CN102662313A - Photoetching alignment parameter prediction method and photoetching method - Google Patents
Photoetching alignment parameter prediction method and photoetching method Download PDFInfo
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- CN102662313A CN102662313A CN2012101429481A CN201210142948A CN102662313A CN 102662313 A CN102662313 A CN 102662313A CN 2012101429481 A CN2012101429481 A CN 2012101429481A CN 201210142948 A CN201210142948 A CN 201210142948A CN 102662313 A CN102662313 A CN 102662313A
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Abstract
The invention provides a photoetching alignment parameter prediction method and a photoetching method. The photoetching alignment parameter prediction method comprises the following steps of: acquiring a first weighted average value and a first prediction accuracy parameter of a photoetching alignment parameter of other layers similar to the current layer of the same product on a machine; acquiring a second weighted average value and a second prediction accuracy parameter of the photoetching alignment parameter of the same layers of other products which have the same technical platform as the current product on the machine; acquiring a photoetching alignment daily observation result value and a third prediction accuracy parameter of the machine; and if the first prediction accuracy parameter is lower than a given threshold value, setting a photoetching alignment value to be equal to a number which accords with a formula of (the first weighted average value*the first prediction accuracy parameter +the second weighted average value*(1-the first prediction accuracy parameter)*the second prediction accuracy parameter)/(the first prediction accuracy parameter +(1-the first prediction accuracy parameter)*the second prediction accuracy parameter)-the result value*the third prediction accuracy parameter.
Description
Technical field
The present invention relates to field of semiconductor manufacture, more particularly, the photoetching method that the present invention relates to a kind of lithography alignment parameter prediction method and adopted this lithography alignment parameter prediction method.
Background technology
In the semiconductor crystal wafer processing technology, rework rate is unusual important index for lithographic process.About 13% the wafer of doing over again is because the new product test manufacture time has used inappropriate lithography alignment parameter to cause measuring exceeds standard.
Automatic feedback system is widely used in and is used for better controlling the lithography alignment parameter in the lithographic process.But, still there are a lot of problems for a factory that product category is a lot.Specifically, this is because the few product of amount can't provide enough data volumes to go to predict exactly the lithography alignment parameter of next product; And this situation also is the same for new product.
But if can't predict the lithography alignment parameter of new product exactly, the product of first (in the first batch) test manufacture will be done over again so.
Therefore, hope can provide a kind of model that can predict the lithography alignment parameter of new product exactly, lithography alignment parameter prediction method that the success ratio that will make new product test-manufacture thus improves widely and corresponding photoetching method.
Summary of the invention
Technical matters to be solved by this invention is to have above-mentioned defective in the prior art; The photoetching method that a kind of lithography alignment parameter prediction method is provided and has adopted this lithography alignment parameter prediction method; It can predict the model of the lithography alignment parameter of new product exactly, will make the success ratio of new product test manufacture improve widely thus.
According to a first aspect of the invention, a kind of lithography alignment parameter prediction method is provided, it comprises: obtain first weighted mean value and the first prediction accuracy parameter with the lithography alignment parameter of other level of the similar identical product of current level on this machine; Obtain second weighted mean value and the second prediction accuracy parameter with the lithography alignment parameter of the identical level of other products on this machine of the constructed platform of current production; Obtain the end value and the 3rd prediction accuracy parameter of the daily monitoring of lithography alignment of this machine; And if the new product of current prediction not the requirement photometry carve alignment value, be 0 then with lithography alignment predicted value indirect assignment.
Preferably, said lithography alignment parameter prediction method also comprises: if the first prediction accuracy parameter is higher than given threshold value, then the lithography alignment predicted value is set to equal: first weighted mean value-end value * the 3rd prediction accuracy parameter.
Preferably; Said lithography alignment parameter prediction method also comprises: if the first prediction accuracy parameter is lower than given threshold value, then the lithography alignment predicted value is set at and equals: (the first weighted mean value * first prediction accuracy parameter+second weighted mean value * (the 1-first prediction accuracy parameter) * second prediction accuracy parameter)/(the first prediction accuracy parameter+(the 1-first prediction accuracy parameter) * second prediction accuracy parameter)-end value * the 3rd prediction accuracy parameter.
Preferably, given threshold value is a variable constant.
Preferably, first weighted mean value and the employed database of the first prediction accuracy parameter thereof are this product ideal values of the alignment parameter of all similar levels in the certain hour section on this machine; Wherein, ideal value is that the alignment parameter of actual use deducts the resulting end value of amount of alignment measured value.
Preferably, all levels that is registered to same anterior layer is similar level, and all metal levels are similar level, and the porose layer of institute is similar level.
Preferably, to second weighted mean value, the alignment parameter of all product levels on this machine is classified as four types, if current machine coupling is only arranged, then these data are the first kind; If current machine and level coupling is only arranged, then these data are classified as second type; If current machine, level, technology platform coupling are only arranged, then these data are classified as the 3rd type; Similarly, if current machine, level, technology platform and anterior layer machine all mate, then these data are classified as the 4th type.
Preferably, calculate second weighted mean value according to said four types or said four a types part.
According to a second aspect of the invention, a kind of photoetching method that has adopted according to the described lithography alignment parameter prediction of first aspect present invention method is provided.
The invention provides a new model, this model predicts exactly the alignment parameter of new product based on the big matured product of amount; And, will make the success ratio of new product test manufacture improve widely thus.
Description of drawings
In conjunction with accompanying drawing, and, will more easily more complete understanding be arranged and more easily understand its attendant advantages and characteristic the present invention through with reference to following detailed, wherein:
Fig. 1 schematically shows the structure according to the alignment parameter predicted value of the embodiment of the invention.
Fig. 2 schematically shows the classification situation synoptic diagram according to the HS vector of the embodiment of the invention.
Fig. 3 schematically shows the classification situation explanation diagrammatic sketch according to the HS vector of the embodiment of the invention.
Fig. 4 schematically shows the classification situation synoptic diagram according to the CE vector of the embodiment of the invention.
Fig. 5 schematically shows the classification situation explanation diagrammatic sketch according to the CE vector of the embodiment of the invention.
Need to prove that accompanying drawing is used to explain the present invention, and unrestricted the present invention.Notice that the accompanying drawing of expression structure possibly not be to draw in proportion.And in the accompanying drawing, identical or similar elements indicates identical or similar label.
Embodiment
In order to make content of the present invention clear more and understandable, content of the present invention is described in detail below in conjunction with specific embodiment and accompanying drawing.
According to the present invention, a kind of lithography alignment parameter prediction method is provided, it comprises:
Obtain first weighted mean value (HS vector) and the first prediction accuracy parameter (RH) with the lithography alignment parameter of other level of the similar identical product of current level on this machine;
Obtain second weighted mean value (CE vector) and the second prediction accuracy parameter (RC) with the lithography alignment parameter of the identical level of other products on this machine of the constructed platform of current production; Wherein, term " constructed platform " refers to and meets identical design size rule and adopt identical manufacturing process.
Obtain the end value (QC vector) and the 3rd prediction accuracy parameter (RQ) of the daily monitoring of lithography alignment of this machine;
And, if the new product of current prediction not the requirement photometry carve alignment value, be 0 then with lithography alignment predicted value indirect assignment;
If the first prediction accuracy parameter (RH) is higher than given threshold value (Pilot_threshold), then the lithography alignment predicted value is set to equal: first weighted mean value-end value * the 3rd prediction accuracy parameter;
If the first prediction accuracy parameter (RH) is lower than given threshold value (Pilot_threshold), then the lithography alignment predicted value is set at and equals: (the first weighted mean value * first prediction accuracy parameter+second weighted mean value * (the 1-first prediction accuracy parameter) * second prediction accuracy parameter)/(the first prediction accuracy parameter+(the 1-first prediction accuracy parameter) * second prediction accuracy parameter)-end value * the 3rd prediction accuracy parameter.
Here, for example, given threshold value (Pilot_threshold) is a variable constant.
Specifically, Fig. 1 schematically shows the structure according to the alignment parameter predicted value of the embodiment of the invention.
JI_Predict comes from following three partial datas to new product lithography alignment parameter prediction value:
1. with weighted mean value---the HS vector of the lithography alignment parameter of other level of the similar identical product of current level on this machine; And RH is the prediction accuracy parameter of HS vector.
2. with weighted mean value---the CE vector of the lithography alignment parameter of the identical level of other products on this machine of the constructed platform of current production; And RC is the prediction accuracy parameter of CE vector.
3. the end value of the daily monitoring of lithography alignment of this machine---QC vector; And RQ is the prediction accuracy parameter of QC vector.
Concrete, the computing method of JI_Predict are following:
(1) if. the new product of current prediction not requirement photometry is carved alignment value, is 0 with lithography alignment value JI_Predict indirect assignment then, RH=1, RC=0.
(2) if. RH is higher than given threshold value Pilot_threshold, and then the lithography alignment value is set to JI_Predict=HS-QC*RQ.
(3) if. RH is lower than given threshold value Pilot_threshold, then the lithography alignment value is set JI_Predict=(HS*RH+CE* (1-RH) * RC)/(RH+ (1-RH) * RC)-QC*RQ.
Here, threshold value Pilot_threshold is a variable constant, can be according to the practice in factory optimization setting.
Fig. 2 schematically shows the classification situation synoptic diagram according to the HS vector of the embodiment of the invention.Fig. 3 schematically shows the classification situation explanation diagrammatic sketch according to the HS vector of the embodiment of the invention.Referring to figs. 2 and 3, for the HS vector, what time need explanation in addition as follows:
In specific embodiment, HS vector and its employed database of reliability forecasting parameters R H are this product ideal values of the alignment parameter of all similar levels (OVL_PERF) in the certain hour section on this machine.So-called ideal value OVL_PERF is meant that the alignment parameter of actual use when producing deducts the resulting end value of amount of alignment measured value.
In specific embodiment, can all data be sorted in chronological order, get many nearest (concrete stroke count value can be optimized according to actual conditions) data.Different according to each data with the matching degree of current predicted condition, data are divided into 4 types, and give its different Base parameter value (Pilot_Base1, Pilot_Base2) and Scale parameter value (Pilot_Scale1, Pilot_Scale2).These two values (Base parameter value and Scale parameter value) can be used when calculating weight.
In specific embodiment, can make weight relevant with the matching degree of time and data.Calculate each data weights W t=Scale*2^ (Day/Pilot_Time)+Base.Wherein time parameter Day is meant that now how long time gap that this data take place; Parameter Pilot_Time is a variable constant.
In specific embodiment; Can heavy n the maximum data of weighting calculate its weighted mean value, be output as
and make RH equal weight limit.
In specific embodiment, Pilot_Base1, Pilot_Base2, Pilot_Scale1, Pilot_Scale2 and Pilot_Time are variable constant, can be optimized according to practice in factory.
In specific embodiment, so-called similar level can define according to the situation of different factories.In general, for example, can think that all levels that is registered to same anterior layer is similar level, and all metal levels are similar level, the porose layer of institute is similar level.
Fig. 4 schematically shows the classification situation synoptic diagram according to the CE vector of the embodiment of the invention.Fig. 5 schematically shows the classification situation explanation diagrammatic sketch according to the CE vector of the embodiment of the invention.Concrete,, what time need as follows to explain for the CE vector with reference to figure 4 and Fig. 5 with ining addition:
In specific embodiment, to the CE vector, can the alignment parameter of all effective product levels on this machine be classified as four types, if current machine coupling is only arranged, then these data are the first kind; If current machine and level coupling is only arranged, then these data are classified as second type; If current machine, level, technology platform coupling are only arranged, then these data are classified as the 3rd type; Similarly, if current machine, level, technology platform and anterior layer machine all mate, then these data are classified as the 4th type.
In specific embodiment, can obtain mean value FEAS (1), FEAS (2), FEAS (3), the FEAS (4) of four types of data respectively, and give its different weight Pilot_Wt1, Pilot_Wt2, Pilot_Wt3 and Pilot_Wt4.Wherein, weight Pilot_Wt1, Pilot_Wt2, Pilot_Wt3 and Pilot_Wt4 are variable constants, can be according to the concrete condition optimization of factory.
In specific embodiment, the CE vector is the weighted mean of these four types of data mean values.Can all include calculating in all four types, also can only select weight the highest several types (< 4) to calculate.
According to the abovementioned embodiments of the present invention, new product lithography alignment parameter prediction system can be incorporated in the automatic feedback control system of factory.After the operator moved this system, it can provide the lithography alignment parameter of required new product, and exported this accuracy for predicting parameter (Pilot_RH and Pilot_RC) for operator's reference.
And in embodiment, if the prediction accuracy parameter is not high, the operator can select branch a slice to do test, but not the Direct Production entire block, to reduce rework rate.
Utilize the lithography alignment parameter of large-tonnage product to come to predict exactly the model of the lithography alignment parameter of new product, will make the success ratio of new product test manufacture improve widely thus.Specifically, will, manufacturing works find that the test manufacture success ratio can reach 99% according to the new product lithography alignment parameter prediction system of the embodiment of the invention after reaching the standard grade test.
It is understandable that though the present invention with the preferred embodiment disclosure as above, yet the foregoing description is not in order to limit the present invention.For any those of ordinary skill in the art; Do not breaking away under the technical scheme scope situation of the present invention; All the technology contents of above-mentioned announcement capable of using is made many possible changes and modification to technical scheme of the present invention, or is revised as the equivalent embodiment of equivalent variations.Therefore, every content that does not break away from technical scheme of the present invention, all still belongs in the scope of technical scheme protection of the present invention any simple modification, equivalent variations and modification that above embodiment did according to technical spirit of the present invention.
Claims (9)
1. lithography alignment parameter prediction method is characterized in that comprising:
Obtain first weighted mean value and the first prediction accuracy parameter with respect to the lithography alignment parameter of other level on this machine like the current layer second phase of identical product;
Obtain second weighted mean value and the second prediction accuracy parameter with the lithography alignment parameter of the identical level of other products on this machine of the constructed platform of current production;
Obtain the end value and the 3rd prediction accuracy parameter of the daily monitoring of lithography alignment of this machine; And if the new product level of current prediction not the requirement photometry carve alignment value, be 0 then with lithography alignment value indirect assignment.
2. lithography alignment parameter prediction method according to claim 1 is characterized in that also comprising:
If the first prediction accuracy parameter is higher than given threshold value, then the lithography alignment predicted value is set to equal: first weighted mean value-end value * the 3rd prediction accuracy parameter.
3. lithography alignment parameter prediction method according to claim 1 and 2; It is characterized in that also comprising: if the first prediction accuracy parameter is lower than given threshold value, then the lithography alignment predicted value is set at and equals: (the first weighted mean value * first prediction accuracy parameter+second weighted mean value * (the 1-first prediction accuracy parameter) * second prediction accuracy parameter)/(the first prediction accuracy parameter+(the 1-first prediction accuracy parameter) * second prediction accuracy parameter)-end value * the 3rd prediction accuracy parameter.
4. lithography alignment parameter prediction method according to claim 1 and 2 is characterized in that given threshold value is a variable constant.
5. lithography alignment parameter prediction method according to claim 1 and 2; It is characterized in that first weighted mean value and the employed database of the first prediction accuracy parameter thereof are this product ideal values of the alignment parameter of all similar levels in the certain hour section on this machine; Wherein, ideal value is that the alignment parameter of actual use deducts the resulting end value of amount of alignment measured value.
6. lithography alignment parameter prediction method according to claim 5 is characterized in that all levels that is registered to same anterior layer is similar level, and all metal levels are similar level, and the porose layer of institute is similar level.
7. lithography alignment parameter prediction method according to claim 1 and 2 is characterized in that, to second weighted mean value, the alignment parameter of all product levels on this machine is classified as four types, if current machine coupling is only arranged, then these data are the first kind; If current machine and level coupling is only arranged, then these data are classified as second type; If current machine, level, technology platform coupling are only arranged, then these data are classified as the 3rd type; If current machine, level, technology platform and anterior layer machine all mate, then these data are classified as the 4th type.
8. lithography alignment parameter prediction method according to claim 7 is characterized in that, calculates second weighted mean value according to said four types or said four a types part.
9. one kind has been adopted the photoetching method according to the described lithography alignment parameter prediction of one of claim 1 to 8 method.
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