CN1659690A - Method for generating multivariate analysis model expression for processing apparatus, method for executing multivariate analysis of processing apparatus, control device of processing apparatus,and c - Google Patents
Method for generating multivariate analysis model expression for processing apparatus, method for executing multivariate analysis of processing apparatus, control device of processing apparatus,and c Download PDFInfo
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Abstract
Detection data detected from a plurality of sensors when a plasma processing device (100A) as a reference and a plasma processing device (100B) of the same type are operated by first setting data are subjected to multivariate analysis so as to create respective multivariate analysis models. After this, when operated by new second setting data, detection data detected from a plurality of sensors of the plasma processing device (100A) are used to create its multivariate analysis model. By using the multivariate analysis model of the plasma processing device (100A) of the second setting data and the multivariate analysis model of the plasma processing device (100B), a multivariate analysis model of the plasma processing device (100B) corresponding to the new second setting data is created. According to this method, for example, even if there is a process characteristic difference between processing devices, a model created for one of the processing devices can be applied directly to another processing device of he same type. Accordingly, there is no need of acquiring data to create a model for each of the processing devices. Thus, it is possible to save labor and reduce the labor hour when creating a model.
Description
Technical field
The present invention relates to the multivariable analytic modell analytical model formula creating method of processing unit, multivariable analytic method, the control device of processing unit and the control system of processing unit that processing unit is used.
Background technology
In semiconductor manufacturing process, use various processing unit.In the film formation process and etching work procedure of handled objects such as semiconductor wafer and glass substrate, be extensive use of processing unit such as plasma processing apparatus.Each processing unit has the intrinsic treatment characteristic with respect to handled object respectively.Therefore, can monitor the treatment characteristic or the prediction processing characteristic of each device, carry out the optimization process of wafer.
For example, drive the etching monitor that has proposed plasma-etching apparatus in the flat 6-132251 communique the spy.In this case, study the relation of the spectrum analysis result of previous etched result (selectivity of uniformity, dimensional accuracy, shape or counterdie etc.) and plasma, the variation of treatment conditions (pressure, gas flow, bias voltage etc.) etc., by storing as database with these relations in advance, then do not need directly to check wafer, can monitor result indirectly.The result of being monitored for the underproof situation of inspection condition under, this information is delivered to Etaching device, the correcting process condition, perhaps abort process is given the manager with this intelligence aids simultaneously.
Open the processing monitoring method that has proposed plasma processing apparatus in the flat 10-125660 communique the spy.In this case, before processing, utilize wafer on probation, make the electric signal modular form related that makes the reflection plasmoid, the detected value of the electric signal that obtains during with the processing actual wafer with plasma treatment properties, in the substitution modular form, the state of prediction and diagnosis plasma.
In addition, open a plurality of parameters that proposed to utilize the semiconductor wafer processing system in the flat 11-87323 communique, the method and apparatus that monitors processing the spy.In this case, analyze a plurality of processing parameters, these parameters are connected each other with carrying out statistical, thus the variation of detection treatment characteristic or system performance.As a plurality of processing parameters, can use luminous, environmental parameter (pressure and temperature in the reaction chamber etc.).RF power parameter (reflection power, tuning voltage etc.) and system parameters (specific system configuration and control voltage).
Yet, under the situation of prior art, owing to statistical methods such as utilizing the multivariable parsing is analyzed various determination datas, make modular form, utilize this modular form, grasp and monitor the state and the treatment characteristic of processing unit, so individual difference between the transducer that is attached to each processing unit etc. is for example arranged, under situation about there are differences aspect the treatment characteristic of each processing unit, even on a processing unit, make modular form, but this modular form can not be used in other a kind of processing unit, and must be for each processing unit, take out various determination datas, make the modular form that it is fit to, like this, need a lot of formality and time when making modular form, this is a problem.In addition, under the situation that treatment conditions change, also must take out various determination datas, make the modular form that it is fit to each treatment conditions.Like this, aspect the making of modular form, needing a lot of formalities and time, also is a problem.
The present invention proposes in order to address the above problem, even its objective is treatment characteristic and treatment conditions that a kind of each processing unit will be provided difference is arranged, if on a processing unit, make modular form, then this modular form can be used on other processing unit of same kind, can reduce formality and burden when each processing unit made modular form, in addition, do not need each processing unit is made modular form again, can estimate the multivariable analytic modell analytical model formula creating method of processing unit of the unit state of each processing unit, the multivariable analytic method of using with processing unit.
Summary of the invention
In order to address the above problem, according to first viewpoint of the present invention, a kind of multivariable analytic modell analytical model formula creating method of processing unit is provided, utilize multivariable to resolve, make the unit state of estimating processing unit or the prediction processing multivariable analytic modell analytical model formula as a result the time, it is characterized in that: comprise following operation:
First operation is utilized multivariable to resolve in each processing unit each and is obtained when moving according to first setting data respectively in a plurality of processing unit by the detection data of a plurality of sensor of described each processing unit and the dependency relation of described first setting data;
Second operation, when with one among described each processing unit during as the benchmark processing unit, utilize multivariable to resolve, obtain in this benchmark processing unit when moving by the detection data of a plurality of sensor of described benchmark processing unit and the dependency relation of described second setting data according to the second new setting data; With
The 3rd operation, according to the described dependency relation in the described benchmark processing unit of obtaining in dependency relation in the described benchmark processing unit of obtaining in the dependency relation in described other processing unit of obtaining in described first operation, described first operation and described second operation, obtain described second setting data and the dependency relation that detects data in described benchmark processing unit other processing unit in addition, according to the dependency relation of obtaining like this, the unit state of described other processing unit of making an appraisal or prediction processing result's multivariable analytic modell analytical model formula.
In order to address the above problem, according to second viewpoint of the present invention, the multivariable analytic method that provides a kind of processing unit to use, it is the multivariable analytic method when utilizing the unit state of multivariable analyzing and evaluating processing unit or prediction processing as a result, it is characterized in that: comprise following operation:
First operation is utilized multivariable to resolve in each processing unit each and is obtained when moving according to first setting data respectively in a plurality of processing unit by the detection data of a plurality of sensor of described each processing unit and the dependency relation of described first setting data;
Second operation, when with one among described each processing unit during as the benchmark processing unit, utilize multivariable to resolve, obtain in this benchmark processing unit when moving by the detection data of a plurality of sensor of described benchmark processing unit and the dependency relation of described second setting data according to the second new setting data; With
The 3rd operation, according to the described dependency relation in the described benchmark processing unit of obtaining in dependency relation in the described benchmark processing unit of obtaining in the dependency relation in described other processing unit of obtaining in described first operation, described first operation and described second operation, obtain described second setting data and the dependency relation that detects data in described benchmark processing unit other processing unit in addition, according to the dependency relation of obtaining like this, the unit state of described other processing unit of making an appraisal or prediction processing result's multivariable analytic modell analytical model formula.
In addition, in the invention of above-mentioned first viewpoint and second viewpoint, described the 3rd operation, according to dependency relation with respect to described second setting data in described other processing unit of the dependency relation in described other processing unit of obtaining in described first operation and detection data, with the proportionate relationship of described dependency relation in the described benchmark processing unit of obtaining in described second operation with respect to the dependency relation in the described benchmark processing unit of obtaining in described first operation, obtain described second setting data in described other processing unit and detect the dependency relation of data also passable.In addition, described multivariable is resolved and for example can be utilized partial least square method (PLS method) to carry out.
In addition, in the invention of above-mentioned first viewpoint and second viewpoint, processing unit can be a plasma processing apparatus.At this moment, described setting data uses a plurality of Control Parameter of may command plasmoid, simultaneously, described detection data are used a plurality of plasmas reflection parameters of being selected from the reflection plasmoid, the multiple arrangement state parameter related with unit state, are reflected that at least one or the parameter more than two in the parameter of processing are also passable.
In addition, in the invention of above-mentioned second viewpoint, above-mentioned multivariable analytic modell analytical model formula is the detection data calculated by dependency relation in above-mentioned other processing unit of obtaining in above-mentioned the 3rd operation and above-mentioned second setting data and the dependency relation formula of above-mentioned second setting data.
Address the above problem for sending out, according to the 3rd viewpoint of the present invention, provide a kind of control device of processing unit, it is arranged in the processing unit of handling handled object, and setting data according to the rules carries out the control of described processing unit, it is characterized in that:
It is connected on described processing unit and the network that links together as the processing unit and the main device of benchmark at least, is provided with the transmission receiving-member that can carry out exchanges data,
Utilize described transmission receiving-member, via described network, detection data and described first setting data by a plurality of sensor of described processing unit in the time of will moving based on first setting data are sent in the described main device, utilize described transmission receiving-member, via described network, from described main device, receive described first setting data that utilizes multivariable to resolve to obtain by described main device based on the data that sent and the dependency relation of described detection data
Utilize described transmission receiving-member, via described network, the second new setting data is sent to main device, utilize described transmission receiving-member, via described network, from described main device, receive described second setting data obtained by described main device based on the data that sent and based on the dependency relation of the detection data of this second setting data;
Dependency relation according to described second setting data that receives from described main device, make multivariable analytic modell analytical model formula,, estimate the unit state or the prediction processing result of described processing unit according to this multivariable analytic modell analytical model formula, according to its result, control described processing unit.
In addition, in the invention of above-mentioned the 3rd viewpoint, above-mentioned detection data are calculated parts, utilize above-mentioned transmission receiving-member, via above-mentioned network, be used to make the setting data of above-mentioned other processing unit of evaluating apparatus state or prediction processing result's multivariable analytic modell analytical model formula when being received in the processed of stipulating in above-mentioned other processing unit, by the above-mentioned dependency relation of above-mentioned setting data that is received and above-mentioned processing unit, the detection data of calculating the above-mentioned processing unit when under the condition identical with the processed of the afore mentioned rules of above-mentioned other processing unit above-mentioned processing unit being moved are also passable.
In addition, in the invention of above-mentioned the 3rd viewpoint, the setting data of above-mentioned other processing unit also can use before the processed of afore mentioned rules by multivariable and resolve the setting data of above-mentioned other processing unit of obtaining and detection data by a plurality of sensor of above-mentioned other processing unit by the dependency relation of the detection data of a plurality of sensor of above-mentioned other processing unit and when making above-mentioned other processing unit carry out the processed of afore mentioned rules when moving based on this setting data are calculated.
In addition, in the invention of above-mentioned the 3rd viewpoint, the dependency relation of described second setting data in the described processing unit, calculated by described main device based on following dependency relation, these dependency relations are: utilize multivariable to resolve the dependency relation of described first setting data in the described processing unit of obtaining by described main device; When the described benchmark processing unit that is utilized multivariable to resolve to obtain by described main device moves based on first setting data by the detection data of a plurality of sensor of described benchmark processing unit and the dependency relation of described first setting data; When the described benchmark processing unit that is utilized multivariable to resolve to obtain by described main device moves based on the second new setting data by the detection data of a plurality of sensor of described benchmark processing unit and the dependency relation of second setting data.
In addition, in the invention of above-mentioned the 3rd viewpoint, processing unit can be a plasma processing apparatus.At this moment, described setting data uses a plurality of Control Parameter of may command plasmoid, simultaneously, described detection data are used a plurality of plasmas reflection parameters of being selected from the reflection plasmoid, the multiple arrangement state parameter related with unit state, are reflected that at least one or the parameter more than two in the parameter of processing are also passable.In addition, above-mentioned multivariable is resolved and can be utilized the partial least square method to carry out.In addition, above-mentioned processing unit can be a plasma processing apparatus.
In order to address the above problem, according to the 4th viewpoint of the present invention, provide a kind of control system of processing unit, it has the control device of the processing unit of handling handled object being controlled based on the setting data of regulation, it is characterized in that:
It has by transmission receiving-member a plurality of above-mentioned processing unit that is connected with network and the main device that is connected with described network,
Described main device; When the detection data that detect when a plurality of sensors that are received in from described a plurality for the treatment of apparatus via described network when moving based on the first setting data respectively in a plurality for the treatment of apparatus by described each treating apparatus and described the first setting data; Utilize multivariate analysis to obtain described the first setting data of receiving and the dependency relation of described detection data for each of described each treating apparatus; And via described network; The dependency relation of obtaining is sent in the corresponding treating apparatus
Described main device; When from described benchmark treating apparatus, being received in described each detection data that detected by a plurality of sensors of described benchmark treating apparatus when processing the treating apparatus as benchmark among the dress and moving based on the second new setting data and described the second setting data via described network; Described the first setting data that utilizes multivariate analysis to obtain to receive and described detection detect the dependency relation of data; And via described network; The dependency relation of obtaining is sent in the described benchmark treating apparatus
Described main device, when receiving described second setting data when via described network other processing unit beyond the described benchmark processing unit, according to the described dependency relation of resolving described first setting data in described other processing unit of obtaining by described multivariable, resolve the described dependency relation of described first setting data in the described benchmark processing unit of obtaining by described multivariable and resolve the described dependency relation of described second setting data in the described benchmark processing unit of obtaining by described multivariable, obtain described second setting data that received and based on the dependency relation of the detection data of this second setting data, and via described network, the dependency relation of being obtained is sent in described other processing unit
Described other processing unit, dependency relation according to described second setting data that from described main device, receives, make multivariable analytic modell analytical model formula, estimate the unit state or the prediction processing result of described processing unit according to this multivariable analytic modell analytical model formula, according to its result, control described processing unit.
In addition, in the invention of above-mentioned the 4th viewpoint, processing unit can be a plasma processing apparatus.At this moment, described setting data can use a plurality of Control Parameter of may command plasmoid, simultaneously, described detection data can be used a plurality of plasmas reflection parameters that are selected from the reflection plasmoid, the multiple arrangement state parameter related with unit state, reflect at least one or the parameter more than two in the parameter of processing.In addition, described multivariable is resolved and can be utilized the partial least square method to carry out.In addition, described processing unit can be a plasma processing apparatus.
Description of drawings
Fig. 1 is the profile of general structure of the plasma processing apparatus of expression first execution mode of the present invention.
Fig. 2 is the block diagram of an example of the multivariable resolution component of expression plasma processing apparatus shown in Figure 1.
Fig. 3 is the block diagram of structure of the processing unit control system of expression second execution mode of the present invention.
Fig. 4 is the figure of the motion flow of the modular form of processing unit control system of explanation present embodiment when making.
Fig. 5 is the figure of the motion flow of the modular form of processing unit control system of explanation present embodiment when making, and it is the continuation of Fig. 4.
Fig. 6 is the figure of the motion flow of the modular form of processing unit control system of explanation present embodiment when making, and it is the continuation of Fig. 5.
Fig. 7 is the figure of the motion flow of explanation when utilizing the modular form of processing unit control system of present embodiment to control.
Embodiment
Below, with reference to accompanying drawing, explain the preferred implementation of device of the present invention.In this specification and accompanying drawing, have the composed component of identical functions structure in fact, with identical symbolic representation, omit its repeat specification.
The plasma processing apparatus of first execution mode of the present invention at first, is described with reference to Fig. 1, Fig. 2.As shown in Figure 1, the plasma processing apparatus 100 of present embodiment has: the process chamber of aluminum (chamber) 101; Be configured in the lower electrode 102 in this treating capacity 101; By insulating part 102A supporting can lifting the supporting mass 103 of aluminum; With, be configured in the shower nozzle (following be called as required " upper electrode ") 104 that these supporting mass 103 tops and double as are supplied with the upper electrode of handling gas.
The top of above-mentioned process chamber 101 makes the last chamber 101A of minor diameter, and the bottom then makes large diameter chamber 101B down.Last chamber 101A is surrounded by dipole subring magnet 105.This dipole subring magnet 105 is a plurality of anisotropic segment cylindrical magnets are contained in the housing that is made of the ring-shaped magnetic body and form, and forms the same in the same direction as horizontal magnetic field as all in last chamber 101A.Make taking out of on the following top of chamber 101B and move into the gateway that wafer W is used, gate valve 106 is installed on this gateway.
High frequency electric source 107 is connected with lower electrode 102 by adaptation 107A, the High frequency power P of 13.56MHz is applied on the lower electrode 102 from this high frequency electric source 107, in last chamber 101A, and upper electrode 104 between the electric field of formation vertical direction.This High frequency power P by with high frequency electric source 107 and adaptation 107A between the kilowatt meter 107B that is connected detect.This High frequency power P is controllable parameter, and in the present embodiment, with controllable parameters such as gas flow described later, interelectrode distances, P is defined as Control Parameter with High frequency power.In addition, because Control Parameter is the parameter that can set, can be described as setting data again in plasma processing apparatus.
Above-mentioned adaptation 107A is equipped with two variable capacitor C1, C2, capacitor C and coil L in inside, obtains impedance matching by variable capacitor C1, C2.The capacity of variable capacitor C1, C2 under the matching status and the high frequency voltage Vpp that measures by the analyzer (not illustrating among the figure) in the above-mentioned adaptation 107A, with APC (automatic pressure controller described later, Automaticpressure controller) aperture etc. is the parameter of the unit state of expression when handling together.In the present embodiment, the aperture with capacity, high frequency voltage Vpp and the APC of variable capacitor C1, the C2 of indication device state is defined as the unit state parameter respectively.In addition, because the unit state parameter is uncontrollable parameter, be the data that can detect, so be also referred to as the detection data.
Configuration electrostatic chuck 108 on above-mentioned lower electrode 102.DC power supply 109 is connected with the battery lead plate 108A of this electrostatic chuck 108.Therefore, under high vacuum,, high voltage is applied on the battery lead plate 108A, but utilizes electrostatic chuck 108 Electrostatic Absorption to live wafer W by from DC power supply 109.On the periphery of this lower electrode 102, configuration focusing ring 110, the plasma that will produce in last chamber 101A concentrates on the wafer W.In addition, the air exhaust loop 111 that is installed in supporting mass 103 tops is configured in the downside of focusing ring 110.On the full periphery of this air exhaust loop 111,,, the gas in the last chamber 101A is drained into down chamber 101B by these holes uniformly-spaced to make a plurality of holes at circumferencial direction.
Above-mentioned supporting mass 103 can lifting between last chamber 101A and following chamber 101B by ball screw framework 112 and bellows 113.Therefore, under situation about wafer W being supplied on the lower electrode 102, lower electrode 102 can drop to chamber 101B by supporting mass 103, opens gate valve 106, by the transport mechanism that does not illustrate among the figure, wafer W is supplied on the lower electrode 102.Interelectrode distance between lower electrode 102 and the upper electrode 104 is the parameter that can be set at setting, as mentioned above, can be used as Control Parameter.
At the supporting mass 103 inner refrigerant flow 103A that are connected with refrigerant pipeline 114 that form, make refrigerant pass through refrigerant pipeline 114, in refrigerant flow 103A, circulate, wafer W is adjusted to set point of temperature.On supporting mass 103, insulating part 102A, lower electrode 102 and electrostatic chuck 108, make gas flow path 103B respectively, He gas is supplied to by gas piping 115A the slight gap between electrostatic chuck 108 and the wafer W from gas introducing mechanism 115 with authorized pressure as backside gas.By He gas, improve the heat conductivity between electrostatic chuck 108 and the wafer W.In addition, 116 is bellows cover.
Form gas introduction part 104A on above-mentioned shower nozzle 104.Treating-gas supply system 118 is connected with this gas introduction part 104A by pipeline 117.Treating-gas supply system 118 has Ar gas supply source 118A, CO gas supply source 118B, C
4F
8Gas supply source 118C and O
2Gas supply source 118D.These gas supply sources 118A, 118B, 118C, 118D, by valve 118E, 118F, 118G, 118H and mass flow controller 118I, 118J, 118K, 118L, each gas is supplied to shower nozzle 104 with the setting flow of stipulating, portion adjusts the mist that becomes the mix proportion with regulation within it.The flow of all gases can be controlled by mass flow controller 118I, 118J, 118K, 118L, and is detectable parameter, as mentioned above, can be used as Control Parameter.
On below above-mentioned shower nozzle 104 whole, dispose a plurality of hole 104B equably, mist as handling gas, by these holes 104B, is supplied in the 101A of chamber from shower nozzle 104.Blast pipe 101C is connected with the steam vent of the bottom of following chamber 101B, and the gas extraction system 119 by being made of the vacuum pump that is connected with this blast pipe 101C etc. drains into gas in the process chamber 101, keeps the gas pressure of regulation.APC valve 101D is set on blast pipe 101C, can automatically regulates aperture according to the gas pressure in the process chamber 101.This aperture is the unit state parameter of indication device state, is uncontrollable parameter.
On the sidewall of above-mentioned process chamber 101, be provided with detection window 121, on the outside of the sidewall of process chamber 101, be provided with optical splitter (hereinafter referred to as " optical measurement device ") 120, it can be by above-mentioned detection window 121, detects luminescence of plasma in the process chamber 101 with multi-wavelength.According to the optical data of the specific wavelength that utilizes this optical measurement device 120 to draw, monitor plasmoid, detect the terminal point of plasma treatment.This optical data with the electric data according to the plasma that is produced by High frequency power P, constitutes the plasma reflection parameter of reflection plasmoid.
Secondly, with reference to accompanying drawing, the multivariable resolution component that is located on the above-mentioned plasma processing apparatus 100 is described.Plasma processing apparatus 100 has multivariable resolution component 200 shown in Figure 2.This multivariable resolution component 200 has: the multivariable analysis program memory unit 201 of storage multivariable analysis program; Control Parameter measuring appliance 221; Sample off and on and reflect the Control Parameter signal sampling parts 202 of the detection signal of parameter measurement device 222 and 223 outputs of unit state parameter measurement device by plasma; Plasma reflection parameter signal sample unit 203 and unit state parameter signal sampling apparatus 204.In addition, also have: the resolution data memory unit 205 of desired data when the analysis result of the modular form that storage interrelates a plurality of plasmas reflection parameters (electric data and optical data), the multiple arrangement state parameter related with unit state and a plurality of Control Parameter etc. and parsing; By modular form, binding purpose Control Parameter, plasma are reflected the arithmetic unit 206 that parameter and loading amount state parameter calculate; According to signal calculated, binding purpose Control Parameter, a plurality of plasma are reflected the predictive diagnosis control assembly 207 that parameter and unit state parameter are predicted, diagnose, controlled from arithmetic unit 206 outputs.
In addition, according to Control Parameter, processing unit control assembly 225, siren 226 and the display unit 224 of control plasma processing apparatus 100 are connected with multivariable resolution component 200 respectively.Processing unit control assembly 225 according to the signal that sends from predictive diagnosis control assembly 207, continues or interrupts the processing of wafer W.As described later, the purpose of siren 226 and display unit 224 is, according to the signal that sends from predictive diagnosis control assembly 207, binding purpose is reported any one unusual in Control Parameter, a plurality of plasma reflection parameter and the unit state parameter.The data of 205 storages of resolution data memory unit and above-mentioned each parameter correlation and their process data (process data that multivariable is used in resolving).It is one that Control Parameter measuring appliance 221 shown in Figure 2, plasma reflection parameter measurement device 222,223 expressions of unit state parameter measurement device compile the measuring appliance of the measuring appliance of a plurality of Control Parameter measuring appliances such as flow detector, optical measurement device, high frequency voltage Vpp measuring appliance, a plurality of plasma reflection parameter, multiple arrangement state parameter respectively.
At this, principle of the present invention is described.The processing unit of for example plasma processing apparatus 100A being regarded as the benchmark when making new modular form is regarded plasma processing apparatus 100B as this benchmark processing unit processing unit in addition.At the individual difference that has only very little deviation to cause between plasma processing apparatus 100A, the 100B by on making.In addition, owing to also have on the transducers such as above-mentioned electric measurement device 107C, optical measurement device 120 because of making the individual difference that in each plasma processing apparatus, produces that difference causes, even, also can not get identical detection data so in a kind of plasma processing apparatus, use with a kind of transducer.Therefore, even in, also need each plasma processing apparatus is made multivariable analytic modell analytical model formula with a kind of plasma processing apparatus.A multivariable analytic modell analytical model formula can not be diverted other multivariable analytic modell analytical model formula with a kind of plasma processing apparatus of work.
Yet, in the present embodiment, even individual difference on making and the individual difference between a plurality of transducer are arranged between plasma processing apparatus 100A, the 100B, but the multivariable analytic modell analytical model formula that article on plasma body processing unit 100A makes can be diverted in another plasma processing apparatus 100B.In the present embodiment, a kind of method of using partial least square method (hereinafter referred to as " PLS (Partial Least Squares) ") to resolve as multivariable, make plasma processing apparatus 100A, 100B multivariable analytic modell analytical model formula separately, find out the individual difference between device, make the modular form that absorbs this individual difference then.The details publication of PLS method is in " JOURNAL OF CHEMOMETRICS, Vol.2 (pp.211-228) (1998) ".
In plasma processing apparatus 100A, 100B, with a plurality of Control Parameter (setting data) as the purpose parameter, with stripped reflection parameter such as a plurality of grades (the detection data that comprise the data of electric data and optics) parameter as an illustration, make make with the purpose parameter as the matrix X of composition with explanatory variable as the regression equation of the related following formula of the matrix Y of composition (1) expression (below, abbreviate " modular form " as) (first operation).
Utilize plasma processing apparatus 100A, 100B arithmetic unit 206 separately, use the PLS method of a kind of method of resolving, explanatory variable and the purpose parameter that draws according to experiment respectively, the regression matrix K that calculates modular form as multivariable
a, K
b, as mentioned above, these modular forms are stored in the resolution data memory unit 205.In addition, in the modular form of following formula (1), (2), K
a, K
bBe respectively the regression matrix of modular form, a represents plasma processing apparatus 100A, and b represents plasma processing apparatus 100B.
X
a＝K
aY
a…???(1)
X
b＝K
bY
b…???(2)
Even matrix X, Y have a plurality of explanatory variables and purpose parameter respectively, if minority measured value is separately arranged, then the PLS method can be obtained the relational expression of matrix X and matrix Y.And, even the relational expression that draws by few measured value, but stability and reliability height are the features of PLS method.When actual measurement became each data of explanatory variable and purpose parameter, the change Control Parameter detected Control Parameter, utilized a plurality of sensor plasma reflection parameters.
In this case, when the scope that changes Control Parameter (High frequency power, cavity indoor pressure, processing gas flow etc.) is narrow and small, shown in (3), can be similar to Control Parameter with linear formula, when the scope of variable parameter is big, shown in (4), can be used as 2 powers, 3 powers and 1 time the approximate Control Parameter of non-linear formula with 2 cross term additions.
This Control Parameter in plasma processing apparatus 100A and plasma processing apparatus 100B, is used identical scope, the Control Parameter of identical value.Asking regression matrix K
a, K
bSituation under owing to can utilize the applicant to be willing to that the spy order of operation identical with the PLS method that proposes in the 2001-398608 specification obtain, omit the explanation of this order of operation here.Individual difference between individual difference between plasma processing apparatus 100A and the plasma processing apparatus 100B and separately the transducer becomes the regression matrix K of following formula (1), formula (2) respectively
a, K
bPoor.
X＝[x
1，x
2，…，x
n]??????????…(3)
X＝[x
1，x
2，…，x
n1
(x
1)
2，(x
2)
2，…，(X
n)
2，
(x
1)
3，(x
2)
3，…，(x
n)
3，
x
1x
2，x
1x
3，…，x
n-1x
n，
(x
1)
2x
2，(x
1)
2x
3…(x
n-1)
2x
n]
…(4)
Yet, utilizing the PLS method to ask under the situation of above-mentioned modular form, a plurality of explanatory variables and a plurality of purpose parameter are measured in the experiment of exercise collection that be by utilizing wafer in advance.Therefore, prepare 18 wafers (TH-OXSi) as the exercise collection.In addition, TH-OX Si is the wafer that forms heat oxide film.In this case, can utilize the planning of experiments method, set Control Parameter (setting data) effectively, finish with minimal experiment.
In plasma processing apparatus 100A, be in the prescribed limit at center with the standard value, to each exercise wafer, change is carried out etch processes as the Control Parameter of purpose parameter to the exercise wafer.When etch processes, for each exercise wafer, every the regulate the flow of vital energy plasma reflection parameter of Control Parameter, electric data and optical datas etc. such as flow, the pressure in the chamber of each gas of body of measured place repeatedly, by arithmetic unit 206, calculate the mean value of these Control Parameter, plasma reflection parameter.The mean value that uses Control Parameter uses plasma reflection parameter as detecting data as setting data.
The scope of change Control Parameter when carrying out etch processes, is envisioned for the scope that Control Parameter changes to greatest extent, and Control Parameter is changed in this imagination scope.In the present embodiment, use High frequency power, cavity indoor pressure, gap size and the body of regulating the flow of vital energy (Ar gas, CO gas, the C of 102,104 at two electrodes up and down everywhere
4F
8Gas and O
2Gas) flow is as Control Parameter (setting data), and the standard value of each Control Parameter is different and different according to etch target.Even in plasma processing apparatus 100B, with identical main points, under identical Control Parameter (setting data), experimentize with plasma processing apparatus 100A, draw Control Parameter (setting data) and plasma reflection parameter (detection data).
Specifically, with the standard value center, in the scope of level 1 shown in the following table 1 and level 2, change each exercise wafer, set Control Parameter, respectively practise the etch processes of wafer.Handle respectively practise wafer during, by electric measurement device 107C, measurement based on electric datas such as high frequency voltage (from first-harmonic to 4 times ripple) V, high-frequency current (from first-harmonic to the 4 times ripple) I of plasma, phase difference as detecting data, simultaneously, by optical measurement device 120, measure the luminescent spectrum intensity (optical data) of 200～950nm wave-length coverage,, utilize these to detect data (electric data and optical data) as plasma reflection parameter as detecting data.In addition, utilize Control Parameter measuring appliance 221 simultaneously, measure each Control Parameter shown in the following table 1.
Table 1
| Electric power | Pressure | The gap | ??Ar | ?CO | ????C 4F 8 | ??O 2 | |
| ??W | ??mTorr | ????mm | ??sccm | ?sccm | ????sccm | ??sccm | |
| Level 1 | ??1460 | ??38 | ????25 | ??170 | ?36 | ????9.5 | ??3.5 |
| Standard value | ??1500 | ??40 | ????27 | ??200 | ?56 | ????10 | ??4 |
| Level 2 | ??1540 | ??42 | ????29 | ??230 | ?64 | ????10.5 | ??4.5 |
| ??2.67％ | ??5.00％ | ????7.41％ | ??15.00％ | ?28.00％ | ????5.00％ | ??12.50％ |
When handling the exercise wafer, set the standard value of above-mentioned each Control Parameter as heat oxide film, under standard value, anticipate 5 dummy wafers, make plasma processing apparatus 100A, 100B stabilisation.Then, in plasma processing apparatus 100A, 100B, carry out the etch processes of 18 exercise wafers.At this moment, as shown in table 2 below in plasma processing apparatus 100A, for each exercise wafer, in the scope of above-mentioned level 1 and above-mentioned level 2 above-mentioned each Control Parameter of change, promptly handle gas (Ar, CO, C
4F
8, O
2) pressure and High frequency power in the flow, chamber, handle and respectively practise wafer.
Then, for each exercise wafer, obtain a plurality of electric datas and a plurality of optical data by separately measuring appliance.These data are stored in the resolution data memory unit 205 as measured value.In arithmetic unit 206, calculate the mean value of the mean value of a plurality of Control Parameter measured value separately, a plurality of plasma reflection parameter (electric data, optical data) measured value separately, these mean values as purpose parameter and explanatory variable, are stored in the resolution data memory unit 205.Then, in arithmetic unit 206, use the PLS method, obtain the regression matrix K of the modular form of following formula (1) according to these operational datas
a(first operation).
In addition, in plasma processing apparatus 100B, also same with plasma processing apparatus 100A, as shown in table 2 below, the change Control Parameter, calculate the mean value of the measured value of each parameter, use these mean values, obtain the regression matrix K of the modular form of above-mentioned (2) formula as purpose parameter and explanatory variable
b(first operation).In following table 2, L1～L18 represents to practise the number of wafer.
Table 2
| Pressure | ??Ar | ??CO | ??C 4F 8 | ??O 2 | The gap | Electric power | |
| ??NO. | ??mTorr | ??sccm | ??sccm | ??sccm | ??sccm | ??mm | ??W |
| ??L1 | ????42 | ??170 | ??64 | ??10 | ??4.5 | ??25 | ??1500 |
| ??L2 | ????38 | ??200 | ??36 | ??9.5 | ??4.5 | ??29 | ??1500 |
| ??L3 | ????40 | ??230 | ??64 | ??9.5 | ??3.5 | ??27 | ??1500 |
| ??L4 | ????42 | ??170 | ??50 | ??9.5 | ??4.5 | ??27 | ??1540 |
| ??L5 | ????38 | ??170 | ??36 | ??9.5 | ??3.5 | ??25 | ??1460 |
| ??L6 | ????38 | ??200 | ??50 | ??10 | ??4 | ??27 | ??1500 |
| ??L7 | ????38 | ??230 | ??50 | ??10 | ??3.5 | ??25 | ??1540 |
| ??L8 | ????38 | ??230 | ??64 | ??10.5 | ??4.5 | ??29 | ??1540 |
| ??L9 | ????42 | ??200 | ??64 | ??10 | ??3.5 | ??29 | ??1460 |
| ??L10 | ????40 | ??170 | ??50 | ??10.5 | ??3.5 | ??29 | ??1500 |
| ??L11 | ????40 | ??200 | ??64 | ??9.5 | ??4 | ??25 | ??1540 |
| ??L12 | ????42 | ??200 | ??36 | ??10.5 | ??3.5 | ??27 | ??1540 |
| ??L13 | ????42 | ??230 | ??36 | ??10.5 | ??4 | ??25 | ??1500 |
| ??L14 | ????40 | ??230 | ??36 | ??10 | ??4.5 | ??27 | ??1460 |
| ??L15 | ????40 | ??200 | ??50 | ??10.5 | ??4.5 | ??25 | ??1460 |
| ??L16 | ????42 | ??230 | ??50 | ??9.5 | ??3.5 | ??29 | ??1460 |
| ??L17 | ????40 | ??170 | ??36 | ??10 | ??3.5 | ??29 | ??1540 |
| ??L18 | ????38 | ??170 | ??64 | ??10.5 | ??3.5 | ??27 | ??1460 |
Obtaining regression matrix K
a, K
bAfter, use plasma processing apparatus 100A, as shown in table 3 under the new treatment conditions shown in the following table 3, change Control Parameter such as handling gas flow from standard value, handle 20 testing wafers (TH-OX Si).Utilize sensor plasma reflection parameter and unit state parameter at this moment respectively.At this moment, as shown in table 3, a plurality of Control Parameter are set at the standard value of treatment conditions, make the plasma processing apparatus running, with 5 naked silicon wafers as dummy wafer.In process chamber 101, flow, make the plasma processing apparatus stabilisation.
Table 3
| Electric power | Pressure | The gap | ????Ar | ???CO | ???C 4F 8 | ??O 2 | |
| ?NO. | ?W | ?mTorr | ????mm | ???sccm | ??sccm | ???sccm | ??sccm |
| Naked Si1 | ?2000 | ?100 | ????35 | ????300 | ????50 | ????10 | ????8 |
| Naked Si2 | ?2000 | ?100 | ????35 | ????300 | ????50 | ????10 | ????8 |
| Naked Si3 | ?2000 | ?100 | ????35 | ????300 | ????50 | ????10 | ????8 |
| Naked Si4 | ?2000 | ?100 | ????35 | ????300 | ????50 | ????10 | ????8 |
| Naked Si5 | ?2000 | ?100 | ????35 | ????300 | ????50 | ????10 | ????8 |
| ?TH-OX?Si6 | ?2000 | ?100 | ????35 | ????300 | ????50 | ????10 | ????8 |
| ?TH-OX?Si7 | ?1980 | ?100 | ????35 | ????300 | ????50 | ????10 | ????8 |
| ?TH-OX?Si8 | ?1900 | ?100 | ????35 | ????300 | ????50 | ????10 | ????8 |
| ?TH-OX?Si9 | ?1980 | ?100 | ????35 | ????280 | ????50 | ????10 | ????8 |
| ?TH-OX?Si10 | ?2000 | ?95 | ????35 | ????300 | ????50 | ????10 | ????8 |
| ?TH-OX?Si11 | ?2000 | ?100 | ????33 | ????300 | ????50 | ????10 | ????8 |
| ?TH-OX?Si12 | ?2000 | ?100 | ????37 | ????300 | ????50 | ????10 | ????8 |
| ?TH-OX?Si13 | ?2000 | ?100 | ????35 | ????270 | ????50 | ????10 | ????8 |
| ?TH-OX?Si14 | ?2000 | ?98 | ????35 | ????300 | ????50 | ????10 | ????8 |
| ?TH-OX?Si15 | ?2000 | ?100 | ????35 | ????300 | ????30 | ????10 | ????8 |
| ?TH-OX?Si16 | ?2000 | ?100 | ????35 | ????300 | ????70 | ????10 | ????8 |
| ?TH-OX?Si17 | ?2000 | ?100 | ????35 | ????300 | ????50 | ????8 | ????8 |
| ?TH-OX?Si18 | ?2000 | ?100 | ????35 | ????300 | ????50 | ????12 | ????8 |
| ?TH-OX?Si19 | ?1900 | ?95 | ????35 | ????300 | ????50 | ????10 | ????6 |
| ?TH-OX?Si20 | ?1980 | ?102 | ????35 | ????300 | ????50 | ????10 | ????10 |
| ?TH-OX?Si21 | ?1900 | ?98 | ????33 | ????300 | ????50 | ????10 | ????8 |
| ?TH-OX?Si22 | ?1980 | ?98 | ????37 | ????300 | ????50 | ????10 | ????8 |
| ?TH-OX?Si23 | ?1900 | ?100 | ????35 | ????270 | ????50 | ????10 | ????8 |
| ?TH-OX?Si24 | ?1980 | ?100 | ????35 | ????350 | ????50 | ????10 | ????8 |
| ?TH-OX?Si25 | ?2000 | ?100 | ????35 | ????300 | ????50 | ????10 | ????8 |
Promptly, after the gap with the upper/lower electrode in the process chamber 101 102,104 is set at 35mm, when beginning the running of plasma processing apparatus, by ball screw framework 112, supporting mass 103 drops to the following chamber 101B of process chamber 101, and gate valve 106 is opened simultaneously, from the gateway, dummy wafer is moved into, be placed on the lower electrode 102.After wafer W is moved into, closing gate valve 106, gas extraction system 119 work simultaneously will be kept the specified vacuum degree in the process chamber 101.By exhaust, the aperture of APC valve 101D can change automatically with air displacement to be adjusted.At this moment, He gas is supplied with as back of the body gas, improved wafer W and lower electrode, the heat conductivity between electrostatic chuck 108 and wafer W specifically, to improve the cooling effectiveness of wafer W from gas introducing mechanism 115.
From treating-gas supply system 118, supply with Ar gas, CO gas, C with the flow of 300sccm, 50sccm, 10sccm and 8sccm respectively
4F
8Gas and O
2Gas.At this moment, because the processing gas pressure in the process chamber 101 is set at 100mTorr,, automatically adjust so the aperture of APC valve 101D adapts with handling gas delivery volume and air displacement.In this state,, complement each other, produce magnetron discharge, generate the plasma of handling gas with the effect of dipole subring magnet 105 when when high frequency electric source 107 applies the High frequency power of 2000W.Beginning owing to be naked silicon wafer, is not carried out etch processes.Naked silicon wafer is being carried out the stipulated time after (for example 1 minute) handle, carrying out operation opposite when moving into, the wafer W after handling is being taken out of in process chamber 101, under identical conditions, handling extremely the 5th follow-up dummy wafer.
Through the processing of dummy wafer, make the plasma processing apparatus stabilisation after, handle testing wafer.For initial testing wafer (is the 6th as wafer), carry out with the etch processes of Control Parameter as standard value.During carrying out this processing, by electric measurement device 107C and optical measurement device 120, repeatedly measure electric data and optical data as detecting data, these measured values are stored in the memory unit that does not illustrate in the drawings.According to these measured values, utilize arithmetic unit 206 to calculate mean value again.
When handling second testing wafer, the set point of High frequency power is changed to 1980W from 1500W, other Control Parameter is above-mentioned standard value, carries out etch processes.During this, same with initial testing wafer, measuring electric data and optical data, calculate mean value respectively as after detecting data.
When handling the 3rd later testing wafer, as shown in table 3, change and set each Control Parameter, each testing wafer is carried out etch processes, for each testing wafer, measure plasma reflection parameter (electric data, optical data) as detecting data, calculate its mean value respectively.
Matrix X by the mean value of this Control Parameter
a' and the matrix Y of the mean value of plasma reflection parameter
a', same with the modular form of above-mentioned (1), make the new modular form shown in following (5) (second operation).
X
a′＝K
a′Y
a′??…(5)
Secondly, make under the situation that changes Control Parameter under plasma processing apparatus 100B and plasma processing apparatus 100A the same terms, for plasma processing apparatus 100B, even unlike plasma processing apparatus 100A, experimentize, also can divert the modular form shown in above-mentioned (5) of plasma processing apparatus 100A.That is, in plasma processing apparatus 100B, under the condition identical, change Control Parameter, the matrix X of the purpose parameter in plasma processing apparatus 100B with plasma processing apparatus 100A
b' in, following (6) formula is set up.At this, be that matrix is X at the purpose parameter of plasma processing apparatus 100B
b' situation under, the modular form of above-mentioned (2) becomes the modular form of following (7) formula.
Relation from the modular form of the modular form of the plasma processing apparatus 100A shown in above-mentioned (1) formula and following (5) formula and the plasma processing apparatus 100B shown in above-mentioned (2) formula and following (7) formula can draw the modular form shown in following (8) formula.That is, because the regression matrix K in plasma processing apparatus 100A
a, new regression matrix K
a' and plasma processing apparatus 100B in regression matrix K
b, new regression matrix K
b' between, proportionate relationship (K
b'/K
a'=K
b/ K
a) set up, so K
b'=K
a' K
b/ K
aK in following (7) formula
b' in, use this relation, can obtain following (8) formula.
X
b′＝X
a′????????????????…(6)
X
b′＝K
b′Y
b′????????????…(7)
X
b′＝(K
a′K
b/K
a)Y
b′?????…(8)
Therefore, at matrix X
b' in, change under the new treatment conditions of Control Parameter, about plasma processing apparatus 100A, if modular form of obtaining (5), then, can make the new modular form that relates to plasma processing apparatus 100B (the 3rd operation) shown in (8) formula from the modular form (1) of the plasma processing apparatus 100A that obtains in advance and modular form (2) and the above-mentioned modular form (7) of plasma processing apparatus 100B.
That is, by obtaining the matrix X of mean value (setting data) with the Control Parameter that relates to the plasma processing apparatus 100A that under new treatment conditions, detects
a' and the matrix Y of the mean value (detection data) of plasma reflection parameter
a' related regression matrix K
a', then can make the new modular form (8) of plasma processing apparatus 100B, can utilize new modular form (8) to estimate the unit state of plasma processing apparatus 100B.This means, if according to experiment, make the above-mentioned modular form (5) that relates to plasma processing apparatus 100A, then for plasma processing apparatus 100B, do not experimentize even change, also can make the new modular form of above-mentioned (8) formula as plasma processing apparatus 100B.
These new modular forms (8) that make are stored in the resolution data memory unit 205 of plasma processing apparatus 100B also passable.Like this, when processing of wafers is carried out in the common running of plasma processing apparatus 100B, when from the value of mean value separately (detection data) a plurality of Control Parameter of prediction and calculation of a plurality of plasmas reflection parameters, can utilize the new modular form (8) of from resolution data memory unit 205, taking out.
In this case, utilize the value (setting data of being predicted) of the Control Parameter that predictive diagnosis control assembly 207 relatively predicted and the change allowed band of the setting data in fact in plasma processing apparatus 100B, set.Be judged as under the unusual situation, utilizing processing unit control assembly 225 to stop plasma processing apparatus 100B, simultaneously unusually by display unit 224, siren 226 reports.
As mentioned above, in the present embodiment, have first operation, second operation and the 3rd operation.First operation is, utilizes multivariable to resolve among each plasma processing apparatus 100A, 100B each and obtains in plasma processing apparatus 100A, 100B respectively the detection data (for example plasma reflection parameter) that detected by a plurality of transducers of each plasma processing apparatus 100A, 100B when moving according to first setting data (for example Control Parameter) and the dependency relation (K in (1) formula of first setting data
a, the K in (2) formula
b).Second operation is, utilize multivariable to resolve to obtain among each plasma processing apparatus 100A, 100B as the data that detect by a plurality of transducers of plasma processing apparatus 100A when moving according to the second new setting data (for example changing the scope new setting data different of Control Parameter) among the plasma processing apparatus 100A of benchmark processing unit and the dependency relation (K in (5) formula of second setting data with first setting data
a').The 3rd operation is, according to the dependency relation K among the plasma processing apparatus 100B that obtains in first operation
b, the dependency relation K among the plasma processing apparatus 100A that obtains in first operation
aWith the dependency relation K among the plasma processing apparatus 100A that obtains in second operation
a', obtain the dependency relation (K in (8) formula as second setting data among the plasma processing apparatus 100B of other processing unit beyond the benchmark processing unit and detection data
b'), again according to the dependency relation K that obtains like this
b', make the unit state of evaluation plasma processing apparatus 100B or prediction processing result's multivariable analytic modell analytical model formula ((8) formula).
Therefore, for the new setting data that produces because of new treatment conditions, in plasma processing apparatus 100A as benchmark, if wafer is carried out the experiment of plasma treatment, make modular form (5), then divert the new modular form (5) of plasma processing apparatus 100A, also can make at as the new modular form (8) of plasma device 100B for example of the processing unit beyond the processing unit of benchmark.Therefore, with regard to plasma processing apparatus 100B,,, also can make new modular form (8) even need not experimentize by new setting data owing to make new modular form.Thus, can alleviate the load that the modular form that relates to plasma processing apparatus 100B makes significantly.
In addition, in the present embodiment, the 3rd operation is according to respect to the dependency relation K among the plasma processing apparatus 100B that obtains in first operation
bSecond setting data and detect the dependency relation K of data
b' with respect to the dependency relation K among the plasma processing apparatus 100A that obtains in first operation
aSecond operation in the dependency relation K that obtains
a' proportionate relationship, obtain second setting data and the dependency relation K that detects data among the plasma processing apparatus 100B
b'.Thus, need not utilize multivariable to resolve, just can calculate the dependency relation K among the plasma processing apparatus 100B simply
b'.
In addition, in the present embodiment, make a plurality of Control Parameter that to control plasmoid and reflect that a plurality of plasmas reflection parameter correlations of plasmoid join, and make multivariable analytic modell analytical model formula.Specifically, utilizing plasma processing apparatus 100A, 100B, when being the purpose parameter with setting data (Control Parameter etc.), is explanatory variable to detect data (plasma reflection parameter etc.), makes multivariable analytic modell analytical model formula (1), (2).And, in new setting data,, use dependency relation K if make multivariable analytic modell analytical model formula (5) for plasma processing apparatus 100A
b' and setting data X
b', calculate the detection data (plasma reflection parameter, unit state parameter etc.) of plasma processing apparatus 100B, for plasma processing apparatus 100B, can make the multivariable analytic modell analytical model formula (8) of new setting data.
In addition, owing to utilize the PLS method to make multivariable analytic modell analytical model formula,, also can predict and estimate above-mentioned each parameter accurately even the experiment number is few.In addition, by analyzing as principal component, can synthetically estimate the operating condition of plasma processing apparatus 100B with the predicted value of plasma processing apparatus 100B.
In addition,,, carry out high-precision multivariable and resolve, can make multivariable analytic modell analytical model formula with few data owing to use the PLS method to ask the multivariable of the dependency relation of setting data and detection data to resolve.
Secondly, with reference to accompanying drawing, second execution mode of the present invention is described.Fig. 3 is the block diagram of all general configuration of the control system of expression present embodiment.This control system 300 by network 320 with main device 310, a plurality of plasma processing apparatus 100A ..., 100N couples together and constitutes.Because plasma processing apparatus 100A ..., the structure with shown in Figure 1 is identical respectively for 100N, omits its detailed explanation.In addition, plasma processing apparatus 100A ..., 100N has multivariable resolution component 200 as shown in Figure 2 respectively.In the present embodiment, multivariable resolution component 200, processing unit control assembly 225 and transmission receiving-member 150 shown in Figure 3 shown in Figure 2 plays the control device as processing unit.
As above-mentioned network 320, can with main device 310 and each plasma processing apparatus 100A ..., 100N etc. links together, and can carry out the twocouese communication, typically can enumerate public loop nets such as internet.As network 320, except the net of above-mentioned public loop, WAN (WAN (wide area network), Wide Area Network), LAN (LAN, LocalArea Network), IP-VPN loop nets such as (Internet Protocol-virtual private net, InternetProtocol-Virtual Private Network) also can.In addition, with the medium that are connected of network 320 can be FDDI (fiber distribution data interface, Fiber Distributed DataInterface) fiber optic cables of generation such as, the coaxial cable of Ethernet (Ethernet) or reverse wireless etc. to cable or IEEE802.11b etc., no matter wired or wireless, satellite network etc. also can.
When each plasma processing apparatus 100 carries out etch processes under desirable treatment conditions, in order to make the new modular form that is used for the evaluating apparatus state, by sending receiving-member 150, data necessary is delivered to desirable plasma processing apparatus 100 from main device 310, the burden in the time of can alleviating the multivariable resolution component 200 of utilizing this plasma processing unit 100 like this and make modular form.And, detect the new modular form that data draw by each when utilizing 100 of plasma processing apparatus to carry out actual processing of wafers, the evaluating apparatus state, according to its result, based on indication, utilize processing unit control assembly 225 to control plasma processing apparatus 100 from predictive diagnosis control assembly 207.
Secondly, utilize the processing of this control system 300 of description of drawings.Processing as control system 300, can enumerate as described in first execution mode, in plasma processing apparatus 100B, divert the new model that in plasma processing apparatus 100A, makes, make situation at the new model of plasma processing apparatus 100B.
The motion flow of the processing when Fig. 4～Fig. 6 represents to make the new model of plasma processing apparatus 100B.In more detail, Fig. 4～Fig. 6 represents with plasma processing apparatus 100A as the benchmark processing unit, with plasma processing apparatus 100B ..., the processing unit beyond the main device of 100N during, benchmark processing unit, benchmark processing unit as the processing unit beyond the benchmark processing unit motion flow.In Fig. 4～Fig. 6,, put down in writing with the representative that is treated to of plasma processing apparatus 100B as the processing unit beyond the benchmark processing unit.For plasma processing apparatus 100C ..., 100N, even when making new modular form, also carry out the action same with plasma processing apparatus 100B.
At first, as shown in Figure 4, ask each plasma processing apparatus 100A ..., 100N regression matrix K
a..., K
nBelow, concrete processing is described.
As the plasma processing apparatus 100A of benchmark processing unit, when being used to ask regression matrix K from input block 152A input
aSetting data (for example Control Parameter) when setting, in step S110, handle wafer W according to this setting data, obtain and detect data (for example plasma reflection parameter), with these setting datas, detection data, be delivered to main device 310 by network 320.
On the other hand, as for example plasma processing apparatus 100B of the processing unit beyond the benchmark processing unit, when being used to ask regression matrix K from input block 152B input
bSetting data (for example Control Parameter) when setting, in poly-S510 of step, handle wafer W according to this setting data, obtain and detect data (for example plasma reflection parameter), with these setting datas, detection data,, be delivered to main device 310 by network 320.
Then, in poly-S230 of step, main device 310 bases are from the program of the PLS method of multivariable analysis program memory unit 314, and are same with above-mentioned the 1st execution mode, utilize arithmetic unit 312 by setting data (purpose parameter) X
a..., X
nWith detection data (explanatory variable) Y
a..., Y
n, obtain each plasma processing apparatus 100A ..., the regression matrix K among the 100N
a..., K
n, be stored in the resolution data memory unit 316.Secondly, in poly-S240 of step, with these setting datas X
a..., X
n, detect data Y
a..., Y
n, regression matrix K
a..., K
n, by network 320, be delivered to each plasma processing apparatus 100A ..., among the 100N.
As the plasma processing apparatus 100A of benchmark processing unit, in poly-S120 of step, receive setting data X from main device 310
a, detect data Y
a, and regression matrix K
a, store as the modular form shown in above-mentioned (1) formula.In addition, as the plasma processing apparatus 100B of the processing unit beyond the benchmark processing unit, in poly-S520 of step, receive setting data X from main device 310
b, detect data Y
b, regression matrix K
b, store as the modular form shown in above-mentioned (2) formula.
Secondly, as shown in Figure 5, make new model as the plasma processing apparatus 100A of benchmark processing unit.The below concrete processing of explanation.
Then, same in the program of device 310 bases in poly-S330 of step with above-mentioned first execution mode from the PLS method of multivariable analysis program memory unit 314, utilize arithmetic unit 312 by new setting data (purpose parameter) X
a', new detection data (explanatory variable) Y
a', obtain the regression matrix K of each plasma processing apparatus 100A
a', be stored in the resolution data memory unit 316.Secondly, in poly-S340 of step, the setting data X that these are new
a', new detection data Y
a', new regression matrix K
a', by network 320, be delivered among each plasma processing apparatus 100A.
As the plasma processing apparatus 100A of benchmark processing unit, in poly-S140 of step, receive setting data X from main device 310
a', detect data Y
a' and regression matrix K
a', as new modular form storage.
Secondly, as shown in Figure 6, ask the modular form of handling the plasma processing apparatus 100B of processing unit in addition as benchmark.Owing to ask the new modular form of benchmark processing unit processing unit in addition according to the new modular form of benchmark processing unit, so in the processing unit beyond the benchmark processing unit, there is no need wafer is carried out plasma treatment again.The below concrete processing of explanation.
Then, main device 310 is in poly-S420 of step, by the regression matrix (K of the processing unit beyond the benchmark processing unit
b..., K
n), new regression matrix (K
b' ..., K
n'), the regression matrix (K of benchmark processing unit
a) and the new regression matrix (K of benchmark processing unit
a') proportionate relationship (K
b'/K
a'=K
b/ K
a), utilize arithmetic unit 312 to obtain new regression matrix (K respectively
b' ..., K
n').For example utilize K
b'=K
a' K
b/ K
aObtain the new regression matrix K shown in (7) formula among the plasma processing apparatus 100B
b'.Like this, when asking the new regression matrix of processing unit beyond the benchmark processing unit, do not need to carry out again the multivariable dissection process of PLS method etc., can obtain simply.
Secondly, main device 310 is in step S430, according to the modular form shown in above-mentioned (7) formula, by new setting data (X
b' ..., X
n'), new regression matrix (K
b' ..., K
n') calculate new detection data (Y
b' ..., Y
n'), be stored in the resolution data memory unit 316 setting data (the X that these are new
b' ..., X
n'), new regression matrix (K
b' ..., K
n'), new detection data (Y
b' ..., Y
n'), by network 320, deliver to respectively corresponding plasma processing apparatus 100B ..., among the 100N.
For example, in plasma processing apparatus 100B, in poly-S540 of step, receive new setting data (X from main device 310
b' ..., X
n'), new regression matrix (K
b' ..., K
n'), new detection data (Y
b' ..., Y
n'), as the storage of the new modular form shown in above-mentioned (8) formula, like this, in the processing unit beyond the standard apparatus, can make respectively the new modular form that is fit to processing unit.
Secondly, the processing of the control system during according to the new modular form that draws like this, evaluating apparatus state with reference to description of drawings.The motion flow of the main device when Fig. 7 represents to estimate the unit state of each plasma processing apparatus according to the new modular form that makes respectively and the motion flow of each plasma processing apparatus.
At first, in certain plasma processing apparatus 100, in poly-S610 of step,, store this permission mobility scale when input during at the permission mobility scale of the reference condition of setting data.This permission mobility scale is that the decision maker state is normal or unusual employed threshold value, for example, change be used to make new modular form setting data for example each Control Parameter during Control Parameter this for the maximum of standard value and the scope of minimum value.
Then, above-mentioned plasma processing apparatus 100, in poly-S620 of step, when the setting data that utilizes input block 152 input actual treatment wafers to use (reference condition for example are the standard value shown in the table 1),, wafer W is advanced plasma treatment according to this setting data, on each wafer W, obtain measured setting data and detect data, with these setting datas, detection data,, deliver in the main device 310 by network 320.
Then, in step S650, according to prediction setting data Xpre ' with respect to the setting data Xobs ' of reality whether in allowing mobility scale, and judge that above-mentioned plasma processing apparatus 100 is normal or unusual.For example, if prediction setting data Xobs ' with respect to the setting data Xpre ' of reality in allowing mobility scale, then be judged as normally, allow mobility scale if surpass, then be judged as unusual.Being judged as under the unusual situation, in step S660, for example the control assembly 225 by processing unit stops above-mentioned plasma processing apparatus 100, simultaneously, utilizes display unit 224, siren 226, and report is unusual.
Like this, main device 310 according to the data from each plasma processing apparatus, is obtained mean value, and carries out the multivariable dissection process, therefore, can alleviate the computing burden of each plasma processing apparatus significantly.In addition, because in each plasma processing apparatus, a large amount of setting datas that obtain when not needing temporary transient storage to carry out plasma treatment and detection data etc. do not need the multivariable analysis program yet, therefore can not want memory unit.Thus, the structure of each plasma processing apparatus can be simple, can suppress manufacturing cost.
In second execution mode, though utilize the situation of the new modular form judgment means state of each plasma processing apparatus one side.But be not to only limit to this because new modular form also is stored in the main device 310, so main device 310 1 sides judge each plasma processing apparatus 100A ..., 100N unit state also can.In this case, when being judged to be when unusual, with abnormality juding information be sent to each plasma processing apparatus 100A ..., also can among the 100N.According to unusual judgement information, by for example processing unit control assembly 225 stop each plasma processing apparatus 100A ..., 100N, utilize 226 reports of display unit 224, siren unusually also passable.Like this, in main device 310, can concentrate the unit state that monitors each plasma processing apparatus.
More than, with reference to description of drawings preferred implementation of the present invention, but the present invention only limits to these examples, much less this be.Those skilled in the art can carry out various changes or correction in the described scope of claims, but these all belong to technical scope of the present invention certainly.
For example, as the setting data in above-mentioned first and second execution modes, as when utilizing new modular form decision maker state in second execution mode, utilization also can by the setting data that Control Parameter measuring appliance 221 is measured when the plasma treatment wafer, in addition, utilize the setting data of importing by input block 152 also can.In this case, when all setting datas can be measured with Control Parameter measuring appliance 221, the setting data that utilization is measured by Control Parameter measuring appliance 221 also can, but when comprising the amount that can not be measured by Control Parameter measuring appliance 221 in setting data, it is effective utilizing the setting data of input.
In addition, in the multivariable of above-mentioned execution mode is resolved, though operative installations state parameter not can use the unit state parameter as purpose parameter or explanatory variable.In addition, in the above-described embodiment, when constructing modular form, though utilize High frequency power, processing gas flow, interelectrode gap and cavity indoor pressure Control Parameter as the purpose parameter, if the parameter that can control then is not to only limit to these.
In addition, as the unit state parameter, though use variable capacitor capacity, high frequency voltage, APC aperture, if measurable parameter of indication device state parameter then is not to only limit to these.In addition, though used electric data and optical data as the reflection plasma reflection parameter of reflection plasmoid based on plasma, if the parameter of reflection plasmoid then is not to only limit to these.In addition, though used high frequency voltage, the high-frequency current of first-harmonic and high order harmonic component (to 4 times of ripples), not to only limit to these as electric data.
And, utilize from pack into the dateout of parts (for example ス キ ヤ ト ロ メ ト リ) output of the wafer process in the plasma processing apparatus of measurement also passable as detecting data.Characteristic values such as the amount of pruning when specifically, utilizing processed film on the thickness, etched wafer of the film form on wafer and its inner evenness are also passable as detecting data.In addition, in the present embodiment, ask the data mean value of plasma reflection parameter on each wafer, use Control Parameter and unit state parameter on every wafer of this mean value prediction, but utilize the real-time plasma reflection parameter in the processing of wafers, also can real-time estimate Control Parameter and unit state parameter.
In addition, in the above-described embodiment, using has magnetic field parallel plate-type plasma processing apparatus, but so long as have the device of Control Parameter and plasma reflection parameter and/or unit state parameter, just can adopt the present invention.
The present invention according to above detailed description, a kind of multivariable analytic modell analytical model formula creating method of processing unit and the multivariable analytic method that processing unit is used can be provided, even each processing unit has the difference of treatment characteristic or treatment conditions, if make modular form for a processing unit, then this modular form can be used in congener other processing unit, do not need each processing unit is made modular form again, can alleviate the load that modular form makes.
Utilizability on the industry
The present invention for example goes in the control system of control device, processing unit of the multivariable analytic modell analytical model formula creating method of processing unit such as plasma processing apparatus, multivariable analytic method that processing unit is used, processing unit.
Claims (20)
1. the multivariable analytic modell analytical model formula creating method of a processing unit utilizes multivariable to resolve, and makes the unit state of estimating processing unit or the prediction processing multivariable analytic modell analytical model formula as a result the time, it is characterized in that: comprise following operation:
First operation is utilized multivariable to resolve in each processing unit each and is obtained when moving according to first setting data respectively in a plurality of processing unit by the detection data of a plurality of sensor of described each processing unit and the dependency relation of described first setting data;
Second operation, when with one among described each processing unit during as the benchmark processing unit, utilize multivariable to resolve, obtain in this benchmark processing unit when moving by the detection data of a plurality of sensor of described benchmark processing unit and the dependency relation of described second setting data according to the second new setting data; With
The 3rd operation, according to the described dependency relation in the described benchmark processing unit of obtaining in dependency relation in the described benchmark processing unit of obtaining in the dependency relation in described other processing unit of obtaining in described first operation, described first operation and described second operation, obtain described second setting data and the dependency relation that detects data in described benchmark processing unit other processing unit in addition, according to the dependency relation of obtaining like this, the unit state of described other processing unit of making an appraisal or prediction processing result's multivariable analytic modell analytical model formula.
2. the multivariable analytic modell analytical model formula creating method of processing unit as claimed in claim 1, it is characterized in that: described the 3rd operation comprises: according to the dependency relation with respect to described second setting data in described other processing unit of the dependency relation in described other processing unit of obtaining in described first operation and detection data, with the proportionate relationship of described dependency relation in the described benchmark processing unit of obtaining in described second operation with respect to the dependency relation in the described benchmark processing unit of obtaining in described first operation, obtain described second setting data in described other processing unit and detect the operation of the dependency relation of data.
3. the multivariable analytic modell analytical model formula creating method of processing unit as claimed in claim 1 is characterized in that: described multivariable is resolved and is utilized the partial least square method to carry out.
4. the multivariable analytic modell analytical model formula creating method of processing unit as claimed in claim 1, it is characterized in that: described each processing unit is a plasma processing apparatus.
5. the multivariable analytic modell analytical model formula creating method of processing unit as claimed in claim 1 is characterized in that:
Described each processing unit is a plasma processing apparatus,
Described setting data uses a plurality of Control Parameter of may command plasmoid, simultaneously, described detection data are used a plurality of plasmas reflection parameters of being selected from the reflection plasmoid, the multiple arrangement state parameter related with unit state, are reflected at least one or the parameter more than two in the parameter of processing.
6. multivariable analytic method that processing unit is used, it is the multivariable analytic method when utilizing the unit state of multivariable analyzing and evaluating processing unit or prediction processing as a result, it is characterized in that: comprise following operation:
First operation is utilized multivariable to resolve in each processing unit each and is obtained when moving according to first setting data respectively in a plurality of processing unit by the detection data of a plurality of sensor of described each processing unit and the dependency relation of described first setting data;
Second operation, when with one among described each processing unit during as the benchmark processing unit, utilize multivariable to resolve, obtain in this benchmark processing unit when moving by the detection data of a plurality of sensor of described benchmark processing unit and the dependency relation of described second setting data according to the second new setting data; With
The 3rd operation, according to the described dependency relation in the described benchmark processing unit of obtaining in dependency relation in the described benchmark processing unit of obtaining in the dependency relation in described other processing unit of obtaining in described first operation, described first operation and described second operation, obtain described second setting data and the dependency relation that detects data in described benchmark processing unit other processing unit in addition, according to the dependency relation of obtaining like this, the unit state of described other processing unit of making an appraisal or prediction processing result's multivariable analytic modell analytical model formula.
7. the multivariable analytic method that processing unit as claimed in claim 6 is used, it is characterized in that: described the 3rd operation comprises: according to the dependency relation with respect to described second setting data in described other processing unit of the dependency relation in described other processing unit of obtaining in described first operation and detection data, with the proportionate relationship of described dependency relation in the described benchmark processing unit of obtaining in described second operation with respect to the dependency relation in the described benchmark processing unit of obtaining in described first operation, obtain described second setting data in described other processing unit and detect the operation of the dependency relation of data.
8. the multivariable analytic method that processing unit as claimed in claim 6 is used is characterized in that: described multivariable is resolved and is utilized the partial least square method to carry out.
9. the multivariable analytic method that processing unit as claimed in claim 6 is used is characterized in that: described each processing unit is a plasma processing apparatus.
10. the multivariable analytic method that processing unit as claimed in claim 6 is used is characterized in that:
Described each processing unit is a plasma processing apparatus,
Described setting data uses a plurality of Control Parameter of may command plasmoid, simultaneously, described detection data are used a plurality of plasmas reflection parameters of being selected from the reflection plasmoid, the multiple arrangement state parameter related with unit state, are reflected at least one or the parameter more than two in the parameter of processing.
11. the multivariable analytic method that processing unit as claimed in claim 6 is used is characterized in that:
Described each processing unit is a plasma processing apparatus,
Described setting data uses a plurality of Control Parameter of may command plasmoid, simultaneously, described detection data use a plurality of plasmas reflection parameters of being selected from the reflection plasmoid, the multiple arrangement state parameter related with unit state, reflect at least one or the parameter more than two in the parameter of processing
Described multivariable analytic modell analytical model formula is to set the detection data that numerical value calculates and the dependency relation formula of described second setting data by the dependency relation in described other processing unit of obtaining in described the 3rd operation and described second.
12. the control device of a processing unit, it is arranged in the processing unit of handling handled object, and setting data according to the rules carries out the control of described processing unit, it is characterized in that:
It is connected on described processing unit and the network that links together as the processing unit and the main device of benchmark at least, is provided with the transmission receiving-member that can carry out exchanges data,
Utilize described transmission receiving-member, via described network, detection data and described first setting data by a plurality of sensor of described processing unit in the time of will moving based on first setting data are sent in the described main device, utilize described transmission receiving-member, via described network, from described main device, receive described first setting data that utilizes multivariable to resolve to obtain by described main device based on the data that sent and the dependency relation of described detection data
Utilize described transmission receiving-member, via described network, the second new setting data is sent to main device, utilize described transmission receiving-member, via described network, from described main device, receive described second setting data obtained by described main device based on the data that sent and based on the dependency relation of the detection data of this second setting data;
Dependency relation according to described second setting data that receives from described main device, make multivariable analytic modell analytical model formula,, estimate the unit state or the prediction processing result of described processing unit according to this multivariable analytic modell analytical model formula, according to its result, control described processing unit.
13. the control device of processing unit as claimed in claim 12 is characterized in that:
The dependency relation of described second setting data in the described processing unit is calculated by described main device based on following dependency relation, and these dependency relations are:
Utilize multivariable to resolve the dependency relation of described first setting data in the described processing unit of obtaining by described main device;
When the described benchmark processing unit that is utilized multivariable to resolve to obtain by described main device moves based on first setting data by the detection data of a plurality of sensor of described benchmark processing unit and the dependency relation of described first setting data;
When the described benchmark processing unit that is utilized multivariable to resolve to obtain by described main device moves based on the second new setting data by the detection data of a plurality of sensor of described benchmark processing unit and the dependency relation of second setting data.
14. the control device of processing unit as claimed in claim 13 is characterized in that: described multivariable is resolved and is utilized the partial least square method to carry out.
15. the checkout gear of processing unit as claimed in claim 12 is characterized in that: described processing unit is a plasma processing apparatus.
16. the control device of processing unit as claimed in claim 12 is characterized in that:
Described each processing unit is a plasma processing apparatus,
Described setting data uses a plurality of Control Parameter of may command plasmoid, simultaneously, described detection data are used a plurality of plasmas reflection parameters of being selected from the reflection plasmoid, the multiple arrangement state parameter related with unit state, are reflected at least one or the parameter more than two in the parameter of processing.
17. the control system of a processing unit, it has the control device of the processing unit of handling handled object being controlled based on the setting data of regulation, it is characterized in that:
It has by transmission receiving-member a plurality of described processing unit that is connected with network and the main device that is connected with described network,
Described main device; When the detection data that detect when a plurality of sensors that are received in from described a plurality for the treatment of apparatus via described network when moving based on the first setting data respectively in a plurality for the treatment of apparatus by described each treating apparatus and described the first setting data; Utilize multivariate analysis to obtain described the first setting data of receiving and the dependency relation of described detection data for each of described each treating apparatus; And via described network; The dependency relation of obtaining is sent in the corresponding treating apparatus
Described main device; When from described benchmark treating apparatus, being received in described each detection data that detected by a plurality of sensors of described benchmark treating apparatus when processing the treating apparatus as benchmark among the dress and moving based on the second new setting data and described the second setting data via described network; Described the first setting data that utilizes multivariate analysis to obtain to receive and described detection detect the dependency relation of data; And via described network; The dependency relation of obtaining is sent in the described benchmark treating apparatus
Described main device, when receiving described second setting data when via described network other processing unit beyond the described benchmark processing unit, according to the described dependency relation of resolving described first setting data in described other processing unit of obtaining by described multivariable, resolve the described dependency relation of described first setting data in the described benchmark processing unit of obtaining by described multivariable and resolve the described dependency relation of described second setting data in the described benchmark processing unit of obtaining by described multivariable, obtain described second setting data that received and based on the dependency relation of the detection data of this second setting data, and via described network, the dependency relation of being obtained is sent in described other processing unit
Described other processing unit, dependency relation according to described second setting data that from described main device, receives, make multivariable analytic modell analytical model formula, estimate the unit state or the prediction processing result of described processing unit according to this multivariable analytic modell analytical model formula, according to its result, control described processing unit.
18. the control system of processing unit as claimed in claim 17 is characterized in that: described multivariable is resolved and is utilized the partial least square method to carry out.
19. the control system of processing unit as claimed in claim 17 is characterized in that: described processing unit is a plasma processing apparatus.
20. the control system of processing unit as claimed in claim 17 is characterized in that:
Described each processing unit is a plasma processing apparatus,
Described setting data uses a plurality of Control Parameter of may command plasmoid, simultaneously, described detection data are used a plurality of plasmas reflection parameters of being selected from the reflection plasmoid, the multiple arrangement state parameter related with unit state, are reflected at least one or the parameter more than two in the parameter of processing.
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| Country | Link |
|---|---|
| JP (1) | JP4224454B2 (en) |
| KR (1) | KR100628392B1 (en) |
| CN (1) | CN100426471C (en) |
| TW (1) | TWI276162B (en) |
| WO (1) | WO2003105210A1 (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101374635B (en) * | 2005-12-20 | 2011-06-08 | 新东工业株式会社 | Method of estimating projection condition information by projection machine and device thereof |
| CN102511072A (en) * | 2009-06-30 | 2012-06-20 | 朗姆研究公司 | Seasoning plasma processing systems |
| CN108369916A (en) * | 2015-11-09 | 2018-08-03 | 应用材料公司 | Chip point-to-point analysis and data are presented |
| CN112585727A (en) * | 2019-07-30 | 2021-03-30 | 株式会社日立高新技术 | Device diagnostic device, plasma processing device, and device diagnostic method |
| US11036902B2 (en) * | 2015-06-19 | 2021-06-15 | Uptake Technologies, Inc. | Dynamic execution of predictive models and workflows |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| JP4678372B2 (en) * | 2004-06-29 | 2011-04-27 | 株式会社ニコン | Management method, management system, and program |
| JP4643392B2 (en) * | 2005-08-24 | 2011-03-02 | 東京エレクトロン株式会社 | Operating state determination method, operating state determination apparatus, program, and storage medium for plasma processing apparatus |
| US7286948B1 (en) * | 2006-06-16 | 2007-10-23 | Applied Materials, Inc. | Method for determining plasma characteristics |
| JP6546867B2 (en) * | 2016-03-10 | 2019-07-17 | 東京エレクトロン株式会社 | How to adjust the processing process |
| JP7034646B2 (en) * | 2017-09-25 | 2022-03-14 | 株式会社Ｓｃｒｅｅｎホールディングス | Anomaly detection device and anomaly detection method |
| JP6990634B2 (en) * | 2018-08-21 | 2022-02-03 | 株式会社日立ハイテク | State prediction device and semiconductor manufacturing device |
| WO2023162856A1 (en) * | 2022-02-22 | 2023-08-31 | 株式会社Ｓｃｒｅｅｎホールディングス | Substrate processing apparatus management system, assistance apparatus, substrate processing apparatus, inter-chamber performance comparison method, and inter-chamber performance comparison program |
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| JPH1194735A (en) * | 1997-09-22 | 1999-04-09 | Horiba Ltd | Quantitative analyzer for sample characteristic using spectrophotometry and multivariate analysis and analysis method using it |
| US6153115A (en) * | 1997-10-23 | 2000-11-28 | Massachusetts Institute Of Technology | Monitor of plasma processes with multivariate statistical analysis of plasma emission spectra |
| US6582618B1 (en) * | 1999-09-08 | 2003-06-24 | Advanced Micro Devices, Inc. | Method of determining etch endpoint using principal components analysis of optical emission spectra |
| US6917845B2 (en) * | 2000-03-10 | 2005-07-12 | Smiths Detection-Pasadena, Inc. | Method for monitoring environmental condition using a mathematical model |
| TW499702B (en) * | 2000-07-04 | 2002-08-21 | Tokyo Electron Ltd | Method for monitoring operation of processing apparatus |
-
2003
- 2003-06-05 WO PCT/JP2003/007132 patent/WO2003105210A1/en active Application Filing
- 2003-06-05 CN CNB038130823A patent/CN100426471C/en not_active Expired - Lifetime
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101374635B (en) * | 2005-12-20 | 2011-06-08 | 新东工业株式会社 | Method of estimating projection condition information by projection machine and device thereof |
| CN102511072A (en) * | 2009-06-30 | 2012-06-20 | 朗姆研究公司 | Seasoning plasma processing systems |
| US11036902B2 (en) * | 2015-06-19 | 2021-06-15 | Uptake Technologies, Inc. | Dynamic execution of predictive models and workflows |
| CN108369916A (en) * | 2015-11-09 | 2018-08-03 | 应用材料公司 | Chip point-to-point analysis and data are presented |
| CN108369916B (en) * | 2015-11-09 | 2022-09-09 | 应用材料公司 | Wafer point-to-point analysis and data presentation |
| CN112585727A (en) * | 2019-07-30 | 2021-03-30 | 株式会社日立高新技术 | Device diagnostic device, plasma processing device, and device diagnostic method |
| CN112585727B (en) * | 2019-07-30 | 2023-09-29 | 株式会社日立高新技术 | Device diagnosis device, plasma processing device, and device diagnosis method |
Also Published As
| Publication number | Publication date |
|---|---|
| JP4224454B2 (en) | 2009-02-12 |
| WO2003105210A1 (en) | 2003-12-18 |
| KR20050010021A (en) | 2005-01-26 |
| TWI276162B (en) | 2007-03-11 |
| CN100426471C (en) | 2008-10-15 |
| TW200404333A (en) | 2004-03-16 |
| KR100628392B1 (en) | 2006-09-26 |
| JPWO2003105210A1 (en) | 2005-10-13 |
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Granted publication date: 20081015 |