furnace tube maintenance period; predicting the particle number of wafers at different wafer bearing positions of the wafer boat according to the particle number on the monitoring sheet; and calculating the particle defect rate of each group of wafers based on the chip number of the wafers, further calculating the total risk values of all the wafers in each group at different wafer bearing positions of the wafer boat under different arrangement sequences, and selecting the arrangement sequence meeting the requirements with the lowest total risk value for operation. The particle prediction system for furnace tube operation is established, particle behaviors of each operation batch are effectively predicted, reasonable configuration of furnace tube machine tables and furnace tube positions is further carried out on different products according to the number difference of product chips, and therefore the effect of particles of a low-pressure chemical deposition furnace tube on the product yield is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of integrated circuits, and in particular to a wafer particle prediction method and prediction system, and a furnace tube particle risk control method. Background Art

[0002] In a vertical LPCVD (Low Pressure Chemical Vapor Deposition) furnace, a number of product wafers are placed from top to bottom on fixed-pitch boats, which then ascend into the reaction chamber (tube) for deposition. A flat, regenerated wafer is placed at the top, middle, and bottom of the product placement area to monitor particle status throughout the batch.

[0003] Due to the characteristics of LPCVD, the thickness of the deposited film on hot wall surfaces such as the inner wall of the reaction chamber, the surface of the wafer boat, and the inner wall of the downstream pipeline gradually accumulates during the maintenance cycle. The thin film accumulated on the surface of the cavity will peel off under the action of stress to form particles that are blown onto the surface of the wafer during operation, resulting in a decrease in product yield or even product scrapping. Summary of the Invention

[0004] The purpose of the present invention is to provide a wafer particle prediction method and prediction system, and a furnace tube particle risk control method to solve the problem that particles from the LPCVD furnace tube are blown onto the wafer surface during operation, resulting in a reduction in product yield or even product scrapping.

[0005] To solve the above technical problems, the present invention provides a wafer particle prediction method, comprising:

[0006] A furnace tube is provided, wherein a wafer boat of the furnace tube comprises three ends, upper, middle and lower, and a plurality of wafer carrying positions between the three ends, and monitoring pieces are placed at the three ends of the wafer boat respectively;

[0007] predicting the number of particles on the monitoring sheet based on the particle behavior pattern during the maintenance period of the furnace tube;

[0008] and predicting the number of particles on the wafers at different wafer carrying positions according to the number of particles on the monitoring film;

[0009] The particle defect rate of the wafers at different wafer carrying positions is calculated based on the number of chips in different groups of wafers and the number of particles on the wafers at different wafer carrying positions, and the total risk value of each group of wafers at different wafer carrying positions under different arrangement orders is calculated, and the arrangement order that meets the requirements and has the lowest total risk value is selected for operation.

[0010] Optionally, the furnace tube includes a reaction chamber, and the number of particles on the monitoring piece includes the number of particles generated on the monitoring piece predicted based on the thickness of the film deposited on the surface of the wafer boat and the number of particles generated on the monitoring piece predicted based on the thickness of the film deposited on the inner wall of the reaction chamber.

[0011] Optionally, the calculation formula for the number of particles in the monitoring film is:

[0012]

[0013] Among them, n is the nth monitoring piece, PD n is the number of particles in the nth monitoring piece, PDT n The number of particles generated on the nth monitoring piece for predicting the thickness of the film deposited on the inner wall of the reaction chamber, PDB n The number of particles generated on the nth monitoring piece for predicting the film thickness deposited on the wafer boat surface, Base n Q is the long-term benchmark particle count at the initial stage of machine maintenance at the nth monitoring piece; n is the maximum number of particles generated by the peeling of the deposited film on the inner wall of the reaction chamber at the nth monitoring piece; TT n M is the deposition film thickness on the inner wall of the reaction chamber when the maximum number of particles at the nth monitoring piece occurs; n R is the influence coefficient of the deposition film thickness on the particles generated by peeling at the nth monitoring piece; n The maximum number of particles generated by the peeling of the deposited film on the wafer boat surface before the machine maintenance at the nth monitoring piece; TB n N is the deposition film thickness on the wafer boat surface during maintenance of the tool at the nth monitoring piece; n is the influence coefficient of the deposited film thickness on the wafer boat surface at the nth monitoring piece on the particles generated by peeling; X is the cumulative film thickness of the film on the inner wall of the reaction chamber; y is the cumulative film thickness of the film on the wafer boat surface.

[0014] Optionally, the furnace tube wafer boat includes wafer carrying positions 1, 2, ...W arranged in sequence from top to bottom, where W is a natural number greater than or equal to 2 and less than or equal to 6, and each wafer carrying position is used to place a group of the wafers. When two wafer carrying positions are set on the wafer boat, a first monitoring piece is placed at the top of the first wafer carrying position, a second monitoring piece is placed between the first wafer carrying position and the second wafer carrying position, and a third monitoring piece is placed at the bottom of the second wafer carrying position; when three wafer carrying positions are set on the wafer boat, a first monitoring piece is placed at the top of the first wafer carrying position, a second monitoring piece is placed in the middle of the second wafer carrying position, and a third monitoring piece is placed at the bottom of the third wafer carrying position; when four wafer carrying positions are set on the wafer boat, a first monitoring piece is placed at the top of the first wafer carrying position, a second monitoring piece is placed between the second wafer carrying position and the third monitoring piece is placed at the bottom of the third wafer carrying position A second monitoring piece is placed between the third wafer carrying position and the fourth wafer carrying position, and a third monitoring piece is placed at the bottom of the fourth wafer carrying position; when five wafer carrying positions are set on the wafer boat, a first monitoring piece is placed at the top of the first wafer carrying position, a second monitoring piece is placed in the middle of the third wafer carrying position, and a third monitoring piece is placed at the bottom of the fifth wafer carrying position; when six wafer carrying positions are set on the wafer boat, a first monitoring piece is placed at the top of the first wafer carrying position, a second monitoring piece is placed between the third wafer carrying position and the fourth wafer carrying position, and a third monitoring piece is placed at the bottom of the sixth wafer carrying position. The particle defect rate of the wafers at different wafer carrying positions is predicted by the first monitoring piece, the second monitoring piece and the third monitoring piece, and then the total risk value of each group of wafers at different wafer carrying positions under different arrangement orders is calculated.

[0015] Optionally, when two wafer carrying positions are provided on the wafer boat, the average number of particles at the first wafer carrying position and the average number of particles at the second wafer carrying position are calculated as follows:

[0016] PDP1=(PD1+PD2) / 2

[0017] PDP2=(PD2+PD3) / 2

[0018] When three wafer loading positions are set on the wafer boat, the average number of particles at the first wafer loading position, the average number of particles at the second wafer loading position, and the average number of particles at the third wafer loading position are calculated as follows:

[0019] PDP1=(PD1*2+PD2) / 3

[0020] PDP2=PD2

[0021] PDP2=(PD2+PD3*2) / 3

[0022] When four wafer carrying positions are set on the wafer boat, the average number of particles at the first wafer carrying position, the average number of particles at the second wafer carrying position, the average number of particles at the third wafer carrying position, and the average number of particles at the fourth position are calculated as follows:

[0023] PDP1=(PD1*3+PD2) / 4

[0024] PDP2=(PD1+PD2*3) / 4

[0025] PDP3=(PD2*3+PD3) / 4

[0026] PDP4=(PD2+PD3*3) / 4

[0027] When five wafer carrying positions are set on the wafer boat, the average number of particles at the first wafer carrying position, the average number of particles at the second wafer carrying position, the average number of particles at the third wafer carrying position, the average number of particles at the fourth wafer carrying position, and the average number of particles at the fifth wafer carrying position are calculated as follows:

[0028] PDP1=(PD1*4+PD2) / 5

[0029] PDP2=(PD1*2+PD2*3) / 5

[0030] PDP3=PD2

[0031] PDP4=(PD2*3+PD3*2) / 5

[0032] PDP5=(PD2+PD3*4) / 5

[0033] When six wafer carrying positions are set on the wafer boat, the average number of particles at the first wafer carrying position, the average number of particles at the second wafer carrying position, the average number of particles at the third wafer carrying position, the average number of particles at the fourth wafer carrying position, the average number of particles at the fifth wafer carrying position, and the average number of particles at the sixth wafer carrying position are calculated as follows:

[0034] PDP1=(PD1*5+PD2) / 6

[0035] PDP2=(PD1+PD2) / 2

[0036] PDP3=(PD1+PD2*5) / 6

[0037] PDP4=(PD2*5+PD3) / 6

[0038] PDP5=(PD2+PD3) / 2

[0039] PDP6=(PD2+PD3*5) / 6

[0040] Among them, PDP1 is the average number of particles at the first wafer carrying position, PDP2 is the average number of particles at the second wafer carrying position, PDP3 is the average number of particles at the third wafer carrying position, PDP4 is the average number of particles at the fourth wafer carrying position, PDP5 is the average number of particles at the fifth wafer carrying position, PDP6 is the average number of particles at the sixth wafer carrying position, PD1 is the number of particles of the first monitoring piece, PD2 is the number of particles of the second monitoring piece, and PD3 is the number of particles of the third monitoring piece.

[0041] Optionally, the particle defect rate of the wafers in a group of wafers at one of the wafer carrying positions is: the ratio of the average number of particles at the wafer carrying position to the number of chips in the group of wafers.

[0042] Optionally, different wafer carrying positions and different groups of wafers may have multiple arrangement sequences, wherein a method for calculating the total risk value of each group of wafers at different wafer carrying positions under one arrangement sequence includes:

[0043] When two wafer carrying positions are set on the wafer boat

[0044] V n (AB)=PDP1 / Dc A +PDP2 / Dc B ;

[0045] When three wafer carrying positions are set on the wafer boat

[0046] V n (ABCD)=PDP1 / Dc A +PDP2 / Dc B +PDP3 / Dc C ;

[0047] When four wafer carrying positions are set on the wafer boat

[0048] V n (ABCD)=PDP1 / Dc A +PDP2 / Dc B +PDP3 / Dc C +PDP4 / Dc D ;

[0049] When five wafer carrying positions are set on the wafer boat

[0050] V n (ABCDE)=PDP1 / Dc A +PDP2 / Dc B +PDP3 / Dc C+PDP4 / Dc D +PDP5 / Dc E ;

[0051] When six wafer carrying positions are set on the wafer boat

[0052] V n (ABCDEF)=

[0053] PDP1 / Dc A +PDP2 / Dc B +PDP3 / Dc C +PDP4 / Dc D +PDP5 / Dc E +PDP6 / Dc F ;

[0054] Among them, V n It refers to the total risk value of the nth arrangement order, A, B, C, D, E and F are the groups of the wafers, PDP1 is the average number of particles at the first wafer loading position, PDP2 is the average number of particles at the second wafer loading position, PDP3 is the average number of particles at the third wafer loading position, PDP4 is the average number of particles at the fourth wafer loading position, PDP5 is the average number of particles at the fifth wafer loading position, PDP6 is the average number of particles at the sixth wafer loading position, and Dc A is the number of chips in group A wafer, Dc B is the number of chips in group B wafers, Dc C is the number of chips in group C wafers, Dc D is the number of chips in group D wafers.

[0055] Based on the same inventive concept, the present invention also provides a wafer particle prediction system, comprising:

[0056] A data acquisition unit, wherein the wafer boat of the furnace tube includes three ends (upper, middle, and lower) and multiple wafer carrying positions between the three ends. Monitoring plates are placed at the upper, middle, and lower ends of the wafer boat, and the number of particles on the monitoring plates is predicted based on the particle behavior pattern during the maintenance cycle of the furnace tube;

[0057] The calculation unit predicts the number of particles on the wafers at different wafer carrying positions based on the number of particles on the monitoring film; calculates the particle defect rate of the wafers at different wafer carrying positions based on the number of chips in different groups of wafers and the number of particles on the wafers at different wafer carrying positions, calculates the total risk value of each group of wafers at different wafer carrying positions under different arrangement orders, and selects the arrangement order that meets the requirements and has the lowest total risk value for operation.

[0058] Based on the same inventive concept, the present invention also provides a method for controlling particle risk of a furnace tube, which obtains the total risk value of each group of wafers at different wafer carrying positions in different arrangement orders according to any of the wafer particle prediction methods described above, and determines whether the particle defect rate of each group of wafers in all arrangement orders exceeds a preset threshold;

[0059] If not, the wafers whose particle defect rate exceeds a preset threshold are removed, and the process is performed in an arrangement sequence with the smallest total risk value.

[0060] Optionally, if the particle defect rate of each group of wafers in all arrangement orders exceeds a preset threshold, the furnace tube is reselected.

[0061] Optionally, after the furnace tube performs the process, the accumulated film thickness deposited on the furnace tube or the wafer boat during the process is fed back to the system, and the number of particles at different wafer carrying positions is further predicted.

[0062] The wafer particle prediction method provided by the present invention places monitoring plates at the top, middle, and bottom ends of a wafer boat. The particle counts on the monitoring plates are predicted based on the particle behavior patterns during the maintenance cycle of the furnace tube. The particle counts on the monitoring plates are then used to predict the particle counts of wafers at different wafer loading positions on the wafer boat. The particle defect rate for each group of wafers is calculated based on the number of chips on the wafers. The total risk value for each group of wafers at different wafer loading positions on the wafer boat under different arrangement sequences is then calculated, and the arrangement sequence with the lowest total risk value that meets the requirements is selected for operation. The present invention establishes a particle prediction system for furnace tube operations based on the particle behavior patterns during the maintenance cycle, effectively predicting the particle behavior of each batch of operations. Furthermore, the furnace tube machine and furnace tube positions are rationally configured for different products based on the differences in the number of chips in each product, thereby reducing the impact of particles in the low-pressure chemical deposition furnace tube on product yield. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Those skilled in the art will appreciate that the accompanying drawings are provided for a better understanding of the present invention and do not constitute any limitation on the scope of the present invention.

[0064] Figure 1 This is a flow chart of a wafer particle prediction method according to an embodiment of the present invention.

[0065] Figure 2 2 is a schematic diagram of the furnace tube structure of an embodiment of the present invention.

[0066] Figure 3 Schematic diagram of the relationship between the thickness of the film deposited on the inner wall of the reaction chamber of the furnace tube and the wafer boat and the maintenance of the furnace tube according to an embodiment of the present invention.

[0067] Figure 4This is a comparison diagram of the predicted curve and the actual curve of the influence of the film thickness of the inner wall of the reaction chamber of the furnace tube of the embodiment of the present invention on the monitoring sheet particles.

[0068] Figure 5 This is a comparison diagram of the predicted curve and the actual curve of the influence of the film thickness on the surface of the crystal boat of the furnace tube of the embodiment of the present invention on the monitoring piece particles.

[0069] Figure 6 This is a comparison diagram of the predicted curve and the actual curve of the influence of the furnace tube on the monitoring sheet particles according to the embodiment of the present invention.

[0070] Figure 7 4 is a flow chart of a method for controlling particle risk in a furnace tube according to an embodiment of the present invention.

[0071] In the attached figure:

[0072] 10-furnace tube; 11-reaction chamber; 12-wafer boat; 12a-first wafer carrying position; 12b-second wafer carrying position; 12c-third wafer carrying position; 12d-fourth wafer carrying position; 21-first monitoring plate, 22-second monitoring plate, 23-third monitoring plate. DETAILED DESCRIPTION

[0073] To make the objects, advantages, and features of the present invention more clearly apparent, the present invention is further described below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the drawings are all in a very simplified form and are not drawn to scale. They are only used to conveniently and clearly assist in illustrating the purposes of the embodiments of the present invention. In addition, the structures shown in the drawings are often part of the actual structure. In particular, different drawings may need to illustrate different focuses and sometimes use different scales.

[0074] As used in the present invention, the singular forms "a", "an", and "the" include plural objects, the term "or" is generally used to include the meaning of "and / or", the term "several" is generally used to include the meaning of "at least one", and the term "at least two" is generally used to include the meaning of "two or more". In addition, the terms "first", "second", and "third" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the technical features indicated. Therefore, the features specified as "first", "second", and "third" may explicitly or implicitly include one or at least two of the features. In addition, as used in the present invention, an element is provided on another element, which generally only indicates that there is a connection, coupling, cooperation or transmission relationship between the two elements, and the connection, coupling, cooperation or transmission between the two elements can be direct or indirect through an intermediate element, and should not be understood to indicate or imply the spatial position relationship between the two elements, that is, one element can be in any orientation such as inside, outside, above, below, or to the side of another element, unless the content clearly indicates otherwise. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0075] Figure 1 FIG. 1 is a flow chart of a wafer particle prediction method according to an embodiment of the present invention. Figure 1 As shown, this embodiment provides a wafer particle prediction method, including:

[0076] Step S10, providing a furnace tube, wherein a wafer boat of the furnace tube includes three ends (upper, middle, and lower) and a plurality of wafer carrying positions between the three ends, and monitoring pieces are placed at the upper, middle, and lower ends of the wafer boat respectively;

[0077] Step S20, predicting the number of particles on the monitoring sheet according to the particle behavior pattern during the maintenance period of the furnace tube;

[0078] Step S30, predicting the number of particles on the wafers at different wafer carrying positions according to the number of particles on the monitoring sheet;

[0079] Step S40, calculates the particle defect rate of the wafers at different wafer carrying positions according to the number of chips in different groups of wafers and the number of particles on the wafers at different wafer carrying positions, and calculates the total risk value of each group of wafers at different wafer carrying positions under different arrangement orders, and selects the arrangement order that meets the requirements and has the lowest total risk value for operation.

[0080] Figure 2 Schematic diagram of the furnace tube structure of an embodiment of the present invention. Figure 2As shown, a furnace tube 10 is provided, and the furnace tube 10 includes a reaction chamber 11 and a wafer boat 12. The wafer boat 12 includes three ends, namely, upper, middle, and lower, and a plurality of wafer carrying positions between the three ends, and each wafer carrying position is used to place a group of wafers. The furnace tube wafer boat includes wafer carrying positions 1, 2, ...W arranged in sequence from top to bottom, where W is a natural number greater than or equal to 2 and less than or equal to 6. When two wafer carrying positions are set on the wafer boat, a first monitoring piece is placed at the top of the first wafer carrying position, a second monitoring piece is placed between the first wafer carrying position and the second wafer carrying position, and a third monitoring piece is placed at the bottom of the second wafer carrying position; when three wafer carrying positions are set on the wafer boat, a first monitoring piece is placed at the top of the first wafer carrying position, a second monitoring piece is placed in the middle of the second wafer carrying position, and a third monitoring piece is placed at the bottom of the third wafer carrying position; when four wafer carrying positions are set on the wafer boat, a first monitoring piece is placed at the top of the first wafer carrying position, and a second monitoring piece is placed between the second wafer carrying position and the second wafer carrying position. A second monitoring plate is placed between the wafer loading position and the third wafer loading position, and a third monitoring plate is placed at the bottom of the fourth wafer loading position. When the wafer boat has five wafer loading positions, the first monitoring plate is placed at the top of the first wafer loading position, the second monitoring plate is placed in the middle of the third wafer loading position, and the third monitoring plate is placed at the bottom of the fifth wafer loading position. When the wafer boat has six wafer loading positions, the first monitoring plate is placed at the top of the first wafer loading position, the second monitoring plate is placed between the third and fourth wafer loading positions, and the third monitoring plate is placed at the bottom of the sixth wafer loading position. In this embodiment, the wafer boat 12 includes four wafer loading positions, for example, a first wafer loading position 12a, a second wafer loading position 12b, a third wafer loading position 12c, and a fourth wafer loading position 12d. Monitoring plates are placed outside the wafer loading positions at both ends and in the middle of the wafer loading positions. That is, a first monitoring piece 21 is placed on the side of the first wafer carrying position 12a away from the second wafer carrying position 12b, a second monitoring piece 22 is placed between the second wafer carrying position 12b and the third wafer carrying position 12c, and a third monitoring piece 23 is placed on the side of the fourth wafer carrying position 12d away from the third wafer carrying position 12c.

[0081] Figure 3 This is a schematic diagram showing the relationship between the inner wall of the reaction chamber of the furnace tube and the thickness of the film deposited on the wafer boat and the maintenance of the furnace tube according to an embodiment of the present invention. Figure 3 As shown, Figure 3The horizontal axis is time, and the vertical axis is the thickness of the deposited film. LPCVD furnace tubes are divided into major maintenance and minor maintenance. Major maintenance involves replacing components such as the reaction chamber, wafer boat, and exhaust pipe, while minor maintenance mainly involves replacing the wafer boat. During the major maintenance cycle, the thin film deposited on the inner wall of the reaction chamber will peel off from the inner wall of the reaction chamber, forming particles that fall on the surface of the wafer. This embodiment summarizes the pattern of particle generation in the furnace tube based on actual operation data and estimates the number of particles generated by the peeling of the thin film on the inner wall of the reaction chamber during each batch of operation. During the minor maintenance cycle, the thin film deposited on the surface of the wafer boat will peel off from the surface of the wafer boat, forming particles that fall on the surface of the wafer. This embodiment summarizes the pattern of particle generation in the furnace tube based on actual operation data and estimates the number of particles generated by the peeling of the wafer boat surface during each batch of operation. By superimposing the above two types of prediction data, the particle behavior of each end control chip during each batch of furnace tube operation can be effectively predicted and the operating products can be controlled in advance.

[0082] Specifically, this embodiment summarizes the pattern of particle generation within the furnace tube based on actual operation data, and estimates the number of particles generated by the thin film peeling off the inner wall of the reaction chamber during each batch operation as follows: through a large amount of data, it is confirmed that the number of particles on the monitoring film at each end of the furnace tube gradually increases with the thickness of the deposited film on the inner wall of the reaction chamber. When the deposited film thickness accumulates to TT (TT is the deposited film thickness on the inner wall of the reaction chamber when the maximum number of particles occurs), the number of particles reaches a maximum value, and then gradually decreases and stabilizes with the deposited film thickness. Based on actual operation data, the following formula is used to estimate the number of particles generated by the peeling off of the inner wall of the reaction chamber of each process menu operation:

[0083]

[0084] Among them, n is the nth monitoring piece (the top, middle and bottom three monitoring pieces, n are 1, 2, 3 respectively), PDT n The number of particles generated on the nth monitoring piece for predicting the thickness of the film deposited on the inner wall of the reaction chamber, Base n Q is the long-term benchmark particle count at the initial stage of machine maintenance at the nth monitoring piece; n is the maximum number of particles generated by the peeling of the deposited film on the inner wall of the reaction chamber at the nth monitoring piece; TT n M is the deposition film thickness on the inner wall of the reaction chamber when the maximum number of particles at the nth monitoring piece occurs; n is the influence coefficient of the deposition film thickness of the inner wall of the reaction chamber at the nth monitoring piece on the particles generated by peeling; X is the cumulative film thickness of the film on the inner wall of the reaction chamber.

[0085] Specifically, the number of particles generated by the peeling of the inner wall of the reaction chamber of the furnace tube on the first monitoring piece 21 is:

[0086]

[0087] Where PDT1 is the number of particles generated on the first monitoring slice, predicted based on the thickness of the deposited film on the reactor inner wall; Q1 is the maximum number of particles generated by the thin film deposited on the reactor inner wall on the first monitoring slice; TT1 is the thickness of the deposited film on the reactor inner wall when the maximum number of particles on the first monitoring slice occurs; M1 is the coefficient of influence of the thickness of the deposited film on the reactor inner wall on the generation of particles from the deposition, with 0 < M1 ≤ 1. Base1 is the long-term baseline particle count at the first monitoring slice during the initial maintenance period of the furnace tube; X is the cumulative thickness of the thin film on the reactor inner wall, which increases with each batch within a maintenance cycle.

[0088] The number of particles generated by the peeling of the inner wall of the reaction chamber of the furnace tube on the second monitoring piece 22:

[0089]

[0090] Where PDT2 is the number of particles generated on the second monitoring plate based on the thickness of the deposited film on the reactor inner wall; Q2 is the maximum number of particles generated by the thin film deposited on the reactor inner wall peeling off the second monitoring plate; TT2 is the thickness of the deposited film on the reactor inner wall when the maximum number of particles on the second monitoring plate occurs; M2 is the coefficient of influence of the thickness of the deposited film on the reactor inner wall on the generation of particles from peeling off, where 0 < M2 ≤ 1. Base2 is the long-term baseline particle count at the initial stage of furnace tube maintenance at the second monitoring plate; X is the cumulative film thickness of the reactor inner wall, which increases with each batch within a large maintenance cycle.

[0091] The number of particles generated by the peeling of the inner wall of the reaction chamber of the furnace tube on the third monitoring piece 23:

[0092]

[0093] Where PDT3 is the number of particles generated on the third monitoring slice, predicted based on the thickness of the deposited film on the reactor inner wall; Q3 is the maximum number of particles generated by the thin film deposited on the reactor inner wall peeling off on the third monitoring slice; TT3 is the thickness of the deposited film on the reactor inner wall when the maximum number of particles on the third monitoring slice occurs; M3 is the coefficient of influence of the thickness of the deposited film on the reactor inner wall on the generation of particles from peeling off, with 0 < M3 ≤ 1. Base3 is the long-term baseline particle count at the initial stage of furnace tube maintenance at the third monitoring slice; X is the cumulative film thickness of the reactor inner wall, which increases with each batch within a large maintenance cycle.

[0094] Figure 4 This is a comparison diagram of the predicted curve and the actual curve of the influence of the film thickness of the inner wall of the reaction chamber of the furnace tube of the embodiment of the present invention on the monitoring sheet particles. Figure 4The following is a trend chart showing the actual number of particles on the first monitoring slice at the top of the LPCVD machine as the thickness of the deposited film on the inner wall of the reaction chamber increases, and the predicted number of particles on the first monitoring slice calculated by the prediction model with parameters set to Q1 of 25, TT1 of 12.5, M1 of 0.7, and Base1 of 5 (the influence of the film thickness deposited on the wafer boat surface on the predicted number of particles on the first monitoring slice has been removed). Figure 4 As can be seen, the abscissa represents the thickness of the film deposited on the inner wall of the reaction chamber, in nanometers. The ordinate represents the number of particles. The predicted particle count for the first monitoring piece closely matches the actual number of particles, indicating that the prediction model for the effect of the film thickness on the inner wall of the reaction chamber of the furnace tube on the number of particles on the monitoring piece is accurate.

[0095] This embodiment summarizes the patterns of particle generation within the furnace tubes based on actual operation data. The method for estimating the number of particles generated by wafer boat surface spalling during each batch of operations is as follows: A large amount of data confirms that the number of particles on the monitoring panels at each end of the furnace tubes gradually increases with the thickness of the film deposited on the wafer boat surface. The number of particles reaches a maximum when the accumulated film thickness reaches TB (TB is the thickness of the film deposited on the wafer boat surface during furnace tube maintenance). Thereafter, the number of particles gradually decreases and stabilizes as the film thickness increases. Based on actual operation data, the following formula is used to estimate the number of particles generated by wafer boat surface spalling during each process menu operation:

[0096]

[0097] Among them, n is the nth monitoring slice (the top, middle and bottom three monitoring slices, n are 1, 2, 3 respectively), PDB n The number of particles generated on the nth monitoring piece for predicting the film thickness deposited on the wafer boat surface, Base n R is the long-term benchmark particle count at the initial stage of machine maintenance at the nth monitoring piece; n The maximum number of particles generated by the peeling of the deposited film on the wafer boat surface before the machine maintenance at the nth monitoring piece; TB n N is the deposition film thickness on the wafer boat surface during maintenance of the tool at the nth monitoring piece; n is the influence coefficient of the deposited film thickness on the wafer boat surface at the nth monitoring piece on the particles generated by peeling; y is the cumulative thickness of the film on the wafer boat surface.

[0098] Specifically, the number of particles generated by the peeling of the inner wall of the reaction chamber of the furnace tube on the first monitoring piece 21 is:

[0099] PDB1=R1*(N1) TB 1 -y +Base1

[0100] Among them, PDB1 is the number of particles generated on the first monitoring piece based on the prediction of the deposited film thickness on the wafer boat surface, Base1 is the long-term benchmark particle number at the initial stage of machine maintenance at the first monitoring piece; R1 is the maximum number of particles generated by peeling of the deposited film on the wafer boat surface before machine maintenance at the first monitoring piece; TB1 is the deposited film thickness on the wafer boat surface during machine maintenance at the first monitoring piece; N1 is the influence coefficient of the deposited film thickness on the wafer boat surface at the first monitoring piece on the particles generated by peeling, 0<N1≤1; y is the cumulative thickness of the film on the wafer boat surface.

[0101] The number of particles generated by the peeling of the inner wall of the reaction chamber of the furnace tube on the second monitoring piece 22:

[0102] PDB2=R2*(N2) TB 2 -y +Base2

[0103] Among them, PDB2 is the number of particles generated on the second monitoring piece for predicting the thickness of the deposited film on the wafer boat surface; Base2 is the long-term benchmark particle number at the initial stage of machine maintenance at the second monitoring piece; R2 is the maximum number of particles generated by peeling of the deposited film on the wafer boat surface before machine maintenance at the second monitoring piece; TB2 is the thickness of the deposited film on the wafer boat surface during machine maintenance at the second monitoring piece; N2 is the influence coefficient of the thickness of the deposited film on the wafer boat surface at the second monitoring piece on the particles generated by peeling, 0<N2≤1; y is the cumulative thickness of the film on the wafer boat surface.

[0104] The number of particles generated by the peeling of the inner wall of the reaction chamber of the furnace tube on the third monitoring piece 23:

[0105] PDB3=R3*(N3) TB 3 -y +Base3

[0106] Among them, PDB3 is the number of particles generated on the third monitoring piece for predicting the thickness of the deposited film on the wafer boat surface; Base3 is the long-term benchmark particle number at the initial stage of machine maintenance at the third monitoring piece; R3 is the maximum number of particles generated by peeling of the deposited film on the wafer boat surface before machine maintenance at the third monitoring piece; TB3 is the thickness of the deposited film on the wafer boat surface during machine maintenance at the third monitoring piece; N3 is the influence coefficient of the thickness of the deposited film on the wafer boat surface at the third monitoring piece on the particles generated by peeling, 0<N3≤1; y is the cumulative thickness of the film on the wafer boat surface.

[0107] Figure 5 This is a comparison diagram of the predicted curve and the actual curve of the influence of the film thickness on the surface of the crystal boat of the furnace tube of the embodiment of the present invention on the monitoring piece particles. Figure 5The following is a trend chart showing the actual number of particles on the first monitoring piece at the top of the LPCVD machine as the film thickness on the wafer boat surface increases, and the predicted number of particles on the first monitoring piece calculated using the prediction model with R1 of 60, TB1 of 4.5, N1 of 0.2, and Base1 of 5 (the effect of the film thickness on the wafer boat surface on the predicted number of particles on the first monitoring piece has been removed). Figure 5 As can be seen, the horizontal axis represents the film thickness deposited on the wafer boat surface, in nanometers. The vertical axis represents the number of particles. The predicted particle count for the first monitoring panel is consistent with the actual number of particles, indicating that the prediction model for the effect of the film thickness on the wafer boat surface on the monitoring panel is accurate.

[0108] The number of particles on the monitoring piece includes the number of particles generated on the monitoring piece based on the prediction of the film thickness deposited on the surface of the wafer boat and the number of particles generated on the monitoring piece based on the prediction of the film thickness deposited on the inner wall of the reaction chamber. By superimposing the above two types of prediction data, the particle behavior of each end control piece during each batch operation of the furnace tube can be effectively predicted. Specifically, combining the prediction model of the particle size of each end control piece of the furnace tube based on the film thickness deposited on the inner wall of the reaction chamber and the prediction model of the particle size of each end control piece of the furnace tube based on the film thickness on the surface of the wafer boat, the calculation formula for the overall prediction of the particle size of each end control piece of the furnace tube is:

[0109]

[0110] Among them, n is the nth monitoring piece (the top, middle and bottom three monitoring pieces, n are 1, 2, 3 respectively), PD n is the number of particles in the nth monitoring piece, PDT n The number of particles generated on the nth monitoring piece for predicting the thickness of the film deposited on the inner wall of the reaction chamber, PDB n The number of particles generated on the nth monitoring piece for predicting the film thickness deposited on the wafer boat surface, Base n Q is the long-term benchmark particle count at the initial stage of machine maintenance at the nth monitoring piece; n is the maximum number of particles generated by the peeling of the deposited film on the inner wall of the reaction chamber at the nth monitoring piece; TT n M is the deposition film thickness on the inner wall of the reaction chamber when the maximum number of particles at the nth monitoring piece occurs; n R is the influence coefficient of the deposition film thickness on the particles generated by peeling at the nth monitoring piece; n The maximum number of particles generated by the peeling of the deposited film on the wafer boat surface before the machine maintenance at the nth monitoring piece; TB n N is the deposition film thickness on the wafer boat surface during maintenance of the tool at the nth monitoring piece; n is the influence coefficient of the deposited film thickness on the wafer boat surface at the nth monitoring piece on the particles generated by peeling; X is the cumulative film thickness of the film on the inner wall of the reaction chamber; y is the cumulative film thickness of the film on the wafer boat surface.

[0111] Specifically, the number of particles in the first monitoring piece 21 is:

[0112]

[0113] Among them, PD1 is the number of particles on the first monitoring piece, PDT1 is the number of particles generated on the first monitoring piece for predicting the thickness of the deposited film on the inner wall of the reaction chamber, PDB1 is the number of particles generated on the first monitoring piece for predicting the thickness of the deposited film on the surface of the wafer boat, Base1 is the long-term benchmark particle number at the initial stage of machine maintenance at the first monitoring piece; Q1 is the maximum number of particles generated by peeling of the deposited film on the inner wall of the reaction chamber at the first monitoring piece; TT1 is the thickness of the deposited film on the inner wall of the reaction chamber when the maximum number of particles at the first monitoring piece occurs; M1 is the influence coefficient of the thickness of the deposited film on the inner wall of the reaction chamber at the first monitoring piece on the particles generated by peeling; R1 is the maximum number of particles generated by peeling of the deposited film on the surface of the wafer boat before machine maintenance at the first monitoring piece; TB1 is the thickness of the deposited film on the surface of the wafer boat during machine maintenance at the first monitoring piece; N1 is the influence coefficient of the thickness of the deposited film on the surface of the wafer boat at the first monitoring piece on the particles generated by peeling; X is the cumulative thickness of the film on the inner wall of the reaction chamber; y is the cumulative thickness of the film on the surface of the wafer boat.

[0114]

[0115] Among them, PD2 is the number of particles on the second monitoring piece, PDT2 is the number of particles generated on the second monitoring piece predicted by the thickness of the deposited film on the inner wall of the reaction chamber, PDB2 is the number of particles generated on the second monitoring piece predicted by the thickness of the deposited film on the surface of the wafer boat, Base2 is the long-term benchmark particle number at the initial stage of machine maintenance at the second monitoring piece; Q2 is the maximum number of particles generated by the peeling of the deposited film on the inner wall of the reaction chamber at the second monitoring piece; TT2 is the thickness of the deposited film on the inner wall of the reaction chamber when the maximum number of particles at the second monitoring piece occurs; M2 is the influence coefficient of the thickness of the deposited film on the inner wall of the reaction chamber at the second monitoring piece on the particles generated by peeling; R2 is the maximum number of particles generated by the peeling of the deposited film on the surface of the wafer boat before machine maintenance at the second monitoring piece; TB2 is the thickness of the deposited film on the surface of the wafer boat during machine maintenance at the second monitoring piece; N2 is the influence coefficient of the thickness of the deposited film on the surface of the wafer boat at the second monitoring piece on the particles generated by peeling; X is the cumulative film thickness of the film on the inner wall of the reaction chamber; y is the cumulative film thickness of the film on the surface of the wafer boat.

[0116]

[0117] Among them, PD3 is the number of particles on the third monitoring piece, PDT3 is the number of particles generated on the third monitoring piece predicted by the thickness of the deposited film on the inner wall of the reaction chamber, PDB3 is the number of particles generated on the third monitoring piece predicted by the thickness of the deposited film on the surface of the wafer boat, Base3 is the long-term benchmark particle number at the initial stage of machine maintenance at the third monitoring piece; Q3 is the maximum number of particles generated by the peeling of the deposited film on the inner wall of the reaction chamber at the third monitoring piece; TT3 is the thickness of the deposited film on the inner wall of the reaction chamber when the maximum number of particles at the third monitoring piece occurs; M3 is the influence coefficient of the thickness of the deposited film on the inner wall of the reaction chamber at the third monitoring piece on the particles generated by peeling; R3 is the maximum number of particles generated by the peeling of the deposited film on the surface of the wafer boat before machine maintenance at the third monitoring piece; TB3 is the thickness of the deposited film on the surface of the wafer boat during machine maintenance at the third monitoring piece; N3 is the influence coefficient of the thickness of the deposited film on the surface of the wafer boat at the third monitoring piece on the particles generated by peeling; X is the cumulative film thickness of the film on the inner wall of the reaction chamber; y is the cumulative film thickness of the film on the surface of the wafer boat.

[0118] Figure 6 This is a correlation diagram of actual particles and predicted particles of the influence of the furnace tube on the particles of the monitoring piece according to an embodiment of the present invention. Figure 6 This is a correlation diagram between the actual number of particles in the first monitoring piece on the top of the LPCVD machine and the number of particles predicted based on the above model. Figure 6 The horizontal axis is the predicted number of particles on the top monitoring piece, and the vertical axis is the actual number of particles on the top monitoring piece. It can be seen that the two are linear, which means that the overall model prediction is accurate.

[0119] Effectively predict the particle behavior of each end-control chip during each batch of furnace operations and implement preemptive control of the products being processed. Specifically, a preset threshold (SpecA) is defined for the particle defect rate (suffer ratio) of each wafer lot. The particle defect rate is the ratio of the estimated number of particles on each wafer lot to the total number of chips in the product (die count). If the particle defect rate exceeds the preset threshold, SpecA, the wafer is at risk of being scrapped.

[0120] Specifically, the above model predicts the particle numbers PD1, PD2, and PD3 of the first monitoring piece, the second monitoring piece, and the third monitoring piece at the three ends of the furnace tube, and further predicts the average particle number of different product positions of the wafer boat of the furnace tube.

[0121] When two wafer carrying positions are set on the wafer boat, the average number of particles at the first wafer carrying position and the average number of particles at the second wafer carrying position are calculated as follows:

[0122] PDP1=(PD1+PD2) / 2

[0123] PDP2=(PD2+PD3) / 2

[0124] When three loading positions are set on the wafer boat, the average number of particles at the first wafer loading position, the average number of particles at the second wafer loading position, and the average number of particles at the third wafer loading position are calculated as follows:

[0125] PDP1=(PD1*2+PD2) / 3

[0126] PDP2=PD2

[0127] PDP2=(PD2+PD3*2) / 3

[0128] When four wafer carrying positions are set on the wafer boat, the average number of particles at the first wafer carrying position, the average number of particles at the second wafer carrying position, the average number of particles at the third wafer carrying position, and the average number of particles at the fourth position are calculated as follows:

[0129] PDP1=(PD1*3+PD2) / 4

[0130] PDP2=(PD1+PD2*3) / 4

[0131] PDP3=(PD2*3+PD3) / 4

[0132] PDP4=(PD2+PD3*3) / 4

[0133] When five wafer carrying positions are set on the wafer boat, the average number of particles at the first wafer carrying position, the average number of particles at the second wafer carrying position, the average number of particles at the third wafer carrying position, the average number of particles at the fourth wafer carrying position, and the average number of particles at the fifth wafer carrying position are calculated as follows:

[0134] PDP1=(PD1*4+PD2) / 5

[0135] PDP2=(PD1*2+PD2*3) / 5

[0136] PDP3=PD2

[0137] PDP4=(PD2*3+PD3*2) / 5

[0138] PDP5=(PD2+PD3*4) / 5

[0139] When six wafer carrying positions are set on the wafer boat, the average number of particles at the first wafer carrying position, the average number of particles at the second wafer carrying position, the average number of particles at the third wafer carrying position, the average number of particles at the fourth wafer carrying position, the average number of particles at the fifth wafer carrying position, and the average number of particles at the sixth wafer carrying position are calculated as follows:

[0140] PDP1=(PD1*5+PD2) / 6

[0141] PDP2=(PD1+PD2) / 2

[0142] PDP3=(PD1+PD2*5) / 6

[0143] PDP4=(PD2*5+PD3) / 6

[0144] PDP5=(PD2+PD3) / 2

[0145] PDP6=(PD2+PD3*5) / 6

[0146] Among them, PDP1 is the average number of particles at the first wafer carrying position, PDP2 is the average number of particles at the second wafer carrying position, PDP3 is the average number of particles at the third wafer carrying position, PDP4 is the average number of particles at the fourth wafer carrying position, PDP5 is the average number of particles at the fifth wafer carrying position, PDP6 is the average number of particles at the sixth wafer carrying position, PD1 is the number of particles of the first monitoring piece, PD2 is the number of particles of the second monitoring piece, and PD3 is the number of particles of the third monitoring piece.

[0147] Next, by predicting the particle defect rate of the wafers at different wafer carrying positions, the total risk value of each group of wafers at different wafer carrying positions under different arrangement orders is calculated. The particle defect rate of a group of wafers at one wafer carrying position is: the ratio of the average number of particles at the wafer carrying position to the number of chips in a group of wafers. There are multiple arrangement orders for different wafer carrying positions and different groups of wafers, wherein a method for calculating the total risk value of each group of wafers at different wafer carrying positions under one arrangement order includes:

[0148] When two wafer carrying positions are set on the wafer boat

[0149] V n (AB)=PDP1 / Dc A +PDP2 / Dc B ;

[0150] When three wafer carrying positions are set on the wafer boat

[0151] V n (ABCD)=PDP1 / Dc A +PDP2 / Dc B +PDP3 / Dc C ;

[0152] When four wafer carrying positions are set on the wafer boat

[0153] V n(ABCD)=PDP1 / Dc A +PDP2 / Dc B +PDP3 / Dc C +PDP4 / Dc D ;

[0154] When five wafer carrying positions are set on the wafer boat

[0155] V n (ABCDE)=PDP1 / Dc A +PDP2 / Dc B +PDP3 / Dc C +PDP4 / Dc D +PDP5 / Dc E ;

[0156] When six wafer carrying positions are set on the wafer boat

[0157] V n (ABCDEF)=

[0158] PDP1 / Dc A +PDP2 / Dc B +PDP3 / Dc C +PDP4 / Dc D +PDP5 / Dc E +PDP6 / Dc F ;

[0159] Among them, V n It refers to the total risk value of the nth arrangement order, A, B, C, D, E and F are the groups of the wafers, PDP1 is the average number of particles at the first wafer loading position, PDP2 is the average number of particles at the second wafer loading position, PDP3 is the average number of particles at the third wafer loading position, PDP4 is the average number of particles at the fourth wafer loading position, PDP5 is the average number of particles at the fifth wafer loading position, PDP6 is the average number of particles at the sixth wafer loading position, and Dc A is the number of chips in group A wafer, Dc B is the number of chips in group B wafers, Dc C is the number of chips in group C wafers, Dc D is the number of chips in group D wafers, Dc E is the number of chips in group E wafers, Dc F is the number of chips in group F wafers.

[0160] Different arrangement orders correspond to different total risk values. When four wafer carrying positions are set on the wafer boat and the wafer group arrangement order is ABCD, the total risk value is:

[0161] V1(ABCD)=PDP1 / Dc A +PDP2 / Dc B +PDP3 / Dc C +PDP4 / Dc D

[0162] …

[0163] When the wafer group arrangement order is DCBA, the total risk value is:

[0164] V4(DCBA)=PDP4 / Dc A +PDP3 / Dc B +PDP2 / Dc C +PDP1 / Dc D ,

[0165] If the particle defect rate of any wafer group in the arrangement exceeds the preset threshold, Spec A, the placement order of that group of wafers cannot be used for product dispatch. After eliminating the unsuitable arrangement order, the remaining arrangement with the lowest risk value is used as the placement order for the furnace operation. If the particle defect rate of any lot of wafers in all combinations exceeds the preset threshold, Spec A, the operation conditions are not met and the wafer batch must be replaced for the operation. This method ensures control of the furnace equipment and position, minimizing the impact of particles on products.

[0166] This embodiment further provides a wafer particle prediction system, including:

[0167] A data acquisition unit, wherein the wafer boat of the furnace tube includes three ends (upper, middle, and lower) and multiple wafer carrying positions between the three ends. Monitoring plates are placed at the upper, middle, and lower ends of the wafer boat, and the number of particles on the monitoring plates is predicted based on the particle behavior pattern during the maintenance cycle of the furnace tube;

[0168] The calculation unit predicts the number of particles on the wafers at different wafer carrying positions based on the number of particles on the monitoring film; calculates the particle defect rate of the wafers at different wafer carrying positions based on the number of chips in different groups of wafers and the number of particles on the wafers at different wafer carrying positions, calculates the total risk value of each group of wafers at different wafer carrying positions under different arrangement orders, and selects the arrangement order that meets the requirements and has the lowest total risk value for operation.

[0169] Figure 7 FIG. 1 is a flow chart of a method for controlling particle risk in a furnace tube according to an embodiment of the present invention. Figure 7As shown, this embodiment also provides a method for controlling particle risk of a furnace tube. According to any of the wafer particle prediction methods described above, the total risk value of each group of wafers in different wafer carrying positions under different arrangement orders is obtained, and it is determined whether the particle defect rate of each group of wafers under all arrangement orders exceeds a preset threshold. If not, the wafers with a particle defect rate exceeding the preset threshold are removed, and the arrangement order with the smallest total risk value is selected to execute the process. The specific steps are as follows:

[0170] In step S101 , multiple groups of wafers are selected and the number of chips in different groups of wafers is read.

[0171] In step S102 , the system calculates the particle defect rate and the total risk value of each group of wafers in different arrangement orders at different wafer carrying positions.

[0172] In step S103, the system determines whether the particle defect rate of the wafer group in all arrangement sequences exceeds the preset threshold. If so, the system returns to step S101 and changes the batch of wafers. If not, the system executes step S104.

[0173] Step S104 , removing the arrangement sequences with wafer particle defect rates exceeding a preset threshold, and selecting the arrangement sequence with the smallest total risk value to perform the operation.

[0174] In step S105 , the machine performs the product operation according to the arrangement sequence recommended by the system, and feeds back the accumulated furnace tube or wafer boat deposition film thickness to the system.

[0175] In step S106, the deposition film thickness data on the furnace tube or wafer boat is used to further predict the particle count at each wafer loading position. That is, after the furnace tube performs the process, the accumulated deposition film thickness on the furnace tube or wafer boat is fed back to the system, and the particle count at each wafer loading position is further predicted.

[0176] In summary, in the wafer particle prediction method provided by the embodiment of the present invention, by placing monitoring pieces at the upper, middle and lower ends of the wafer boat, the number of particles on the monitoring pieces is predicted according to the particle behavior law during the maintenance cycle of the furnace tube; and the number of particles on the wafers at different wafer carrying positions of the wafer boat is predicted based on the number of particles on the monitoring piece; and the particle defect rate of each group of wafers is calculated based on the number of chips on the wafer, and the total risk value of each group of wafers at different wafer carrying positions of the wafer boat under different arrangement orders is calculated, and the arrangement order with the lowest total risk value that meets the requirements is selected for operation. In the present invention, based on the particle behavior law during the maintenance cycle, a particle prediction system for furnace tube operation is established, and the particle behavior of each batch of operation batches is effectively predicted. Further, according to the difference in the number of product chips, the furnace tube machine and furnace tube position are reasonably configured for different products, thereby reducing the impact of particles in the low-pressure chemical deposition furnace tube on product yield.

[0177] Furthermore, it should be recognized that although the present invention has been disclosed above with reference to preferred embodiments, the above embodiments are not intended to limit the present invention. Any person skilled in the art can utilize the above disclosed technical content to make many possible changes and modifications to the technical solution of the present invention, or modify it into equivalent embodiments with equivalent variations, without departing from the scope of the technical solution of the present invention. Therefore, any simple modifications, equivalent variations, and modifications made to the above embodiments based on the technical essence of the present invention, without departing from the content of the technical solution of the present invention, shall still fall within the scope of protection of the technical solution of the present invention.

Claims

1. A wafer particle prediction method, characterized in that: include: A furnace tube is provided, wherein a wafer boat of the furnace tube comprises three ends, upper, middle and lower, and a plurality of wafer carrying positions between the three ends, and monitoring pieces are placed at the three ends, respectively; Predicting the number of particles on the monitoring film according to the particle behavior rules during the maintenance period of the furnace tube; And predicting the number of particles on the wafers at different wafer carrying positions according to the number of particles on the monitoring sheet; The particle defect rate of the wafers at different wafer carrying positions is calculated according to the number of chips in different groups of wafers and the number of particles on the wafers at different wafer carrying positions, and the total risk value of all the wafers in each group at different wafer carrying positions under different arrangement orders is calculated, and the arrangement order that meets the requirements and has the lowest total risk value is selected for operation.

2. The wafer particle prediction method according to claim 1, characterized in that: The furnace tube includes a reaction chamber, and the number of particles on the monitoring piece includes the number of particles generated on the monitoring piece predicted based on the film thickness deposited on the surface of the wafer boat and the number of particles generated on the monitoring piece predicted based on the film thickness deposited on the inner wall of the reaction chamber.

3. The wafer particle prediction method according to claim 2, characterized in that: The calculation formula of the number of particles in the monitoring film is: PD n =PDT n +PDB n -Base n =Q n *(M n ) |x-TT n | +R n *(N n ) TB n -y +Base n Among them, n is the nth monitoring piece, PD n is the number of particles in the nth monitoring film, PDT n The number of particles generated on the nth monitoring piece for predicting the deposition film thickness on the inner wall of the reaction chamber, PDB n The number of particles generated on the nth monitoring film for predicting the film thickness deposited on the wafer boat surface, Base n Q is the long-term benchmark particle count at the initial stage of machine maintenance at the nth monitoring piece; n is the maximum number of particles generated by the peeling of the deposited film on the inner wall of the reaction chamber at the nth monitoring piece; TT n M is the deposition film thickness on the inner wall of the reaction chamber when the maximum number of particles at the nth monitoring piece occurs; n R is the influence coefficient of the deposition film thickness of the inner wall of the reaction chamber at the nth monitoring piece on the particles generated by peeling; n TB is the maximum number of particles generated by the peeling of the deposited film on the surface of the wafer boat before the machine maintenance at the nth monitoring piece; n N is the deposition film thickness on the surface of the wafer boat during the machine maintenance at the nth monitoring piece; n is the influence coefficient of the deposited film thickness on the surface of the wafer boat at the nth monitoring piece on the particles generated by peeling; x is the cumulative film thickness of the film on the inner wall of the reaction chamber; y is the cumulative film thickness of the film on the surface of the wafer boat.

4. The wafer particle prediction method according to claim 3, characterized in that: The wafer boat of the furnace tube includes wafer carrying positions 1, 2, ... W arranged in sequence from top to bottom, W is a natural number greater than or equal to 2 and less than or equal to 6, and each wafer carrying position is used to place a group of the wafers; when two wafer carrying positions are arranged on the wafer boat, a first monitoring piece is placed at the top of the first wafer carrying position, a second monitoring piece is placed between the first wafer carrying position and the second wafer carrying position, and a third monitoring piece is placed at the bottom of the second wafer carrying position; When three wafer carrying positions are set on the wafer boat, a first monitoring piece is placed at the top of the first wafer carrying position, a second monitoring piece is placed in the middle of the second wafer carrying position, and a third monitoring piece is placed at the bottom of the third wafer carrying position; when four wafer carrying positions are set on the wafer boat, a first monitoring piece is placed at the top of the first wafer carrying position, a second monitoring piece is placed between the second wafer carrying position and the third wafer carrying position, and a third monitoring piece is placed at the bottom of the fourth wafer carrying position; when five wafer carrying positions are set on the wafer boat, a first monitoring piece is placed at the top of the first wafer carrying position, The second monitoring film is placed in the middle of the third wafer carrying position, and the third monitoring film is placed at the bottom of the fifth wafer carrying position; when six wafer carrying positions are set on the wafer boat, the first monitoring film is placed at the top of the first wafer carrying position, the second monitoring film is placed between the third wafer carrying position and the fourth wafer carrying position, and the third monitoring film is placed at the bottom of the sixth wafer carrying position; the particle defect rate of the wafers at different wafer carrying positions is predicted by the first monitoring film, the second monitoring film and the third monitoring film, and then the total risk value of each group of wafers at different wafer carrying positions under different arrangement orders is calculated.

5. The wafer particle prediction method according to claim 4, characterized in that: When two wafer carrying positions are set on the wafer boat, the average number of particles at the first wafer carrying position and the average number of particles at the second wafer carrying position are calculated as follows: PDP1=(PD1+PD2) / 2 PDP2=(PD2+PD3) / 2 When three carrying positions are set on the wafer boat, the average number of particles at the first wafer carrying position, the average number of particles at the second wafer carrying position, and the average number of particles at the third wafer carrying position are calculated as follows: PDP1=(PD1*2+PD2) / 3 PDP2=PD2 PDP2=(PD2+PD3*2) / 3 When four wafer carrying positions are set on the wafer boat, the average number of particles at the first wafer carrying position, the average number of particles at the second wafer carrying position, the average number of particles at the third wafer carrying position, and the average number of particles at the fourth position are calculated as follows: PDP1=(PD1*3+PD2) / 4 PDP2=(PD1+PD2*3) / 4 PDP3=(PD2*3+PD3) / 4 PDP4=(PD2+PD3*3) / 4 When five wafer carrying positions are set on the wafer boat, the average number of particles at the first wafer carrying position, the average number of particles at the second wafer carrying position, the average number of particles at the third wafer carrying position, the average number of particles at the fourth wafer carrying position, and the average number of particles at the fifth wafer carrying position are calculated as follows: PDP1=(PD1*4+PD2) / 5 PDP2=(PD1*2+PD2*3) / 5 PDP3=PD2 PDP4=(PD2*3+PD3*2) / 5 PDP5=(PD2+PD3*4) / 5 When six wafer carrying positions are set on the wafer boat, the average number of particles at the first wafer carrying position, the average number of particles at the second wafer carrying position, the average number of particles at the third wafer carrying position, the average number of particles at the fourth wafer carrying position, the average number of particles at the fifth wafer carrying position, and the average number of particles at the sixth wafer carrying position are calculated as follows: PDP1=(PD1*5+PD2) / 6 PDP2=(PD1+PD2) / 2 PDP3=(PD1+PD2*5) / 6 PDP4=(PD2*5+PD3) / 6 PDP5=(PD2+PD3) / 2 PDP6=(PD2+PD3*5) / 6 Among them, PDP1 is the average number of particles at the first wafer carrying position, PDP2 is the average number of particles at the second wafer carrying position, PDP3 is the average number of particles at the third wafer carrying position, PDP4 is the average number of particles at the fourth wafer carrying position, PDP5 is the average number of particles at the fifth wafer carrying position, PDP6 is the average number of particles at the sixth wafer carrying position, PD1 is the number of particles of the first monitoring film, PD2 is the number of particles of the second monitoring film, and PD3 is the number of particles of the third monitoring film.

6. The wafer particle prediction method according to claim 5, characterized in that: The particle defect rate of the wafers in a group of the wafers at one of the wafer carrying positions is: the ratio of the average number of particles at the wafer carrying position to the number of chips in the group of the wafers.

7. The wafer particle prediction method according to claim 5, characterized in that: There are multiple arrangement sequences for different wafer carrying positions and different groups of wafers, wherein a method for calculating the total risk value of each group of wafers at different wafer carrying positions under one arrangement sequence includes: When two wafer carrying positions are set on the wafer boat V n (AB)=PDP1 / Dc A +PDP2 / Dc B ; When three wafer carrying positions are set on the wafer boat V n (ABCD)=PDP1 / Dc A +PDP2 / Dc B +PDP3 / Dc C ; When four wafer carrying positions are set on the wafer boat V n (ABCD)=PDP1 / Dc A +PDP2 / Dc B +PDP3 / Dc C +PDP4 / Dc D ; When five wafer carrying positions are set on the wafer boat V n (ABCDE)=PDP1 / Dc A +PDP2 / Dc B +PDP3 / Dc C +PDP4 / Dc D +PDP5 / Dc E ; When six wafer carrying positions are set on the wafer boat V n (ABCDEF)= PDP1 / Dc A +PDP2 / Dc B +PDP3 / Dc C +PDP4 / Dc D +PDP5 / Dc E +PDP6 / Dc F ; Among them, V n It refers to the total risk value of the nth arrangement order, A, B, C, D, E and F are the groups of the wafers, PDP1 is the average number of particles at the first wafer carrying position, PDP2 is the average number of particles at the second wafer carrying position, PDP3 is the average number of particles at the third wafer carrying position, PDP4 is the average number of particles at the fourth wafer carrying position, PDP5 is the average number of particles at the fifth wafer carrying position, PDP6 is the average number of particles at the sixth wafer carrying position, Dc A is the number of chips in wafer group A, Dc B is the number of chips in group B wafers, Dc C is the number of chips in group C wafers, Dc D is the number of chips in group D wafers, Dc E is the number of chips in the E group wafer, Dc F is the number of chips in group F wafers.

8. A wafer particle prediction system, characterized in that: include: A data acquisition unit, wherein the wafer boat of the furnace tube comprises three ends, upper, middle and lower, and a plurality of wafer carrying positions between the three ends, and monitoring pieces are placed at the three ends of the wafer boat, respectively, and the number of particles on the monitoring piece is predicted according to the particle behavior law during the maintenance period of the furnace tube; The calculation unit predicts the number of particles of wafers at different wafer carrying positions according to the number of particles on the monitoring film; calculates the particle defect rate of wafers at different wafer carrying positions according to the number of chips in different groups of wafers and the number of particles of wafers at different wafer carrying positions, calculates the total risk value of each group of wafers at different wafer carrying positions under different arrangement orders, and selects the arrangement order that meets the requirements and has the lowest total risk value to perform the operation.

9. A furnace tube particle risk control method, characterized in that: The wafer particle prediction method according to any one of claims 1 to 7 obtains the total risk value of each group of wafers at different wafer carrying positions under different arrangement orders, and determines whether the particle defect rate of each group of wafers under all arrangement orders exceeds a preset threshold; If not, the wafers whose particle defect rate exceeds a preset threshold are removed, and the arrangement sequence with the smallest total risk value is selected to perform the process.

10. The furnace tube particle risk control method according to claim 8, characterized in that: After the furnace tube performs the process, the accumulated film thickness deposited on the furnace tube or the wafer boat in the process is fed back to the system, and the number of particles at different wafer carrying positions is further predicted.

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