Method and system for monitoring characteristics of thin film

Abstract

The invention relates to a monitoring method and a monitoring system for thin film characteristics. Wherein the thin film is a process thin film manufactured by a target process. The film characteristic monitoring method comprises the following steps: acquiring front pipeline pressure data in a process chamber cleaning process; determining a film characteristic monitoring model according to the front pipeline pressure data; and performing real-time monitoring on the characteristics of the thin film manufactured by the target process according to the thin film characteristic monitoring model. According to the invention, hysteresis-free film characteristic monitoring can be realized, so that the yield of wafer products can be improved, and the cost loss can be effectively avoided.

Description

Technical Field

[0001] The present application relates to the field of semiconductor technology, and in particular to a method and system for monitoring thin film characteristics. Background Art

[0002] Chemical Vapor Deposition (CVD) is an important process for forming thin films in semiconductor manufacturing. The quality of the grown thin films will greatly affect the stability of the semiconductor manufacturing process and product reliability. Therefore, it is very important to monitor the properties of the thin films formed by chemical vapor deposition.

[0003] In the current semiconductor technology field, the method for monitoring the characteristics of thin films deposited by chemical vapor deposition process tools is usually to regularly perform chemical vapor deposition processes on test machine wafers (such as control baffles, i.e., non-product wafers), and then use a measurement tool to measure the resulting product wafers to analyze their film quality, thereby reflecting the stability of the chemical vapor deposition process tool.

[0004] However, the monitoring method of regularly measuring the tester wafer in the related art needs to be carried out according to a certain test cycle (for example, measurement is performed every 4 days or a week, etc.). Therefore, this monitoring method inevitably has a certain lag, and it is difficult to timely feedback the abnormal film characteristics of the wafer product. When the process parameters fed back by the measurement are abnormal, it is very likely that hundreds or even thousands of product wafers have been affected, causing serious cost losses and greatly reducing the wafer product yield. Summary of the invention

[0005] Based on this, the embodiments of the present application provide a method and system for monitoring thin film characteristics, which can realize hysteresis-free thin film characteristic monitoring, thereby helping to improve the yield of wafer products and effectively avoid cost losses.

[0006] In order to achieve the above-mentioned purpose, on the one hand, some embodiments of the present application provide a method for monitoring film properties. The film is a process film manufactured by a target process; the method for monitoring film properties includes: obtaining front-line pipeline pressure data during the process chamber cleaning process; determining a film property monitoring model based on the front-line pipeline pressure data; and monitoring the film properties manufactured by the target process in real time based on the film property monitoring model.

[0007] In some embodiments, determining the film characteristic monitoring model according to the front-line pipeline pressure data includes: determining an initial model based on the front-line pipeline pressure data, and determining the film characteristic monitoring model based on the initial model.

[0008] In some embodiments, determining the initial model based on the front-line pipeline pressure data, and determining the thin film characteristic monitoring model based on the initial model, includes: constructing a front-line pipeline pressure curve based on the front-line pipeline pressure data; determining the initial model according to the front-line pipeline pressure curve; the method for determining the initial model includes iterating the front-line pipeline pressure curve; determining the thin film characteristic monitoring model according to the initial model; the method for determining the thin film characteristic monitoring model includes deriving the initial model.

[0009] In some embodiments, the products and / or by-products generated during the process chamber cleaning process are discharged from the wafer machine through the front-line pipeline; the initial model is used to represent the change in the front-line pipeline pressure with cleaning time; and the thin film characteristic monitoring model is used to represent the rate of change of the front-line pipeline pressure with cleaning time.

[0010] In some embodiments, the thin film characteristics obtained by the target process manufacturing are monitored in real time according to the thin film characteristic monitoring model, and a thin film abnormality warning is issued when the thin film characteristic monitoring model is abnormal, including: determining the front-line pipeline pressure change rate at the target moment according to the thin film characteristic monitoring model; and issuing a thin film abnormality warning when the front-line pipeline pressure change rate exceeds a preset threshold.

[0011] In some embodiments, the front-line pipeline pressure data includes the front-line pipeline pressure of different wafers during the process of cleaning the process chamber after executing the target process; the determining the film characteristic monitoring model according to the front-line pipeline pressure data includes: determining the film characteristic monitoring model of each wafer according to the front-line pipeline pressure data;

[0012] Among them, the real-time monitoring of thin film characteristics according to the thin film characteristic monitoring model and the issuance of thin film abnormality warning when the thin film characteristic monitoring model is abnormal also include: determining the front-line pipeline pressure change rate corresponding to each wafer at the target moment according to the thin film characteristic monitoring model of each wafer; determining the front-line pipeline pressure change rate curve according to the front-line pipeline pressure change rate of different wafers; feeding back the front-line pipeline pressure change rate curve to the statistical process control system to monitor the thin film characteristics of different wafers in real time, and issuing a thin film abnormality warning for the current wafer when the front-line pipeline pressure change rate curve exceeds a preset threshold.

[0013] In some embodiments, after the thin film abnormality warning is performed on the current wafer, the thin film characteristic monitoring method further includes: adjusting the process parameters of the next wafer accordingly according to the abnormality of the thin film characteristic monitoring model of the current wafer.

[0014] On the other hand, the present application also provides a monitoring system for thin film properties according to some embodiments; the thin film is a process thin film manufactured by a target process; the monitoring system for thin film properties includes a data acquisition module, a data processing module and a monitoring module. The data acquisition module is configured to: acquire the front-line pipeline pressure data during the process chamber cleaning process. The data processing module is connected to the data acquisition module; the data processing module is configured to: determine a thin film property monitoring model based on the front-line pipeline pressure data. The monitoring module is connected to the data processing module; the monitoring module is configured to: perform real-time monitoring of the thin film properties manufactured by the target process according to the thin film property monitoring model.

[0015] In some embodiments, the data processing module includes a first determination unit, a second determination unit, and a third determination unit. The first determination unit is connected to the data acquisition module; the first determination unit is configured to: construct a front-line pipeline pressure curve based on the front-line pipeline pressure data. The second determination unit is connected to the first determination unit; the second determination unit is configured to: determine an initial model according to the front-line pipeline pressure curve; the method for determining the initial model includes iterating the front-line pipeline pressure curve. The third determination unit is connected to the second determination unit; the third determination unit is configured to: determine the film characteristic monitoring model according to the initial model; the method for determining the film characteristic monitoring model includes deriving the initial model.

[0016] In some embodiments, the monitoring module includes a fourth determination unit and an early warning unit. The fourth determination unit is connected to the data processing module; the fourth determination unit is configured to: determine the front-line pipeline pressure change rate at the target time according to the membrane characteristic monitoring model. The early warning unit is connected to the fourth determination unit; the early warning unit is configured to: when the front-line pipeline pressure change rate exceeds a preset threshold, issue a membrane abnormality early warning.

[0017] The embodiments of the present application may or at least have the following advantages:

[0018] In the embodiment of the present application, by obtaining the front-line pipeline pressure data during the process of cleaning the process chamber after executing the target process, and determining the film characteristic monitoring model according to the front-line pipeline pressure data, the film characteristics obtained by the target process manufacturing are then monitored in real time based on the film characteristic monitoring model. Among them, since the products and / or by-products generated during the process chamber cleaning process need to be discharged from the wafer machine through the front-line pipeline, the front-line pipeline pressure will be associated with the generation rate of the products and / or by-products during the cleaning process, and the change of the film properties will affect the generation rate of the products and / or by-products during the cleaning process. Therefore, the film characteristic monitoring model in the embodiment of the present application can effectively reflect the actual situation of the film characteristics obtained by the target process manufacturing. In this way, the embodiment of the present application realizes real-time monitoring of the film characteristics of the process film obtained by the target process manufacturing based on the film characteristic monitoring model, and can promptly issue an early warning when a film abnormality problem occurs, so as to realize the film characteristic monitoring without hysteresis, thereby helping to improve the wafer product yield and effectively avoid cost losses.

[0019] The details of one or more embodiments of the present application are set forth in the following drawings and description. Other features, objects, and advantages of the present application will become apparent from the description, drawings, and claims. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0021] Figure 1 A schematic flow chart of a method for monitoring thin film properties provided in some embodiments;

[0022] Figure 2 A flowchart of a monitoring method of step S200 provided in some embodiments;

[0023] Figure 3 A schematic flow chart of another method for monitoring film properties provided in some embodiments;

[0024] Figure 4 A schematic flow chart of another method for monitoring film properties provided in some embodiments;

[0025] Figure 5 A schematic diagram of a front-line pipeline pressure curve provided in some embodiments;

[0026] Figure 6A schematic diagram of a front-line pipeline pressure change rate curve provided in some embodiments;

[0027] Figure 7 A schematic flow chart of a system for monitoring thin film properties provided in some embodiments;

[0028] Figure 8 A schematic flow chart of another system for monitoring film properties provided in some embodiments;

[0029] Fig. 9 The present invention is a schematic flow chart of yet another system for monitoring thin film characteristics provided in some embodiments.

[0030] Description of reference numerals:

[0031] 1-data acquisition module, 2-data processing module, 21-first determination unit, 22-second determination unit, 23-third determination unit, 3-monitoring module, 31-fourth determination unit, 32-early warning unit, SPC-statistical process control system. DETAILED DESCRIPTION

[0032] In order to facilitate understanding of the present application, the present application will be described more fully below with reference to the relevant drawings. The preferred embodiments of the present application are given in the drawings. However, the present application can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the disclosure of the present application more thorough and comprehensive.

[0033] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein in the specification of this application are only for the purpose of describing specific embodiments and are not intended to limit this application.

[0034] It should be understood that when an element or layer is referred to as being "on," "adjacent to," or "connected to" other elements or layers, it may be directly on, adjacent to, connected to, or coupled to other elements or layers, or there may be intervening elements or layers. It should be understood that, although the terms first, second, third, etc. may be used to describe various elements, components, regions, layers, doping types, and / or portions, these elements, components, regions, layers, doping types, and / or portions should not be limited by these terms. These terms are only used to distinguish one element, component, region, layer, doping type, or portion from another element, component, region, layer, doping type, or portion. Therefore, without departing from the teachings of the present application, the first element, component, region, layer, doping type, or portion discussed below may be represented as a second element, component, region, layer, or portion.

[0035] When used herein, the singular forms "a", "an", and "said / the" may also include plural forms, unless the context clearly indicates otherwise. It should also be understood that when the terms "consisting of" and / or "comprising" are used in this specification, the presence of the features, integers, steps, operations, elements and / or parts can be determined, but the presence or addition of one or more other features, integers, steps, operations, elements, parts and / or groups is not excluded. At the same time, when used herein, the term "and / or" includes any and all combinations of the relevant listed items.

[0036] Embodiments of the invention are described herein with reference to cross-sectional views that are schematic representations of idealized embodiments (and intermediate structures) of the present application, such that variations in the shapes shown due to, for example, manufacturing techniques and / or tolerances are anticipated. Embodiments of the present application should not be limited to the specific shapes of the regions shown herein, but include deviations in shapes due to, for example, manufacturing techniques. Therefore, the regions shown in the figures are schematic in nature, their shapes do not represent the actual shapes of the regions of the device, and do not limit the scope of the present application.

[0037] The embodiments of the present application provide a method and system for monitoring thin film characteristics, which can realize hysteresis-free thin film characteristic monitoring, thereby facilitating improving wafer product yield and effectively avoiding cost losses.

[0038] It should be noted that the film is a process film manufactured by the target process.

[0039] In some embodiments, see Figure 1 The method for monitoring film characteristics includes the following steps S100~S300.

[0040] S100, obtaining front-line pipeline pressure data during the process chamber cleaning process.

[0041] S200, determining a film characteristic monitoring model according to front-line pipeline pressure data.

[0042] S300, real-time monitoring of the film characteristics obtained by the target process according to the film characteristics monitoring model.

[0043] For example, the film properties include, but are not limited to, the film refractive index, the film density and / or the film internal stress.

[0044] In the embodiment of the present application, by obtaining the front-line pipeline pressure data during the process of cleaning the process chamber after executing the target process, and determining the film characteristic monitoring model according to the front-line pipeline pressure data, the film characteristics obtained by the target process manufacturing are then monitored in real time based on the film characteristic monitoring model. Among them, since the products and / or by-products generated during the process chamber cleaning process need to be discharged from the wafer machine through the front-line pipeline, the front-line pipeline pressure will be associated with the generation rate of the products and / or by-products during the cleaning process, and the change of the film properties will affect the generation rate of the products and / or by-products during the cleaning process. Therefore, the film characteristic monitoring model in the embodiment of the present application can effectively reflect the actual situation of the film characteristics obtained by the target process manufacturing. In this way, the embodiment of the present application realizes real-time monitoring of the film characteristics of the process film obtained by the target process manufacturing based on the film characteristic monitoring model, and can promptly issue an early warning when a film abnormality problem occurs, so as to realize the film characteristic monitoring without hysteresis, thereby helping to improve the wafer product yield and effectively avoid cost losses.

[0045] In some examples, the thin film properties include a film refractive index, a film density, and / or a film internal stress.

[0046] In some embodiments, step S200 includes the following step S210.

[0047] S210, determining an initial model based on the front-line pipeline pressure data, and determining a film characteristic monitoring model based on the initial model.

[0048] In some embodiments, see Figure 2 , step S210 includes the following steps S211~S213.

[0049] S211, constructing a front-line pipeline pressure curve based on the front-line pipeline pressure data.

[0050] S212, determining an initial model according to the front-line pipeline pressure curve; the method for determining the initial model includes iterating the front-line pipeline pressure curve.

[0051] S213, determining a thin film characteristic monitoring model according to the initial model; the method for determining the thin film characteristic monitoring model includes deriving the initial model.

[0052] In some embodiments, the products and / or by-products generated during the process chamber cleaning process are discharged from the wafer machine through the front-line pipeline; the initial model is used to represent the change in the front-line pipeline pressure with the cleaning time; and the thin film characteristic monitoring model is used to represent the rate of change of the front-line pipeline pressure with the cleaning time.

[0053] In an embodiment of the present application, a numerical method is used to iterate the front-line pipeline pressure curve to determine an initial model for representing the change of the front-line pipeline pressure with the cleaning time, and the initial model is differentiated to determine a thin film characteristic monitoring model for representing the rate of change of the front-line pipeline pressure with the cleaning time; in this way, a mapping relationship is established to determine the thin film characteristic monitoring model, so that the determination of the thin film characteristic monitoring model is more accurate, and hysteresis-free thin film characteristic monitoring is achieved, which is beneficial to improving the yield of wafer products.

[0054] In some embodiments, see Figure 3 , step S300 includes the following steps S311~S312.

[0055] S311, determining the front-line pipeline pressure change rate at the target time according to the film characteristic monitoring model.

[0056] S312, when the front-line pipeline pressure change rate exceeds a preset threshold, a membrane abnormality warning is issued.

[0057] In some embodiments, see Figure 4 The front-line pipeline pressure data includes the front-line pipeline pressure of different wafers during the process chamber cleaning process after executing the target process; step S200 includes the following step S220.

[0058] S220, determining a film characteristic monitoring model for each wafer according to the front-line pipeline pressure data.

[0059] Accordingly, please continue to refer to Figure 4 , step S300 also includes the following steps S321~S323.

[0060] S321, determining the front-line pipeline pressure change rate corresponding to each wafer at the target time according to the thin film characteristic monitoring model of each wafer.

[0061] S322, determining a front-line pipeline pressure change rate curve according to the front-line pipeline pressure change rates of different wafers.

[0062] S323, feed back the front-line pipeline pressure change rate curve to the statistical process control system to monitor the film characteristics of different wafers in real time, and when the front-line pipeline pressure change rate curve exceeds a preset threshold, issue a film abnormality warning for the current wafer.

[0063] In an embodiment of the present application, by feeding back the front-line pipeline pressure change rate curve to a statistical process control system (Statistical Process Control, SPC for short), the operator only needs to establish a mapping relationship through the process control system to achieve automatic monitoring of film properties, which is conducive to the automatic adjustment of process parameters and realizes hysteresis-free film property monitoring.

[0064] In some embodiments, after performing a thin film abnormality warning on the current wafer in step S323, the thin film property monitoring method further includes the following step S400.

[0065] S400, adjusting the process parameters of the next wafer accordingly according to the abnormality of the thin film characteristic monitoring model of the current wafer.

[0066] In an embodiment of the present application, by determining the thin film characteristic monitoring model of each wafer in a wafer batch, it is possible to timely issue a thin film abnormality warning for the current wafer, thereby making corresponding adjustments to the process parameters of the next wafer according to the abnormality of the thin film characteristic monitoring model of the current wafer; in this way, it is possible to accurately monitor the abnormal film characteristics of each wafer in the wafer batch, and correct the process parameters in time, so that the abnormal film characteristics of the current wafer will not affect the next wafer, thereby realizing non-hysteresis thin film characteristic monitoring, which is beneficial to improving the wafer product yield and effectively avoiding cost losses.

[0067] It should be understood that although Figure 1~Figure 4 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, Figure 1~Figure 4 At least part of the steps may include multiple steps or multiple stages. These steps or stages are not necessarily performed at the same time, but can be performed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed in turn or alternately with other steps or at least part of the steps or stages in other steps.

[0068] In order to more clearly illustrate the monitoring method of the film characteristics in some of the above embodiments, the following embodiments are combined with Figure 5~Figure 6 Understand.

[0069] It should be noted that the film is a process film manufactured by the target process.

[0070] In some embodiments, the method for monitoring film characteristics includes the following steps S100 - S300 .

[0071] In step S100 , foreline pressure data (foreline pressure) during cleaning of a process chamber is obtained.

[0072] For example, the target process includes but is not limited to a deposition process; the target process may be, for example, a chemical vapor deposition (CVD) process.

[0073] For example, the process chamber may be a reaction chamber of a chemical vapor deposition (CVD) machine.

[0074] For example, cleaning of the process chamber may include cleaning the sidewalls, showerheads, and / or support bases of the process chamber to remove film residues attached thereto.

[0075] It should be noted that the products and / or by-products generated during the process chamber cleaning process are discharged from the wafer machine through the front-line pipeline.

[0076] In step S200, a film characteristic monitoring model is determined according to the front-line pipeline pressure data.

[0077] In some embodiments, step S200 includes the following step S210.

[0078] In step S210, an initial model is determined based on the front-line pipeline pressure data, and a film characteristic monitoring model is determined based on the initial model.

[0079] In some embodiments, step S210 includes the following steps S211 to S213.

[0080] In step S211, refer to Figure 5 , based on the front-line pipeline pressure data, construct the front-line pipeline pressure curve.

[0081] For example, please continue to see Figure 5 , the front-line pipeline pressure curve can be used to represent the change of the front-line pipeline pressure (P) with the cleaning time (T).

[0082] For example, the unit of the front-line pipeline pressure (P) may be, for example, megapascal (MPa); the unit of the cleaning time may be, for example, second (s).

[0083] For example, the value of the front-line pipeline pressure may fluctuate within a range of 0.1 MPa to 0.5 MPa.

[0084] In step S212, an initial model is determined according to the front-line pipeline pressure curve; illustratively, the method for determining the initial model includes iterating the front-line pipeline pressure curve.

[0085] For example, the initial model may be a polynomial function; the initial model may be, for example:

[0086] ;

[0087] in, , , … , is the first coefficient.

[0088] It should be noted that the first coefficient is determined by iterating the front-line pipeline pressure curve.

[0089] In some examples, an initial model is used to represent the change in frontline line pressure over purge time.

[0090] In step S213, a thin film characteristic monitoring model is determined according to the initial model; illustratively, the method for determining the thin film characteristic monitoring model includes deriving the initial model.

[0091] For example, the film characteristic monitoring model may be a first-order derivative function of a polynomial function; the film characteristic monitoring model may be, for example:

[0092] ;

[0093] in, , , … , is the first coefficient.

[0094] In some examples, a membrane property monitoring model is used to represent the rate of change of the frontline line pressure with cleaning time.

[0095] In step S300, the film characteristics obtained by the target process are monitored in real time through the film characteristic monitoring model, and a film abnormality warning is issued when the film characteristic monitoring model is abnormal.

[0096] For example, the film properties include, but are not limited to, the film refractive index, the film density and / or the film internal stress.

[0097] In some embodiments, step S300 includes the following steps S311 - S312 .

[0098] In step S311, refer to Figure 5 ,According to the film characteristic monitoring model, the front-line pipeline pressure change rate at the target time (T0) is determined.

[0099] For example, the target time (T0) may be 10 s, 20 s, 30 s, 40 s, 50 s, 60 s, 70 s, 80 s, 90 s, or 100 s, etc.

[0100] For example, the front-line pipeline pressure change rate at the target moment can be determined based on the front-line pipeline pressure at the target moment (T=T0) and the front-line pipeline pressure at the previous moment (T=T0-1); the front-line pipeline pressure change rate at the target moment can, for example, be the ratio between the change in the front-line pipeline pressure between the target moment (T=T0) and the previous moment (T=T0-1) and the front-line pipeline pressure at the previous moment (T=T0-1).

[0101] In step S312, when the front-line pipeline pressure change rate exceeds a preset threshold, a membrane abnormality warning is issued.

[0102] For example, the preset threshold may be a preset value set based on past experience.

[0103] In some examples, the preset threshold includes an upper threshold and a lower threshold; step S312 can also be: when the front-line pipeline pressure change rate is greater than the upper threshold or the front-line pipeline pressure change rate is less than the lower threshold, a membrane abnormality warning is issued.

[0104] It should be noted that the upper threshold and the lower threshold can be set according to the value of the standard change rate; wherein the upper threshold is greater than the standard change rate, and the lower threshold is less than the standard change rate.

[0105] For example, taking the standard change rate as 30% as an example; the upper threshold value may be, for example, 35%, 40%, 45%, 50% or 55%, etc., and the lower threshold value may be, for example, 25%, 20%, 15%, 10% or 5%, etc.

[0106] In some embodiments, the frontline pressure data includes frontline pressures of different wafers during a process chamber cleaning process after performing a target process.

[0107] By way of example, the different wafers may be, for example, a plurality of wafers in the same wafer batch.

[0108] In some examples, step S200 includes the following step S220.

[0109] In step S220 , a thin film characteristic monitoring model of each wafer is correspondingly determined according to the front-line pipeline pressure data.

[0110] Accordingly, step S300 also includes the following steps S321 to S323.

[0111] In step S321 , the front-line pipeline pressure change rate at the target time corresponding to each wafer is determined respectively according to the thin film characteristic monitoring model of each wafer.

[0112] For example, the target time (T0) may be 10 s, 20 s, 30 s, 40 s, 50 s, 60 s, 70 s, 80 s, 90 s, or 100 s, etc.

[0113] In step S322, refer to Figure 6 , according to the front-line pipeline pressure change rate of different wafers, the front-line pipeline pressure change rate curve is determined.

[0114] In step S323, the front-line pipeline pressure change rate curve is fed back to the statistical process control system (Statistical Process Control, SPC) to monitor the film characteristics of different wafers in real time. When the front-line pipeline pressure change rate curve exceeds a preset threshold, a film abnormality warning is issued for the current wafer.

[0115] In some embodiments, after performing a thin film abnormality warning on the current wafer in step S323, the thin film property monitoring method further includes the following step S400.

[0116] In step S400, according to the abnormality of the thin film characteristic monitoring model of the current wafer, the process parameters of the next wafer are adjusted accordingly.

[0117] By way of example, the process parameters include, but are not limited to, deposition temperature, deposition gas flow rate, precursor gas concentration, deposition time, and the like.

[0118] The present application also provides a monitoring system for thin film properties according to some embodiments, and the monitoring system for thin film properties can be used to execute the monitoring methods for thin film properties in some of the above embodiments. The monitoring system for thin film properties also has the technical advantages of the above-mentioned monitoring methods for thin film properties. It should be noted that for the parts that are the same or corresponding to the above embodiments, reference can be made to the corresponding descriptions of the above embodiments, and will not be described in detail below.

[0119] It should be noted that the film is a process film manufactured by the target process.

[0120] In some embodiments, see Figure 7 The monitoring system of film characteristics includes a data acquisition module 1, a data processing module 2 and a monitoring module 3. The data acquisition module 1 is configured to obtain the front-line pipeline pressure data during the process chamber cleaning process. The data processing module 2 is connected to the data acquisition module 1; the data processing module 2 is configured to determine the film characteristic monitoring model according to the front-line pipeline pressure data. The monitoring module 3 is connected to the data processing module 2; the monitoring module 3 is configured to monitor the film characteristics obtained by the target process in real time according to the film characteristic monitoring model.

[0121] It should be noted that the products and / or by-products generated during the process chamber cleaning process are discharged from the wafer machine through the front-line pipeline.

[0122] In the embodiment of the present application, the front-line pipeline pressure data in the process of cleaning the process chamber after executing the target process is obtained by the data acquisition module 1, and the film characteristic monitoring model is determined according to the front-line pipeline pressure data by the data processing module 2, and then the film characteristics obtained by the target process are monitored in real time by the monitoring module 3 based on the film characteristic monitoring model. Among them, since the products and / or by-products generated in the process chamber cleaning process need to be discharged from the wafer machine through the front-line pipeline, the front-line pipeline pressure will be associated with the generation rate of the products and / or by-products in the cleaning process, and the change of the film properties will affect the generation rate of the products and / or by-products in the cleaning process. Therefore, the film characteristic monitoring model in the embodiment of the present application can effectively reflect the actual situation of the film characteristics obtained by the target process. In this way, the embodiment of the present application realizes real-time monitoring of the film characteristics of the process film obtained by the target process based on the film characteristic monitoring model, and can timely warn when abnormal film problems occur, so as to realize the film characteristic monitoring without hysteresis, which is conducive to improving the yield of wafer products and effectively avoiding cost losses.

[0123] In some embodiments, see Figure 8 , the data processing module 2 includes a first determination unit 21, a second determination unit 22 and a third determination unit 23. The first determination unit 21 is connected to the data acquisition module 1; the first determination unit 21 is configured to: construct a front-line pipeline pressure curve based on the front-line pipeline pressure data. The second determination unit 22 is connected to the first determination unit 21; the second determination unit 22 is configured to: determine an initial model according to the front-line pipeline pressure curve; the method for determining the initial model includes iterating the front-line pipeline pressure curve. The third determination unit 23 is connected to the second determination unit 22; the third determination unit 23 is configured to: determine a film characteristic monitoring model according to the initial model; the method for determining the film characteristic monitoring model includes deriving the initial model.

[0124] In some embodiments, see Fig. 9 The monitoring module 3 includes a fourth determination unit 31 and an early warning unit 32. The fourth determination unit 31 is connected to the data processing module 2; the fourth determination unit 31 is configured to: determine the front-line pipeline pressure change rate at the target time according to the membrane characteristic monitoring model. The early warning unit 32 is connected to the fourth determination unit 31; the early warning unit 32 is configured to: when the front-line pipeline pressure change rate exceeds a preset threshold, issue a membrane abnormality early warning.

[0125] In some embodiments, the frontline pressure data includes frontline pressures of different wafers during a process chamber cleaning process after performing a target process.

[0126] In some examples, the data processing module 2 is further configured to: determine a thin film characteristic monitoring model for each wafer according to the front-line pipeline pressure data.

[0127] In some examples, the fourth determination unit 31 is further configured to: determine the front-line pipeline pressure change rate corresponding to each wafer at the target moment according to the thin film characteristic monitoring model of each wafer; and determine the front-line pipeline pressure change rate curve according to the front-line pipeline pressure change rates of different wafers.

[0128] For some examples, see Fig. 9 The early warning unit 32 is also connected to the statistical process control system SPC; the early warning unit 32 is also configured to: feed back the front-line pipeline pressure change rate curve to the statistical process control system to monitor the film characteristics of different wafers in real time, and when the front-line pipeline pressure change rate curve exceeds a preset threshold, issue a film abnormality early warning for the current wafer.

[0129] It should be noted that after the early warning unit 32 issues a thin film abnormality early warning for the current wafer, the operator can adjust the process parameters of the next wafer accordingly based on the abnormality of the thin film characteristic monitoring model of the current wafer. In this way, the abnormal film characteristics of each wafer in the wafer batch can be accurately monitored, and the process parameters can be corrected in time, so that the abnormal film characteristics of the current wafer will not affect the next wafer, thereby realizing non-hysteresis thin film characteristic monitoring, which is conducive to improving the wafer product yield and effectively avoiding cost losses.

[0130] In the description of this specification, the description with reference to the terms "some embodiments", "some examples", "exemplarily", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic descriptions of the above terms do not necessarily refer to the same embodiment or example.

[0131] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0132] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application.

Claims

1. A method for monitoring thin film properties, characterized in that: The film is a process film manufactured by a target process; the monitoring method comprises: Obtain front-line pipeline pressure data during process chamber cleaning; Determining a film characteristic monitoring model according to the front-line pipeline pressure data; The film properties of the process film obtained by the target process are monitored in real time according to the film property monitoring model.

2. The method for monitoring thin film properties according to claim 1, characterized in that: Determining the film characteristic monitoring model according to the front-line pipeline pressure data includes: An initial model is determined based on the front-line pipeline pressure data, and the film characteristic monitoring model is determined based on the initial model.

3. The method for monitoring thin film properties according to claim 2, characterized in that: The determining of the initial model based on the front-line pipeline pressure data, and determining the film characteristic monitoring model based on the initial model, comprises: Based on the front-line pipeline pressure data, construct a front-line pipeline pressure curve; Determine an initial model according to the front-line pipeline pressure curve; the method for determining the initial model includes iterating the front-line pipeline pressure curve; The thin film characteristic monitoring model is determined according to the initial model; the method for determining the thin film characteristic monitoring model includes deriving the initial model.

4. The method for monitoring thin film properties according to claim 3, characterized in that: The products and / or by-products generated during the process chamber cleaning process are discharged from the wafer machine through the front-line pipeline; the initial model is used to represent the change in the front-line pipeline pressure with the cleaning time; the thin film characteristic monitoring model is used to represent the change rate of the front-line pipeline pressure with the cleaning time.

5. The method for monitoring thin film properties according to claim 1, characterized in that: The real-time monitoring of the film properties obtained by the target process according to the film property monitoring model includes: Determining the front-line pipeline pressure change rate at a target time according to the film characteristic monitoring model; When the front-line pipeline pressure change rate exceeds a preset threshold, a membrane abnormality warning is issued.

6. The method for monitoring thin film properties according to claim 5, characterized in that: The front-line pipeline pressure data includes the front-line pipeline pressure during the process of cleaning the process chamber after performing the target process on different wafers; Determining the film characteristic monitoring model according to the front-line pipeline pressure data includes: Determining a film characteristic monitoring model for each wafer according to the front-line pipeline pressure data; Wherein, the real-time monitoring of the film properties according to the film property monitoring model further includes: Determining the front-line pipeline pressure change rate at the target time corresponding to each wafer respectively according to the film characteristic monitoring model of each wafer; Determining a front-line pipeline pressure change rate curve according to the front-line pipeline pressure change rates of different wafers; The front-line pipeline pressure change rate curve is fed back to the statistical process control system to monitor the film characteristics of different wafers in real time. When the front-line pipeline pressure change rate curve exceeds a preset threshold, a film abnormality warning is issued for the current wafer.

7. The method for monitoring thin film properties according to claim 6, characterized in that: After the film abnormality warning is performed on the current wafer, the film property monitoring method further includes: According to the abnormal situation of the film characteristic monitoring model of the current wafer, the process parameters of the next wafer are adjusted accordingly.

8. A monitoring system for thin film properties, characterized in that: The film is a process film manufactured by a target process; the monitoring system comprises: The data acquisition module is configured to: acquire front-line pipeline pressure data during the process chamber cleaning process; A data processing module, connected to the data acquisition module, is configured to: determine a film characteristic monitoring model according to the front-line pipeline pressure data; The monitoring module is connected to the data processing module and is configured to: perform real-time monitoring of the film characteristics obtained by the target process according to the film characteristics monitoring model.

9. The thin film property monitoring system according to claim 8, characterized in that: The data processing module comprises: A first determination unit, connected to the data acquisition module, is configured to: construct a front-line pipeline pressure curve based on the front-line pipeline pressure data; A second determining unit is connected to the first determining unit and is configured to: determine an initial model according to the front-line pipeline pressure curve; the method for determining the initial model includes iterating the front-line pipeline pressure curve; The third determination unit is connected to the second determination unit and is configured to: determine the thin film characteristic monitoring model according to the initial model; the determination method of the thin film characteristic monitoring model includes deriving the initial model.

10. The thin film property monitoring system according to claim 8, characterized in that: The monitoring module comprises: A fourth determination unit, connected to the data processing module, is configured to: determine the front-line pipeline pressure change rate at a target time according to the film characteristic monitoring model; The early warning unit is connected to the fourth determination unit and is configured to: when the pressure change rate of the front-line pipeline exceeds a preset threshold, issue a membrane abnormality early warning.

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