EP1200982A1 - Method for monitoring a production process for preparing a substrate in semiconductor manufacturing - Google Patents

Abstract

The invention relates to a method for monitoring a production process, whereby several models are used for detecting a finish point. The results of said model are subsequently compared with one another and the best model therefrom is used in other productions processes for detecting a finish point. The inventive method provides the advantage that process changes resulting from chamber contamination or sensor drift are compensated for by selecting the best model thereby ensuring reliable finish point detection even in case of unfavorable process conditions.

Description

description

Method for monitoring a manufacturing process for processing a substrate in semiconductor manufacturing

The invention is in the field of semiconductor technology and relates to a method for monitoring a manufacturing process for processing a substrate in semiconductor manufacturing.

A large number of manufacturing processes are used in the production and processing of semiconductor substrates to form semiconductor circuits integrated therein. Deposition processes and etching processes for structuring layers applied to a substrate may be mentioned here as examples. These manufacturing processes must always be monitored because unnoticed because of their complexity disturbances or poorly adapted to process conditions can cause feh ^¬ lerhaft manufactured semiconductor circuits. In order to be able to carry out this monitoring efficiently, there is a general desire to characterize the manufacturing process by real-time analysis of certain measured variables determined during the manufacturing process in order to be able to intervene in a regulating manner if necessary.

Possible methods for checking manufacturing processes are known, for example, from US Pat. No. 5,877,032. A method for determining the end point of a plasma etching process is described therein, in which the detected optical emission of the plasma is used to determine the end point. The background to this approach is the fact that, in the case of etching processes, a layer located on a substrate is etched through, thereby exposing the underlying substrate. The interaction of the etching gas with the exposed substrate can be detected spectroscopically as a change in the emission spectrum of the plasma. This change is according to US 5,877,032 with a variety of predetermined reference curves are compared and the comparison is used to conclude the end point of the plasma etching process.

A method for determining the end point of a plasma etching process is also known from US Pat. No. 5,739,051. In this case, the optical emission of the plasma is also used to determine the end point, emission lines which are characteristic of the interaction of the etching gas with the substrate being used for the evaluation.

However, it is very often difficult to extract the measurement variable characteristic of the etching process from the large number of available spectra or also from other measurement quantities. A method based on the so-called main component analysis is therefore proposed according to US Pat. No. 5,658,423, in which the temporal development of the entire emission spectrum of approximately 240 to 600 nanometers is used for the end point analysis. The main component analysis reduces the amount of data to a few so-called basic patterns and uses their temporal development for the detection of the end point. As a result, the detection of the end point is no longer based on the evaluation of a single emission wavelength but on the change in the entire available spectrum. In principle, however, this approach also requires the provision of reference values for comparison with the currently measured variables.

In particular, US 5,737,496 attempts to circumvent the last-mentioned problem by using a neural network. The neural network is trained on the basis of a large number of determined measured variables, so that it can subsequently be used for decision-making with regard to the end point recognition. However, it has been shown that neural networks often learn wrong signals and patterns, so that misinterpretation can occur. An incorrect training of the neural network arises for example, by changing the emission spectra due to signs of aging in the sensors or chamber contamination. A so-called virtual sensor system is therefore proposed according to US Pat. No. 5,864,773, in which these changes are taken into account before the actual evaluation of the measured variables. This is to create a virtual sensor that is free of chamber-specific or process-specific error effects. Since the experience of the operating personnel must also be used here, unexpected errors and changes cannot be automatically taken into account.

It is therefore an object of the present invention to provide a method for monitoring a manufacturing process for processing a substrate in semiconductor production, which enables the manufacturing process to be monitored safely and as error-free as possible and is used in particular to determine the end point of the manufacturing process.

This invention is achieved by a method according to claim 1.

According to the invention, a method for monitoring a manufacturing process for processing a substrate in semiconductor manufacturing is provided, which has the following steps:

Specification of a first model for determining the end point of the production process, which is defined by an algorithm, by at least one predetermined measurement variable that can be determined during the production process and by an abort criterion, the algorithm delivering a decision variable when applied to the determined measurement variable that used to determine the end point of the manufacturing process when compared with the termination criterion; Performing the manufacturing process in a suitable chamber, a substrate to be treated being introduced into the chamber and processed therein; Determining the measured variable predetermined by the first model during the manufacturing process;

Applying the algorithm of the first model to the determined measured variable and determining the decision variable; Comparing the decision size with the termination criterion specified by the first model, the manufacturing process being terminated when it is fulfilled;

Use of a second model for the comparative Bestim ^¬ mung of the end point of this manufacturing process, which the also by an algorithm, by at least a predetermined, during the manufacturing process ermittel- bare variable and is defined by a termination criterion, wherein the second model for determining the endpoint of a Manufacturing process following subsequent manufacturing process is used, provided that the end point is determined by the second model with greater significance than with the first model.

In the method according to the invention, a first model is initially specified. This model is determined in particular by an algorithm, by the selection of at least one predetermined measurement variable that can be determined during the manufacturing process and by an abort criterion. The measured variable can be, for example, the intensity of the optical emission of the plasma at a wavelength predetermined by the model, the pressure, temperature and other variables that can be determined during the manufacturing process. The measured variable is preferably determined by means of a sensor provided on the chamber and fed to a data processing system.

The algorithm specified by the model is applied to the measured variable determined during the manufacturing process and provides a decision variable. To the X tn υ G 1

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In the following, the invention is described using an exemplary embodiment and is shown chemically in the accompanying figures.

FIG. 1 shows individual method steps for determining the end point of a plasma process,

FIG. 2 shows the selection of a suitable model for determining the end point,

3 a and b show an insulation layer on a substrate with contact holes of different depths to be introduced therein,

FIG. 4 shows the standardized spectrum of an oxide etching process at different times,

FIG. 5 shows the time course of an emission line of this oxide etching process,

FIG. 6 shows a selected emission line of this oxide etching process for determining the end point,

Figure 7 shows the changed emission line due to chamber contamination,

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should be used. In the present exemplary embodiment, the first model is initially used in the plasma process, even if the second model has determined the end point with a higher significance. But then the endpoint is used in a subsequent plasma process the second model to ^¬ He mediation.

Advantage of this approach is to determine the end ^¬ punkts with little variation, so that the etching processes in WE sentlichen can be made with the same period of time. However, if longer etching times result due to contamination, these are taken into account by the second model, since this is assigned a different emission wavelength, for example, in which the changes are registered and manifested.

The model selection will be deepened in the following on Figure 2. Basically, more than just two models for endpoint determination can be specified. It makes sense to start with a single model for endpoint detection of the current one

To use plasma process. The other models are then used to compare the end point. It is also possible to use data records from previous plasma processes for model evaluation in order to find out which model is the most robust against process changes. The model evaluation can either take place parallel to the end point detection of the first model, or can follow after the plasma process has ended. Thus, according to the invention, in addition to monitoring the plasma process and determining the end point, further monitoring is provided such that the models used for determining the end point are continuously checked for their suitability. ^This ensures that reliable models are always used.

The invention is to be deepened in the following using a specific exemplary embodiment. For this purpose, FIGS. 3a GX 1 1 Φ

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The y-axis shows the percentage change in the wavelength intensities between main and over etch. Fig. 4 illustrates that the maximum change for this process is 918 nm. The course of this wavelength (918 nm) is shown in FIG. 5. This example demonstrates how the "best" wavelength can be found by comparing the main and over etch curves.

Over etch is usually understood to mean an extension of the etching time determined (main etch, i.e. the time for etching through the silicon oxide layer) in order to compensate for possible fluctuations in the etching rate over the substrate.

It can be clearly seen in FIG. 4 that there is a maximum change in the signal swing at about 918 nm.

The time course of the emission wavelength at 918 nm is shown in FIG. 5. It can also be seen here that there is a sharp drop in intensity which can be used for the detection of the end point.

However, another line, namely the so-called CN line at 378 nm, was used for the detection in the contact hole etching of the silicon oxide layer 105 of the end point. This is shown in Figure 6. Two local maxima are clearly recognizable, the first maximum being associated with the flatter contact hole and the second maximum with the deeper contact hole in the silicon oxide layer 105. The maxima, ie the change in the intensity of the CN line, is due to an interaction of the etching gas with the respectively exposed materials which are located at the bottom of the contact holes. The end point of the plasma etching process can be determined in particular from the position of the second maximum. After the end point has been reached, the etching process is preferably continued for a predetermined time (over etch) in order to compensate for fluctuations in the local etching rate. These fluctuations are expressed, for example, in relatively broad and flat 1 1 G

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End point as recognized. Of course, it is also possible to compare the currently determined measurement curve with several model curves in order to counteract a drift of the measurement curve. The end point is then determined by the fact that the currently measured measurement curve reaches a predetermined section in the model course assigned to it. Graphical derivations can also be assigned to the threshold analysis.

In contrast, threshold-free analyzes form the second category, which is characterized, for example, by the recognition of zero crossings, maxima and turning points.

Claims

claims

1. A method for monitoring a manufacturing process for processing a substrate in semiconductor production, comprising the steps:

Specification of a first model for determining the end point of the production process, which is defined by an algorithm, by at least one predetermined measurement variable that can be determined during the production process and by an abort criterion, the algorithm delivering a decision variable when applied to the measurement variable ascertained used to determine the end point of the manufacturing process when compared to the termination criterion; Performing the manufacturing process in a suitable chamber, a substrate to be treated being introduced into the chamber and processed therein; Determining the measurement variable predetermined by the first model during the manufacturing process; - Applying the algorithm of the first model to the determined measured variable and determining the decision variable; Comparing the decision size with the termination criterion specified by the first model, the manufacturing process being terminated when it is fulfilled; - Use of a second model for the comparative determination of the end point of this manufacturing process, which is also defined by an algorithm, by at least one predetermined measured variable that can be determined during the manufacturing process and by an abort criterion, the second model for determining the end point of a further one following the manufacturing process Manufacturing process is used, provided that the end point is determined by the second model with greater significance than with the first model.

2. The method according to claim 1, characterized in that is used in the further manufacturing process of the second model and for the comparative determination of its end point a third model, which also by a Algo ^¬ algorithm, by at least a predetermined, during Her ^¬ provisioning process detectable measurand and is defined by a ^¬ From failure criterion, the third model for the determination of the end point of subsequent Herstellungspro- processes is used, the determination of the endpoint provided by the third model having higher significance than the second model was carried out.

3. The method according to claim 1 or 2, characterized in that the significance of the determination of the end point is determined by comparing the measured variables of the individual models.

4. The method according to claim 1 or 2, characterized in that the significance of the determination of the end point is determined by comparing the decision variables determined by the algorithms of the respective models.

5. The method according to claim 4, characterized in that the determined decision variables are first compared with their assigned termination criteria and the significance is determined from the result thus obtained.

6. The method according to any one of the preceding claims, characterized in that the measured variables determined are stored.

7. The method according to any one of the preceding claims, characterized in that stored variables from the manufacturing process preceding manufacturing processes are used to determine the significance of the individual models.

8. The method according to any one of the preceding claims, characterized in that at least one sensor is arranged on the chamber, which is used to determine the respective measured variable.

9. The method according to any one of the preceding claims, characterized in that the algorithms of the models used determine the position of a local maximum, the local gradient or the point of inflection of a curve representing the temporal development of the measured variable and thereby deliver the decision variable.

10. The method according to any one of the preceding claims, characterized in that the models differ at least in the predetermined measured variable or the predetermined algorithm.

11. Procedure for monitoring a plasma process with the steps:

Specification of a first model for determining the end point of the plasma process, which is based on the intensity of at least one predetermined emission wavelength of the .alpha

Plasma and is defined by an abort criterion, the algorithm, when applied to the determined measured variable, delivers a decision variable which, when compared with the abort criterion, serves to determine the end point of the plasma process;

Performing the plasma process using a plasma-excited gas in a plasma chamber, one being treating substrate is introduced into the plasma chamber and there interacts with the plasma-excited gas;

Determining the measured variable predetermined by the first model during the plasma process;

Applying the algorithm of the first model to the determined measured variable and determining the decision variable; Comparing the decision size with the termination criterion specified by the first model, the plasma process being terminated when it is fulfilled;

Use of a second model for comparative determination of the end point of this plasma process, which is also defined by an algorithm, by at least one predetermined measured variable that can be determined during the plasma process based on the intensity of at least one predetermined emission wavelength of the plasma and by an abort criterion, the second model for the determination of the end point of a further plasma process following the plasma process is used, provided the determination of the end point was carried out with greater significance than with the first model by the second model.

12. The method according to claim 11, characterized in that in the further plasma process the second model and a third model is used for comparative determination of its end point, which is also based on an algorithm, by at least one predetermined measurable variable which can be determined during the plasma process the intensity of at least one predetermined emission wavelength of the plasma and is defined by an abort criterion, the third model being used for the determination of the end point of subsequent plasma processes, provided that the end point was determined by the third model with greater significance than with the second model.

13. The method according to claim 11 or 12, characterized in that the significance of the determination of the end point is determined by comparing the temporal development of the measured variables on the basis of the predetermined emission wavelengths of the individual models.

14. The method according to any one of claims 11 to 13, characterized in that the significance of the determination of the end point is determined by comparing the decision variables determined by the algorithms of the respective models.

15. The method according to claim 14, characterized in that the determined decision variables are first compared with their assigned termination criteria and the significance is determined from the result thus obtained.

16. The method according to any one of claims 11 to 15, characterized in that the intensity of a plurality of emission wavelengths of the plasma is measured during the plasma process, these are used as measured variables and are stored.

17. The method according to any one of claims 11 to 16, characterized in that the measured variables of the plasma processes on a ge ^¬ common emission wavelength are compared and from a measure of the contamination of the plasma chamber is determined based.

18. The method according to any one of claims 11 to 17, characterized in that the plasma process is a plasma etching process and the plasma-excited gas is a dry etching gas with which at least parts of the substrate are etched.

19. The method according to claim 18, characterized in that the substrate has an insulation layer into which contact holes are etched by means of the plasma etching process.

20. The method according to claim 19, characterized in that the insulation layer consists of silicon oxide.

21. The method according to any one of claims 19 or 20, characterized in that contact holes are etched with different depths in the insulation layer.

22. The method according to any one of claims 11 to 21, characterized in that a rotating plasma is used in the plasma process.

23. The method according to any one of claims 11 to 22, characterized in that the determination of the measured variable comprises averaging over a predetermined period.

24. The method according to any one of claims 22 to 23, characterized in that the predetermined period corresponds to at least one orbital period of the rotating plasma.

25. The method according to any one of claims 11 to 24, characterized in that the algorithms of the models used determine the position of a local maximum, the local gradient or the turning point of a curve representing the temporal development of the measured variable and thereby provide the decision variable.

26. The method according to any one of claims 11 to 25, characterized in that the models differ at least in the predetermined measured variable or the predetermined algorithm.