JPH0926396A - Method and apparatus for inspecting fault of foreign matter or the like - Google Patents

Abstract

PROBLEM TO BE SOLVED: To facilitate the setting of inspecting conditions and to sort and judge the inspecting fault. SOLUTION: A fault detecting simulator 1 previously obtains the light intensity distribution and the detection output of a detector in an apparatus 6 based on the distribution of the scattered lights from the surface of a sample to be inspected in which a surface structure is modeled and the distribution of the scattered lights from the fault of a foreign matter existing on the sample to be inspected. Thus, the condition that the ratio of the detected output of the surface of the sample to be detected to that of the fault becomes maximum is obtained and the condition 14 is standardized, and hence the condition 14 by the apparatus 6 can be easily set. Therefore, the operation can be enhanced in efficiency, stabilized, and the burden on operator can be alleviated.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method of inspecting a semiconductor device, a magnetic disk, a thin film transistor, and the like for defects such as foreign particles during manufacturing, and an apparatus therefor.

[0002]

2. Description of the Related Art In the manufacturing process of semiconductors and the like, defects such as foreign substances existing on the surface of products are inspected. In this inspection, for example, a defect such as a foreign substance is detected by irradiating the product with light and detecting scattered light generated from a defect such as a foreign substance existing on the surface of the product.

By the way, in the inspection of a defect inspection apparatus for foreign matters and the like, the target product has various structures depending on the product type and process, such as the geometrical shape of the surface, the physical properties such as reflectance, or the film thickness. When illumination for inspection is performed on the surface having such various structures, the scattered light generated varies depending on the sample depending on the structure. In addition, scattered light from defects such as foreign substances existing on the surface is also affected by the surface structure of the sample, and also varies depending on the sample.

For this reason, it is necessary to set the inspection conditions for each type and process of the sample to be inspected. To set the inspection conditions, the sample is actually inspected by the inspection device, and the inspection conditions such as the detection threshold are changed based on the obtained detection result, and the scattered light from the sample surface is detected. Instead, the setting is made so that only scattered light from defects such as foreign matter is detected. Trial and error adjustment is required to obtain such detection conditions.

A standard sample to which standard particles are adhered is used as a sample used for setting the inspection conditions of the inspection device or for calibrating the sensitivity of the inspection device. Several inventions relating to this standard sample have been made. . For example, Japanese Unexamined Patent Publication
No. 214641 discloses a method of using a standard sample to which metal particles having a polydisperse particle size distribution are attached in order to perform calibration without depending on the characteristics of the inspection device. Further, in Japanese Patent Laid-Open No. 3-1218044, there is one in which a surface protector (pellicle) having a transparent film formed on the surface of a sample to which standard particles are adhered is provided, and the effect of adhered foreign matter is eliminated by the protector. . Further, in Japanese Patent Application Laid-Open No. 5-160244, there is one in which fine particles attached to a sample are covered with a fixing film so that they can be washed, thereby enabling repeated use over a long period of time. Further, in JP-A-5-340884, there is one in which a thin film having the same optical properties as a CVD film is spin-coated on the particles to form a standard sample of foreign matter in the film.

On the other hand, in order to investigate the cause of defects such as foreign substances and take countermeasures, the distribution of defects such as foreign substances on the sample, or the size and shape of defects such as foreign substances are classified and judged. In the inspection apparatus, the distribution of defects such as foreign matter on the sample can be obtained from the detection result. However, the size can be predicted to some extent from the detection output, but the size of the scattered light generated differs depending on the surface structure of the sample, as described above. It is difficult to quantitatively determine the size of a defect such as a foreign substance.

Therefore, in reality, the size of defects such as foreign matter is confirmed by the visual observation system as well as the shape. Regarding the classification / judgment of the detection results in the inspection device, the position information of the detected foreign matter is stored in order to improve the workability and certainty of the visual confirmation of the detection results, as disclosed in JP-A-62-75336. An example of an inspection device that automatically positions a foreign substance in the visual field of a visual observation system based on the stored position information is disclosed. Further, Japanese Patent Application Laid-Open No. 4-109108 discloses a particle size-scattered light correction curve created for correcting scattered light detector output according to the optical characteristics of the thin film for inspecting foreign matter on the thin film. An example of an inspection device for discriminating the size of a foreign substance adhered to is described.

Further, in order to predict the performance of the inspection device,
In the prior art, a simulation of scattered light detection in a defect inspection of foreign matter or the like is performed. For example, as a first conventional technique, Robert G. et al. Knollenbur
g "The importance of medi
a reflexive index in eva
luating liquid and surfac
e microcontamination meas
elements ”Proceedings of I
nstate of Environmental
Sciences pp. 501-511,1986
Uses the Mie theory to simulate the amount of scattered light detected from standard particles in a liquid or on a bare silicon substrate.

As a second conventional technique, Gregor
y L. Wojcik, David K. Vaugha
m, Lee K .; Galbraith "Calcul
ation of light scatter fr
om structureson silicon s
urfaces ”SPIE Vol.774 Las
ers in Microlithography p
p. 21-31, 1987, a finite element time domain difference method (FD-TD method) is used to simulate the scattered light distribution from a cylindrical object on a bare silicon substrate or a spherical particle.

In the first conventional technique, Mi is used for calculation of scattered light.
e theory is used. Wolf about Mie theory
This is an analytical solution of scattered light from spherical particles, which is described in the literature such as "Principles of Optics" pp932-971. Therefore, it is impossible to calculate the scattered light generated from the circuit pattern on the wafer other than the spherical particles.

Further, in the second prior art, a numerical simulation of electromagnetic wave scattering is performed, but it is only a simulation of the distribution of scattered light generated from a detection target and does not include a simulation related to detection. It was impossible to perform a simulation considering the configuration of.

[0012]

In the above-mentioned prior art, in setting the inspection conditions and classifying / determining the inspection results,
The work requires a skilled person and a large amount of work, and therefore there is a very troublesome problem in inspecting for defects such as foreign matter.

In view of the above-mentioned problems of the prior art, an object of the present invention is to allow inspection conditions to be set easily and to easily and surely classify / determine inspection defects such as foreign matter. Another object of the present invention is to provide an inspection method, and another object of the present invention is to provide an apparatus for inspecting defects such as foreign matters, which can accurately implement the above method.

[0014]

In order to achieve the above object, the present invention uses a defect detection simulator such as a foreign matter,
By using the result as a reference, it is possible to simplify the setting of the inspection condition of the inspection device and to classify / determine the inspection result.

That is, in the method of the present invention, in the apparatus for inspecting defects such as foreign matter based on the scattered light generated from the surface of the inspection sample and the scattered light generated from the foreign matter existing in the inspection sample, the surface is previously measured. Based on the distribution of scattered light generated from the surface of the sample to be inspected whose structure is modeled and the distribution of scattered light generated from defects such as foreign substances existing on the sample to be inspected, the light intensity distribution and the detector A simulation step in which the detection output is obtained, and based on the light intensity distribution and the detection output, a condition that maximizes the ratio of the detection output of the sample surface to be inspected and the detection output of the defect is obtained and the inspection conditions are standardized. And an inspection step of inspecting and outputting an actual inspection sample by the device under the standardized conditions, an actual inspection result by the inspection step, and an inspection by the simulation step. Compares the output, it is characterized in that it has a actual process classifying and determining the shape of the defects such as foreign matter.

Further, the apparatus of the present invention has a defect classification judging mechanism for separating and judging the shape of a defect such as a foreign matter while setting the inspection condition for the inspection sample. The defect classification determination mechanism is based on the distribution of scattered light generated from the surface of the sample to be inspected whose surface structure is modeled and the distribution of scattered light generated from defects such as foreign substances existing on the sample to be inspected. A defect detection simulator for obtaining the light intensity distribution and the detection output of the detector in the apparatus, and based on the light intensity distribution and the detection output by the defect detection simulator, the detection output of the sample surface to be inspected and the detection output of the defect When the actual inspection sample is inspected by the device under the conditions standardized by the device parameter setting means for obtaining the condition that maximizes the ratio and standardizing the inspection conditions, It is characterized by having an inspection result comparison means for comparing the actual inspection result with the detection output of the defect detection simulator and classifying and determining the actual shape of defects such as foreign particles. It is an.

[0017]

In the method of the present invention, as described above, in the apparatus for inspecting defects such as foreign matter based on the scattered light generated from the surface of the inspection sample and the scattered light generated from the foreign matter existing in the inspection sample, Based on the distribution of scattered light generated from the surface of the sample to be inspected whose surface structure is modeled and the distribution of scattered light generated from defects such as foreign matter existing on the sample to be inspected, the light intensity distribution and the detector in the device And the detection output is obtained, and based on the light intensity distribution and the detection output, a condition that maximizes the ratio between the detection output of the surface of the sample to be inspected and the detection output of the defect is obtained and the inspection conditions are standardized. Since the process has the steps, it is possible to easily set the inspection condition by the defect inspection apparatus by the simulation step. Therefore, a trial-and-error approach is eliminated, and it is possible to improve work efficiency, stabilize work, and reduce the burden on workers.

Moreover, under the standardized conditions, an inspection step of inspecting and outputting an actual inspection sample by the apparatus and an actual inspection result by the inspection step and a detection output by the simulation step are provided. Since it has a step of comparing and classifying and determining the actual shape of defects such as foreign particles, it is possible to realize high-speed processing, and therefore classify and determine inspection results easily and reliably. be able to.

Further, in the apparatus of the present invention, as described above, the distribution of scattered light generated from the surface of the sample to be inspected whose surface structure is modeled and the scattered light generated from defects such as foreign matters existing on the sample to be inspected. And a defect detection simulator that obtains a light intensity distribution and a detection output of a detector in the apparatus based on the distribution of the light intensity distribution, and a detection output of the surface of the inspected sample and the defect based on the light intensity distribution and the detection output by the defect detection simulator. Under the conditions standardized by the device parameter setting means for determining the condition that maximizes the ratio of the detection output of When inspected, the inspection result comparison means compares the actual inspection result with the detection output of the defect detection simulator to classify and determine the actual shape of a defect such as a foreign substance. Is provided with the defect classification determination mechanism having, it may be carried out properly the method.

[0020]

Embodiments of the present invention will be described below with reference to FIGS. 1 to 6 show an embodiment of a defect inspection apparatus 6 for carrying out the method of the present invention. In FIG.
Reference numeral 21 denotes an inspection stage unit. The inspection stage unit 21 fixes the sample to be inspected to the upper surface by a fixing means 218 and is movable in the Z direction, and a Z stage 210.
X stage 211 for moving the sample 26 to be inspected in the X direction via Y, and Y for similarly moving the sample 26 in the Y direction.
Stage 212, Z stage 210, X stage 21
The stage drive system 213 drives each stage of the 1 and Y stages 212, and the focus position detection control system 214 detects the Z direction position of the sample 26 to be inspected. Each stage is controlled so that focusing can always be performed with required accuracy during inspection of the sample 26 to be inspected. The coordinates X, Y, and Z are directions indicated by arrows in FIG.

Reference numeral 22 is an illumination system. Reference numeral 221 denotes a laser light source, and 222 denotes a condenser lens, which condenses the light flux emitted from the laser light source 221 and illuminates the surface of the sample 26 to be inspected.

A detection optical system 24 has an objective lens 241 facing the surface of the sample 26 to be inspected, and a viewing zone lens (hereinafter referred to as a field lens) 243 provided near the image forming position of the objective lens 241. There is. The light passes through the spatial filter 244 provided on the Fourier transform surface for the inspection visual field 215 of the inspected sample 26 and the imaging lens 245, and the inspection visual field 215 on the inspected sample 26 is a detector of the signal processing system 25 described later. An image is formed on 251.

The field lens 243 is the objective lens 2
41, the image of the upper focal position 246 on
Image on 4. Further, the optical path is branched by the half mirror 242 inserted in the optical path, and the second field lens 246 causes the upper focal position 2 on the objective lens 241.
The image of 46 is formed on the Fourier transform plane observation detector 252. The spatial filter 244 uses the difference in the distribution on the Fourier transform surface of the scattered light generated from the surface of the sample 26 to be inspected and the scattered light generated from the defect such as a foreign substance, from the surface of the sample 26 to be inspected. It is a means for blocking the scattered light generated and for distinguishing the scattered light generated by a defect such as a foreign substance by a light shielding portion and a transmission portion. A plurality of types of spatial filters 244 are attached to switching means 249 such as a revolver or a slide, which will be described later,
The switching means 249 has a structure that can be switched according to the surface structure of the sample to be inspected. Instead of the spatial filter, a polarization filter that distinguishes the scattered light generated from the surface of the inspected sample 26 and the scattered light generated from a defect such as a foreign substance may be used.

Reference numeral 25 is a signal processing system.
Includes the detector 251, a binarization circuit 253 for binarizing the output of the detector 251, a Fourier transform plane observation detector 252, a microcomputer 254, and a display means 255. .

The detector 251 photoelectrically converts incident light, and detects scattered light generated from the surface of the sample 26 to be inspected while scanning the X stage 210. In this case, when a defect such as a foreign substance existing on the sample 26 to be inspected exists in the detection field of view, the intensity of light incident on the detector increases, so that the output from the detector 251 is also increased. If a one-dimensional solid-state image sensor is used for the detector 251, there is an advantage that the detection field of view can be widened while maintaining the spatial resolution of detection.

Further, the Fourier transform plane observation detector 252
Is for detecting the light intensity distribution on the Fourier transform plane, and uses a photoelectric conversion element capable of detecting the light intensity distribution. For example, it is possible to use a one-dimensional or two-dimensional solid-state imaging device.

The binarization circuit 253 is preset with a threshold value for binarization, and an output value equal to or higher than the scattered light intensity corresponding to a foreign substance of a desired size output from the detector 251 is input. In this case, the logic level "1" is output.

Further, the microcomputer 254 has two
When the binarization circuit 253 outputs a logic level “1”, it is determined that “there is a defect”, the position information of the X stage 210 and the Y stage 211, and the pixel position in the element in the case of the detector 251 which is not a single element. The defect position information calculated from the above, the detection output value of the detector 251, and the image data of the Fourier transform image of the defect such as a foreign substance obtained by the Fourier transform surface observation detector 252 are stored in the memory, and the result is stored. It is configured to output to the display means 255.

Therefore, the defect inspection apparatus 6 is configured so that the scattered light generated from the surface of the inspection sample 26 and the inspection sample 26
A defect such as a foreign substance is detected based on the foreign substance adhering to the surface of the sample or scattered light generated from a defect such as a foreign substance such as a defective portion generated in the sample 26 to be inspected.

Therefore, in the defect inspection apparatus 6 of the embodiment, a defect classification determination mechanism for determining the size of a defect such as a foreign substance based on the inspection result 15 by the apparatus 6 and classifying / determining the shape of the defect is provided. I have it. The defect classification determination mechanism is roughly divided into a defect detection simulator 1 such as a particle, a simulation result database 2, a calculation result conversion unit 3, an apparatus parameter 4, and an inspection result comparison unit 5, as shown in FIG. have.

More specifically, the defect detection simulator 1 includes an electromagnetic wave simulator 111 as shown in FIG.
Thus, the optical behavior simulation of the surface of the sample 26 to be inspected is performed. That is, first, a standard inspected sample 26 in which a surface structure is modeled is prepared, and the object shape data 01, the physical property data 02 of the inspected sample 26 prepared, the wavelength of the illumination light in the inspection apparatus, the illumination angle, From the illumination condition data 03 such as the polarization, the electromagnetic wave simulator 111 obtains the scattered light distribution 104 including the scattered light intensity distribution, the phase distribution and the polarized light distribution from the surface of the inspected sample 26. Further, similarly to this, the distribution of scattered light generated from defects such as foreign matter existing on the surface of the sample 26 is also calculated. By such a procedure, the electromagnetic wave simulator 111 obtains the distribution of scattered light generated from the surface of the reference sample and scattered light generated from the foreign matter on the sample in the reference sample. This makes it possible to some extent predict which filter should be used from the intensity and polarization distribution of scattered light.

Next, the defect detection simulator 1 performs a detection simulation. In the detection simulation, the re-imaging simulator uses the scattered light distribution 104 including the intensity distribution, the phase distribution, and the polarization distribution of the scattered light obtained from the above calculation result, the filtering condition 105, and the detected pixel size condition 106. 112, light intensity distribution 1
07 and the detection output 308 on the detector 251 is determined.
Then, the spatial filter 244 or the polarization filter 24
By performing a detection simulation using the condition of 8 as a parameter, the condition that maximizes the ratio of the detection output of the sample surface and the detection output of the particles is obtained. The detection condition thus obtained is the optimum detection condition.

Therefore, the defect detection simulator 1 is
Based on the object shape data 01, the physical property value data 02, and the illumination condition data 03, the scattered light distribution 104 obtained from the surface of the inspected sample 26 and the scattered light distribution generated from defects such as foreign substances existing on the inspected sample 26 An arithmetic unit 100 including an electromagnetic wave simulator 111 that obtains 104, a re-imaging simulator 112 that obtains a light intensity distribution 107 and a detection output 108 based on the obtained scattered light distribution 104, filtering condition 105, and detection pixel size condition 106, Object shape data 01, physical property value data 02, illumination condition data 03, scattered light distribution 04, filtering condition 05, detection pixel size condition 06, light intensity distribution 07, detection output 08
Of the electromagnetic wave simulator 111 and the re-imaging simulator 112.

The electromagnetic wave simulator 111 operates based on the Maxwell equation, and the reimaging simulator 112 operates based on the Fourier transform method, which will be described later.

Further, the defect detection simulator 1 is
The obtained optimum conditions are output to the display device 121 and the simulation result database 2 is used as a database.
The simulation result database 2 outputs the simulation result 13 to the external device 33 composed of the defect inspection device 6 via the communication means 123 while being accumulated, integrated, and managed.

The calculation result conversion means 3 converts the simulation result 13 obtained by the defect detection simulator 1 into device parameters. Therefore, the calculation result conversion means 3 creates a relation between the value obtained by the defect detection simulator 1 and the parameter value on the device 6 as a device parameter conversion table, and based on this, the simulation result 13 is used as the device parameter. It is a means for converting data.

The device parameter setting means 4 sets the inspection condition 14 of the defect inspection device 6, that is, the inspection condition 14 such as the type of the spatial filter 244 and the detection threshold value based on the data converted by the calculation result converting means 3. Then, the setting data is commanded to the defect inspection apparatus 6. In this case, the defect inspection apparatus 6 selects a desired type of spatial filter 244, a desired threshold value, etc. according to a command from the apparatus parameter setting unit 4.

When the defect inspection apparatus 6 inspects an actual inspection object and the inspection result 15 is output from the microcomputer 254, the inspection result comparing means 5 outputs the actual inspection result 15 and the defect detection simulator 1. The size of the defect is determined and the shape of the defect is classified / determined by comparing the size with the detection output 08 of the simulation by, that is, by comparing the scattered light distribution from the defect such as a foreign substance. I am trying to do it.

In this case, the method of classifying the inspection results by the inspection result comparing means 5 will be described. The size of a defect such as a foreign substance can also be determined by the intensity distribution of scattered light. FIG. 6 shows an example of standard particles (diameter 0.5 μm, 0.8 μm,
Scattered light intensity distribution from 1.0 μm, 2.0 μm) is shown.
It is observed that the scattered light intensity distribution differs depending on the diameter of the particles, and the larger the diameter, the more the number of stripes. This is Figure 2
252 for Fourier transform plane observation of the inspection device shown in FIG.
Can be observed. If a polarization filter 248 can be installed in front of the detector 252, the polarization distribution of scattered light can be measured. By comparing the measurement result of the scattered light distribution with the simulation result 13, the size of a defect such as a foreign substance can be determined. Furthermore, since the scattered light distribution shown above is also related to the shape of the foreign matter, the detection simulator 1
By performing a simulation in which the shape of a defect such as a foreign substance is changed, storing the simulation in the simulation result database 2, and comparing the simulation result 13 with the scattered light distribution from the defect such as a foreign substance obtained by the inspection apparatus. Shape is classified according to the size of defects such as foreign particles
It becomes possible to judge.

Finally, the simulation method will be described. As described above with reference to FIG. 3, the defect detection simulator 1 receives the intensity, phase, and phase of scattered light from the detection target by the electromagnetic wave simulator 111 from the input of the object shape 01 of the detection target, the physical property data 02, and the illumination condition data 03.
The distribution 04 such as polarization is calculated, and then this scattered light distribution 0
4, the re-imaging simulator 112 calculates the image intensity distribution of the detection target and the detection output 35 from the detection condition data such as 4, the filtering condition 05 including the spatial filter and the polarization filter, and the detection pixel size condition 06. The calculation result is displayed on the display device 121, and the external storage means 1
It is accumulated as a database in 22 and is integrated and managed. Further, the simulation result 13 is output from the external storage means 122 to another device such as an inspection device by the communication means 123.

Here, the electromagnetic wave simulator 111 and the re-imaging simulator 112 will be described in more detail. The electromagnetic wave simulator 111 performs numerical calculation of the electromagnetic wave problem. The numerical calculation of electromagnetic wave problem is described in "Basic analysis method of electromagnetic wave problem" supervised by Eikichi Yamashita, and was used for antenna problem or waveguide problem in the past. There are various methods for numerical calculation of the electromagnetic wave problem, but when this is used for the problem of light as in the present invention, the scattered light (scattered electromagnetic field) generated when an object is illuminated with light (electromagnetic wave) is calculated. In doing so, the calculation target area is divided into small parts called elements, an equivalent discretized model is created for each, and then the whole is assembled from these. The so-called finite element method, boundary element method, and difference method can be applied. FIG. 5 shows an example of a model to be calculated (particles on the substrate, 41: particles, 42: substrate).

Next, the reimaging simulator 112 will be described. As the re-imaging simulator 112, a simulator in which an optical system is modeled by Fourier transform (hereinafter referred to as Fourier simulator) is used. Modeling of the imaging optical system by the Fourier simulator will be described below with reference to FIG. The coherent light 60 having the wavelength λ is formed on the stripe pattern with the pitch d _1.
When irradiated with (coherent light), according to the following formula 1,
Light is diffracted in the direction of the angle θ ₁ .

[0043]

[Equation 1]

Here, the lens 63 having the focal length f is arranged so that the position of the stripe pattern surface 61 becomes the focal position.
Since the first-order diffracted light 62 is projected at a distance of S ₁ from the center on the screen assumed at the focal position on the exit side, the angle θ ₁ and the distance S ₁ have the relationship of Equation 2.

[0045]

[Equation 2]

[0046] Equation 1, from equation (2), when the pitch of the fringe pattern to d ₁ is less than d _2, theta _1> theta _2, and the
Even on the screen surface 65, S ₁ > S ₂ . In this way, when the pitch of the stripe pattern decreases from d ₁ to d ₂ , the distance from the center is S ₁ on the screen surface 65.
To S ₂ increases. Here, the spatial frequencies s ₁ ′, s ₂ ′ of the stripe pattern (the number of repetitions of light and dark per unit length)
Is defined as in the following expression (3).

[0047]

(Equation 3)

From the above equations 1, 2 and 3, the following relationships are established.

[0049]

(Equation 4)

From the above, the coherent light 60 is projected on the screen according to the spatial frequency of the pattern on the stripe pattern surface. This means that the spatial axis is transformed into the frequency axis on the screen surface, which can be mathematically described by the Fourier transform.

Next, when the lens 64 having the focal length f is arranged at a position f from the screen surface 65, a fringe pattern is formed on the image plane. At this time, the relationship between the screen surface 65 and the image surface 66 is the reverse of the relationship between the stripe pattern surface 61 and the screen surface 65. That is, the image can be reproduced by the inverse Fourier transform of the Fourier transform plane.

In the detection simulator, the intensity and phase distribution of scattered light obtained by the electromagnetic wave simulator correspond to the image on the Fourier transform plane in FIG. Then, the re-imaging simulator is used to reproduce the image of the detection target from the intensity of the far scattered field and the phase distribution (image on the Fourier transform plane) obtained by the electromagnetic wave simulator. With the above configuration, it is possible to perform detection simulation using the surface morphology of the sample to be inspected or the configuration of the inspection device as a parameter.

As the execution means of the Fourier simulator, the Fast Fourier Transform (FFT) is generally used, but other means may be used. As for the re-imaging simulator, not only the Fourier simulator but also another frequency analysis method such as the maximum entropy method (MEM) may be used.

Since the defect inspection apparatus 6 of the embodiment has the defect separation judging mechanism as described above, its function and effect will be described below. At the time of actual inspection, the inspected sample 26 whose surface structure is modeled is used, and based on this, the defect detection simulator 1 for a foreign substance or the like of the defect separation determination mechanism detects the shape data 01 of the inspection object, the physical property data 02, and the defect inspection. Device 6
Based on the device parameter data 03 of the optical system, a simulation result 13 of a defect such as a particle or a scattered light detection output from the inspection target is output and stored in the simulation result database 2. The stored simulation result 13 is converted into data compatible with the device parameters through the calculation result conversion means 3, and based on this, the device parameter setting means 4 causes the defect inspection device 5 such as a foreign matter to be inspected.
The inspection condition 14 is set.

As a result, the defect inspecting apparatus 5 is selected for the condition such as the spatial filter 244 of the type set by the apparatus parameter setting means 4 and the threshold value.
The inspection target to be detected is set on the inspection stage unit 21 and the inspection target is inspected.

In this case, the inspection result 15 of the defect inspection apparatus 6
Is sent to the inspection result comparison means 5, where the classification / judgment result 16 is obtained by comparison with the simulation result 13. The classification / judgment result 16 is fed back to the calculation result conversion means 3 and used in the next inspection.

In the method of the present invention, as described above, the defect detection simulator 1 distributes the scattered light generated from the surface of the sample to be inspected whose surface structure is modeled in advance and the foreign matter existing on the sample to be inspected. Based on the distribution of scattered light generated from the defect, the light intensity distribution and the detection output of the detector in the device are obtained, and based on the light intensity distribution and the detection output, the detection output of the surface of the sample to be inspected and the detection of the defect Since there is a simulation process for standardizing the inspection condition 14 by obtaining the condition that maximizes the ratio with the output, the inspection condition 14 by the defect inspection apparatus can be easily set by the simulation process. Therefore, a trial-and-error approach is eliminated, and it is possible to improve work efficiency, stabilize work, and reduce the burden on workers.

Moreover, when the actual inspection sample is inspected and output by the defect inspection device 6 under the standardized condition, the actual inspection result 15 and the detection output by the simulation step are compared with the inspection result comparing means. Compare by 5,
Since there is a step of classifying / determining the shape of an actual defect such as a foreign substance, it is possible to realize high-speed processing, and therefore classification / determination of inspection results can be performed easily and reliably.

Further, the theoretically optimum inspection condition 14 obtained from the simulation result 13 makes it possible to operate the apparatus in a state in which the capacity of the apparatus is maximized. Furthermore, the margin of the detection parameter can be estimated. For example, the foreign matter on the deposition film changes its output depending on the thickness of the deposition film, but if it is predicted how far the inspection device can detect the foreign matter, stable operation of the inspection device becomes possible. Similarly, the simulator can calculate how the detection result changes when the conditions of the device change, for example, when the position of the spatial filter shifts. This makes it possible to estimate the cause when the device changes over time.

Further, by recognizing the detection result on the physical model through the simulation, it becomes easy to make the inspection result compatible between the apparatuses having different detection methods. When comparing devices with different detection methods,
Considering that the actual detection is performed using the sample and the comparison is performed, the setting of the detection condition is different if the detection method is different, and at this time, the detection results obtained from the test conditions determined by trial and error indicate that the devices are It is difficult to make comparisons and make the inspection results compatible. With the device configuration according to the present invention, even when comparing the actual detection results with the sample to be inspected, it is possible to compare the devices with the detection results under the optimal conditions that the device can take. It becomes possible to quantitatively interpret the inspection results of each device.

Further, in the apparatus of the present invention, as described above, the distribution of scattered light generated from the surface of the sample to be inspected whose surface structure is modeled and the scattering generated from defects such as foreign matters existing on the sample to be inspected. The defect detection simulator 1 for obtaining the light intensity distribution and the detection output of the detector in the device based on the light distribution, and the detection output of the surface of the sample to be inspected based on the light intensity distribution and the detection output by the defect detection simulator 1. Under the conditions standardized by the device parameter setting means 4 for standardizing the inspection condition 14 by obtaining a condition that maximizes the ratio between the defect detection output and the detection output of the defect. When the inspection target is inspected by the device 6, the actual inspection result 15 is compared with the detection output by the defect detection simulator to classify / determine the actual shape of defects such as foreign particles. Because test results compared and a defect classification decision mechanism and a means 5 that can be performed accurately above method.

7 to 9 show other embodiments of the defect classification judging mechanism, respectively. 7 to 9, the same reference numerals as those in FIG. 1 represent the same or corresponding ones. In the embodiment shown in FIG. 7, the defect detection simulator 1 and the calculation result conversion means 3 are directly connected. As a result, the simulation result database 2 shown in FIG. 1 becomes unnecessary, so that the system configuration can be simplified and the cost can be reduced.

In the embodiment shown in FIG. 8, an object shape data 01, physical property value data 02,
The illumination condition data 03 is input by the measuring device 101 and the measurement data converting means 102 for measuring dimensions, measuring film thickness and the like. According to this, since the measured value of the inspected sample 26 can be input to the defect detection simulator 1, more precise simulation and setting of the inspection condition 14 can be performed in response to a process error different from the design data.

The embodiment shown in FIG. 9 uses one defect classification judging mechanism and a plurality of defect inspection devices 6, and the plurality of defect inspection devices 6 are networked to the defect classification judging mechanism via the communication line 103. Has been converted. According to this, it becomes possible to centrally manage the inspection condition 14 and the inspection result of the defect inspection apparatus 6.

FIGS. 10 and 11 show filter switching means in the defect inspection apparatus 6, respectively. In the embodiment shown in FIG. 10, as the filter switching means 249,
It is composed of a slider 2491 in which a plurality of types of spatial filters 244 are arranged side by side on a straight line and an actuator 2492 that reciprocally drives the slider 2491. By driving the actuator 2492, the slider 2491 is moved in the linear direction to obtain a desired spatial filter. 244 is positioned and selected.

The embodiment shown in FIG. 11 is composed of a revolver 2493 in which a plurality of types of spatial filters 244 are arranged side by side in the same radius and mounted as a filter switching means 249, and an actuator 2494 for rotationally driving the revolver. By driving the actuator 2494, the revolver 2493 is rotated around the axis, and the desired spatial filter 24
4 is positioned and selected. FIG.
0 and FIG. 11, these actuators 249
2, 2494 may be either a motor or a cylinder. Of course, a polarization filter may be used instead of the spatial filter 244.

[0067]

As described above, according to the first and second aspects of the present invention,
According to 2, according to the distribution of scattered light generated from the surface of the sample to be inspected whose surface structure is modeled in advance and the distribution of scattered light generated from defects such as foreign matters existing on the sample to be inspected, The intensity distribution and the detection output of the detector in the apparatus are obtained, and based on the light intensity distribution and the detection output, an inspection is performed by obtaining a condition that maximizes the ratio of the detection output of the sample surface to be inspected and the detection output of the defect. It has a simulation process to standardize the conditions and is configured to set the inspection conditions by the defect inspection equipment, eliminating the trial-and-error approach, improving work efficiency, stabilizing, and reducing the burden on workers. When the actual inspection sample is inspected and output by the device under the standardized conditions, the actual inspection result and the detection by the simulation process can be performed. It has a process of classifying and judging the shape of the defect such as an actual foreign substance by comparing with the force, and it is configured to speed up the processing, so the classification and judgment of the inspection results can be performed easily and reliably. There is an effect that can be.

According to claim 3, in the simulation step, the scattered light distribution obtained from the surface of the sample to be inspected and the sample to be inspected by Maxwell's equation based on the object shape data, the physical property data, and the illumination condition data. A step of obtaining scattered light distributions generated from defects such as foreign substances existing above, and a step of obtaining a light intensity distribution and a detection output based on the obtained scattered light distributions, filtering conditions, and detection pixel size conditions by a Fourier transform method Since it has the above, there is an effect that the surface morphology of the sample to be inspected can be clarified and the detection simulation can be made accurate.

According to claims 4 to 6, the distribution of scattered light generated from the surface of the sample to be inspected whose surface structure is modeled and the scattered light generated from defects such as foreign matters existing on the sample to be inspected. A defect detection simulator for obtaining a light intensity distribution and a detection output of a detector in the apparatus based on the distribution, and a detection output on the surface of the sample to be inspected and the defect based on the light intensity distribution and the detection output by the defect detection simulator 1. Device parameter setting means for obtaining a condition that maximizes the ratio of the detection output of the device and the inspection condition and standardizing the device parameter setting device under the conditions standardized by the device parameter setting device. When inspected, the actual inspection result is compared with the detection output by the defect detection simulator,
Since it has a defect classification judging mechanism having inspection result comparing means for classifying and judging the shape of defects such as actual foreign matters,
There is an effect that the above method can be performed accurately. Claim 7
According to this, there is also an effect that claim 3 can be implemented accurately.

[Brief description of drawings]

FIG. 1 is a schematic configuration diagram of a defect classification determination mechanism showing an embodiment of a defect inspection apparatus for carrying out the method of the present invention.

FIG. 2 is a schematic configuration diagram showing a defect inspection apparatus.

FIG. 3 is an explanatory diagram showing a defect detection simulator of a defect classification determination mechanism.

FIG. 4 is an explanatory diagram showing an example in which an inspection target of a light scattering simulator is modeled.

FIG. 5 is an explanatory diagram showing an FFT simulator.

FIG. 6 is an explanatory diagram showing an intensity distribution of scattered light generated from particles.

FIG. 7 is a schematic configuration diagram of a defect classification judging mechanism showing another embodiment of the defect inspection apparatus for carrying out the method of the present invention.

FIG. 8 is a schematic configuration diagram of a defect classification determination mechanism showing still another embodiment of the defect inspection apparatus.

FIG. 9 is a schematic configuration diagram of a defect classification determination mechanism showing still another embodiment of the defect inspection apparatus.

FIG. 10 is a front view (a) showing a filter switching means in the defect inspection apparatus and a plan view (b) of the filter.

FIG. 11 is a front view (a) and a plan view (b) of the filter, showing another filter switching means of the defect inspection apparatus.

[Explanation of symbols]

01 ... Shape data of inspection target, 02 ... Physical property value data of inspection target, 03 ... Data of device parameter of optical system, 1 ...
Simulator for detecting defects such as foreign matter, 2 ... Simulation result database, 3 ... Calculation result conversion means, 4 ... Device parameter setting means, 5 ... Detection result comparing means, 6 ... Defect inspection apparatus for foreign matter, 13 ... Simulation result, 14 ...
Inspection condition, 15 ... Inspection result, 16 ... Classification / judgment result.

Claims (7)

[Claims] 1. Scattered light generated from the surface of an inspection sample,
In an apparatus for inspecting defects such as foreign matter based on scattered light generated from foreign matter existing in the inspection sample, the distribution of scattered light generated from the surface of the inspected sample whose surface structure is modeled in advance and the inspected sample Based on the distribution of scattered light generated from defects such as foreign matter existing on the above, the light intensity distribution and the detection output of the detector in the device are obtained, and based on the light intensity distribution and the detection output, A simulation step of standardizing the inspection condition by obtaining a condition that maximizes the ratio of the detection output and the detection output of the defect, and under the standardized condition, an actual inspection sample is inspected by the device. In addition, the inspection step for outputting and the actual inspection result by the inspection step and the detection output by the simulation step are compared to determine the actual size of a defect such as a foreign substance and determine the shape of the defect. Defect inspection method foreign matter and having a kind-determining step. 2. Scattered light generated from the surface of the inspection sample,
In an apparatus for inspecting defects such as foreign matter based on scattered light generated from foreign matter existing in the inspection sample, the distribution of scattered light generated from the surface of the inspected sample whose surface structure is modeled in advance and the inspected sample The distribution of scattered light generated from a defect such as a foreign substance existing above is obtained, and the intensity distribution, phase distribution, and polarization distribution of the obtained scattered light are obtained, and based on the obtained values, the light intensity distribution and detection in the device are performed. The detection output of the detector is obtained, and based on the light intensity distribution and the detection output, a condition that maximizes the ratio of the detection output of the surface of the sample to be inspected and the detection output of the defect is obtained and the inspection conditions are standardized. A simulation process, an inspection process of inspecting and outputting an actual inspection sample by the device under the standardized conditions, an actual inspection result by the inspection process, and an inspection by the simulation process. It compares the output, along with determining the actual size of defects such as foreign matter, and classify the shape of the defect
A method for inspecting a defect such as a foreign matter, which comprises the step of judging. 3. The scattered light distribution obtained from the surface of the sample to be inspected based on the object shape data, the physical property value data, and the illumination condition data by Maxwell's equation, and the foreign matter existing on the sample to be inspected in the simulation step. And a step of obtaining a light intensity distribution and a detection output based on the obtained scattered light distribution, the filtering condition, and the detected pixel size condition by the Fourier transform method, respectively. The defect inspection method for foreign matter or the like according to any one of claims 1 and 2. 4. Scattered light generated from the surface of the inspection sample,
In a device for inspecting defects such as foreign substances based on scattered light generated from foreign substances existing in the inspection sample, while setting inspection conditions for the inspection sample, a defect classification determination mechanism that separates and determines the shape of defects such as foreign substances The defect classification determination mechanism has a distribution of scattered light generated from the surface of the sample to be inspected whose surface structure is modeled and a distribution of scattered light generated from defects such as foreign substances existing on the sample to be inspected. A defect detection simulator for obtaining the light intensity distribution and the detection output of the detector in the apparatus, and the detection output of the surface of the sample to be inspected and the detection output of the defect based on the light intensity distribution and the detection output by the defect detection simulator. And an actual inspection under the conditions standardized by the device parameter setting means for determining the condition that maximizes the ratio of When the material is inspected by the device, the actual inspection result is compared with the detection output by the defect detection simulator to determine the size of an actual defect such as a foreign substance, and to classify and determine the shape of the defect. A defect inspection apparatus for foreign matter and the like, comprising: inspection result comparison means. 5. Scattered light generated from the surface of the inspection sample,
In a device for inspecting defects such as foreign substances based on scattered light generated from foreign substances existing in the inspection sample, while setting inspection conditions for the inspection sample, a defect classification determination mechanism that separates and determines the shape of defects such as foreign substances The defect classification determination mechanism has a distribution of scattered light generated from the surface of the sample to be inspected whose surface structure is modeled and a distribution of scattered light generated from defects such as foreign substances existing on the sample to be inspected. As well as
The intensity distribution, phase distribution, and polarization distribution of the obtained scattered light are obtained, the light intensity distribution and the detection output of the detector in the device are obtained based on the obtained values, and the object is detected based on the light intensity distribution and the detection output. Defect detection simulator for standardizing the inspection conditions by obtaining the condition that the ratio of the detection output of the inspection sample surface and the detection output of the defect is the maximum, based on the light intensity distribution and the detection output by the defect detection simulator, Device parameter setting means for standardizing the inspection conditions by obtaining a condition that maximizes the ratio of the detection output of the surface of the sample to be inspected and the detection output of the defect, and under the conditions standardized by the device parameter setting means. When an actual inspection sample is inspected by the device, the actual inspection result is compared with the detection output by the defect detection simulator to determine the actual size of a defect such as a foreign substance. The defect inspection apparatus of foreign matter and having a classification-determining test results comparing means the shape of the defect. 6. Scattered light generated from the surface of the inspection sample,
In a device for inspecting defects such as foreign substances based on scattered light generated from foreign substances existing in the inspection sample, while setting inspection conditions for the inspection sample, a defect classification determination mechanism that separates and determines the shape of defects such as foreign substances The defect classification determination mechanism has a distribution of scattered light generated from the surface of the sample to be inspected whose surface structure is modeled and a distribution of scattered light generated from defects such as foreign substances existing on the sample to be inspected. As well as
The intensity distribution, phase distribution, and polarization distribution of the obtained scattered light are obtained, the light intensity distribution and the detection output of the detector in the device are obtained based on the obtained values, and the object is detected based on the light intensity distribution and the detection output. Defect detection simulator for standardizing the inspection conditions by obtaining the condition that the ratio of the detection output of the inspection sample surface and the detection output of the defect is the maximum, based on the light intensity distribution and the detection output by the defect detection simulator, Device parameter setting means for standardizing the inspection conditions by obtaining a condition that maximizes the ratio of the detection output of the surface of the sample to be inspected and the detection output of the defect, and under the conditions standardized by the device parameter setting means. When an actual inspection sample is inspected by the device, the actual inspection result is compared with the detection output by the defect detection simulator to determine the actual size of a defect such as a foreign substance. And an inspection result comparing unit that classifies and determines the shape of the defect, and the apparatus parameter setting unit sets the inspection condition when the inspection condition is set based on the data converted by the calculation result converting unit. A defect inspection apparatus for inspecting foreign matters, which is characterized by instructing the apparatus. 7. The defect detection simulator exists on the inspected sample and the scattered light distribution obtained from the surface of the inspected sample based on the object shape data, the physical property value data, and the illumination condition data by the mask well equation. An electromagnetic wave simulator for obtaining scattered light distributions generated from defects such as foreign substances, and the scattered light distribution obtained by the Fourier transform method,
The defect inspection apparatus for foreign matter or the like according to any one of claims 4 to 6, further comprising a re-imaging simulator that obtains a light intensity distribution and a detection output based on a filtering condition and a detected pixel size condition.