CN103698985B - The Forecasting Methodology of exposure energy parameter in a kind of photoetching trial run - Google Patents

Abstract

A Forecasting Methodology for exposure energy parameter in photoetching trial run, comprising: when newly trying out, the exposure energy parameter predicted is with reference to the same technique of same equipment, the exposure energy with interlayer structure; When change equipment is tried out, the exposure energy parameter predicted calculates based on the exposure energy ratio on often kind of equipment.When change equipment is tried out, its computing method comprise: step S1: the exposure energy matrix enumerating equipment, and the technological parameter in photoetching process; Step S2: carry out Condition Matching, and based on the exposure energy parameter calculation exposure energy parameter reference value Dose_Ref(n under described condition); Weights W t(n step S3: the exposure energy parameter Dose_Ref(n based on sample in database)) and time Day(n), obtain the exposure energy parameter Dose_JI of prediction.In photoetching trial run of the present invention, the Forecasting Methodology of exposure energy parameter is when carrying out exposure energy prediction, can increase substantially trial run success ratio, cost-saving.

Description

The Forecasting Methodology of exposure energy parameter in a kind of photoetching trial run

Technical field

The present invention relates to technical field of semiconductors, particularly relate to the Forecasting Methodology of exposure energy parameter in a kind of photoetching trial run.

Background technology

At present, automated process control (Automated Process Control, APC) is used widely in lithographic process controls.Such as, control to carry out exposure energy parameter regulation and control to ensure that production line critical size parameter meets technological requirement by automated process.

But, in actual production, because different product has measured height online, certainly will some problems have been produced.It mainly can not provide enough data to go to predict exact value owing to the product of short run.Especially, in the workshop of On-line Product amount complexity, there will be more trial run problem.Carrying out in the process of trying out, being difficult to prediction exposure energy parameter, so must test be passed through, to carry out exposure energy parameter calculating.Meanwhile, described test wafer also needs to do over again after test terminates.But the test wafer disqualification rate of doing over again is relatively high, increase production cost.

Therefore for prior art Problems existing, this case designer is by means of being engaged in the industry experience for many years, active research improves, trial run that the large batch of product of production line is be pilot is utilized to provide the prediction of exposure energy parameter, so there has been the Forecasting Methodology of exposure energy parameter in a kind of photoetching trial run of the present invention.

Summary of the invention

The present invention be directed in prior art, the product of described short run can not provide enough data to go to predict exact value, and the test run wafer disqualification rate of doing over again is relatively high, increase the Forecasting Methodology that the defects such as production cost provide exposure energy parameter in a kind of photoetching trial run.

For realizing the object of the present invention, the invention provides the Forecasting Methodology of exposure energy parameter in a kind of photoetching trial run, described method utilizes trial run that the large batch of product of production line is be pilot to provide the prediction of exposure energy parameter, specifically comprise: when newly trying out, the exposure energy parameter predicted is with reference to the same technique of same equipment, the exposure energy with interlayer structure; When change equipment is tried out, the exposure energy parameter predicted calculates based on the exposure energy ratio on often kind of equipment.

Alternatively, described when change equipment is tried out, the exposure energy parameter predicted calculates based on the exposure energy ratio on often kind of instrument, and its computing method comprise further:

Perform step S1: enumerate in relevant device the exposure energy matrix meeting photoetching process conditional parameter, described technological parameter comprises product related process, interlayer structure, photoresistance thickness, exposure illumination setting, critical size value, device type;

Perform step S2: carry out Condition Matching, and based on the exposure energy parameter calculation exposure energy parameter reference value Dose_Ref(n under above-mentioned condition);

Perform step S3: the exposure energy parameter Dose_Ref(n based on sample in database) weights W t(n) and time Day(n), obtain the exposure energy parameter Dose_JI of described prediction;

Wherein, described time Day(n) meet the sample of process conditions to the current time in characterization database, Pilot_time characterizes the time constant of setting;

Weight $\mathrm{Wt}\left(n\right)=2^{\frac{-\mathrm{Day}\left(n\right)}{\mathrm{Pilot}\_\mathrm{time}}};$

The exposure energy parameter of prediction $\mathrm{Dose}\_\mathrm{JI}=\frac{\mathrm{\ΣDose}\_\mathrm{Ref}\left(n\right)\·\mathrm{Wt}\left(n\right)}{\mathrm{\ΣWt}\left(n\right)}.$

In sum, in photoetching trial run of the present invention, the Forecasting Methodology of exposure energy parameter is when carrying out exposure energy prediction, can increase substantially trial run success ratio, cost-saving.

Accompanying drawing explanation

Figure 1 shows that the process flow diagram of the Forecasting Methodology of exposure energy parameter in photoetching of the present invention trial run.

Embodiment

By describe in detail the invention technology contents, structural attitude, reached object and effect, coordinate accompanying drawing to be described in detail below in conjunction with embodiment.

Refer to Fig. 1, Figure 1 shows that the process flow diagram of the Forecasting Methodology of exposure energy parameter in photoetching of the present invention trial run.The Forecasting Methodology of exposure energy parameter in described photoetching trial run, comprising: when newly trying out, the exposure energy parameter predicted is with reference to the same technique of same equipment, the exposure energy with interlayer structure; When change equipment is tried out, the exposure energy parameter predicted calculates based on the exposure energy ratio on often kind of equipment.Wherein, when change equipment is tried out, the exposure energy parameter predicted calculates based on the exposure energy ratio on often kind of equipment, and its computing method comprise further:

Perform step S1: enumerate in relevant device the exposure energy matrix meeting photoetching process conditional parameter, described technological parameter comprises product related process, interlayer structure, photoresistance thickness, exposure illumination setting, critical size value, device type;

Perform step S2: carry out Condition Matching, and based on the exposure energy parameter calculation exposure energy parameter reference value Dose_Ref(n under above-mentioned condition);

Perform step S3: the exposure energy parameter Dose_Ref(n based on sample in database) weights W t(n) and time Day(n), obtain the exposure energy parameter Dose_JI of described prediction.

Wherein, described time Day(n) meet the sample of process conditions to the current time in characterization database, Pilot_time characterizes the time constant of setting;

Weight $\mathrm{Wt}\left(n\right)=2^{\frac{-\mathrm{Day}\left(n\right)}{\mathrm{Pilot}\_\mathrm{time}}};$

The exposure energy parameter of prediction $\mathrm{Dose}\_\mathrm{JI}=\frac{\mathrm{\ΣDose}\_\mathrm{Ref}\left(n\right)\·\mathrm{Wt}\left(n\right)}{\mathrm{\ΣWt}\left(n\right)}.$

By the exposure energy prediction that the Forecasting Methodology of exposure energy parameter in photoetching of the present invention trial run is carried out, and known in repeatedly revision test, and the success ratio of trial run can reach 99.32%.

In sum, in photoetching trial run of the present invention, the Forecasting Methodology of exposure energy parameter is when carrying out exposure energy prediction, can increase substantially trial run success ratio, cost-saving.

Those skilled in the art all should be appreciated that, without departing from the spirit or scope of the present invention, can carry out various modifications and variations to the present invention.Thus, if when any amendment or modification fall in the protection domain of appended claims and equivalent, think that these amendment and modification are contained in the present invention.

Claims (1)

1. the Forecasting Methodology of exposure energy parameter in photoetching trial run, it is characterized in that, described method comprises:

When newly trying out, the exposure energy parameter predicted is with reference to the same technique of same equipment, the exposure energy with interlayer structure;

When change equipment is tried out, the exposure energy parameter predicted calculates based on the exposure energy ratio on often kind of equipment, and its computing method comprise further:

Perform step S1: enumerate in relevant device the exposure energy matrix meeting photoetching process conditional parameter, described technological parameter comprises product related process, interlayer structure, photoresistance thickness, exposure illumination setting, critical size value, device type;

Perform step S2: carry out Condition Matching, and based on exposure energy parameter calculation exposure energy parameter reference value Dose_Ref (n) under above-mentioned condition;

Perform step S3: based on weights W t (n) and time Day (n) of the exposure energy parameter Dose_Ref (n) of sample in database, obtain the exposure energy parameter Dose_JI of described prediction;

Wherein, meet the sample of process conditions to the current time in described time Day (n) characterization database, Pilot_time characterizes the time constant of setting;

Weight $Wt\left(n\right)=2^{\frac{-Day\left(n\right)}{Pilot\_time}};$

The exposure energy parameter of prediction $Dose\_JI=\frac{\mathrm{\Σ}Dose\_\mathrm{Re}f\left(n\right)\·Wt\left(n\right)}{\mathrm{\Σ}Wt\left(n\right)}.$