# Subsequent Corrections were Made to data some slides. See file: 

# “Updated Slides to 11172012 presentation 01 Feb 2012”

• As a result of additional data analysis work which took place after the 11/17/2011 meeting, several corrections were made to the calculations, resulting in changes to the tables and data in slides 11, 12, 23, 24, 30, 31, 32, and 33 in this deck (10, 11, 22, 23, 

### 29, 30, 31, and 32 in the original file without this explanation slide). The corrected or updated slides are provided in a separate file titled “Corrected Slides for the 11172011 EPA SIA Etch Meeting” and the corrected slides are annotated with the corresponding slide number of the original slide. The major changes were made in gas usage, 300mm, 2010, 2 factor model. The changes in the tables and data did not result in changes to the text or the conclusions.

– Originally, C3F8 was not carried through the calculations, both for etch emissions and other emissions. It is now included.

– Lower and upper emission factors were calculated using 1.92 * standard error. This is corrected to 1.96 * standard error.

– The 2010 300 mm gas usage data input source for the 2 factor model had a formatting error, causing incorrect gas usage input values. The original data had missing gas usage. This has been corrected.

– There were two typos in the use of the byproduct emission factors for Wafer cleaning and CVD. These have been corrected. The total FGas use went up with these corrections. This means that the % that is etch and etch byproducts went down.

1

## Accelerating Sustainable Manufacturing

Copyright ©2010 Advanced Materials Research Center, AMRC, International SEMATECH Manufacturing Initiative, and ISMI are servicemarks of SEMAT ECH , and the SEMATECH logo are registered servicemarks of SEMATECH, Inc. All other servicemarks and trademarks are the property of their respective owners. 

# ISMI/SIA Alternative to Recipe 

# Specific Testing
Laurie Beu Consultant to ISMI 

# Michael Haslam Predictum, Consultant to ISMI 

# November 17, 2011

# Contents

• Disclaimer

• Key Takeaways

• Precision and Accuracy Analysis

– Data Sets for Comparison

– Emissions Calculations

– Emission Factors Tables

• Tier 2b

• Tier 2c

• 2 Parameter

• 3 Parameter



### – Calculating Error

– Emission Factor Error Calculations

– Replacing missing factors

– Gas Apportioning Error

– Industry level comparisons

– Facility level error curves

– Byproduct Methodology Comparisons 

## • Industry Proposals to Address Other Outstanding Issues

– 2 parameter default emission factors

– Combine etch and wafer cleans

– Gas apportioning

– Abatement

– Ensuring representativeness



### – Byproducts

– Process for updating emission factors

3 November 17, 2011

# Disclaimer

• Disclaimer of Liability

– This presentation has been prepared upon request using preliminary survey results and is subject to change without notice at the authors’ discretion for reasons including, without limitation, receipt of additional information and continued analysis of survey results

.

– The authors’ and presenters’ intent is to report survey findings and to provide non - partisan analysis to the intended audience

. This presentation is not intended to constitute lobbying, and shall not be interpreted as lobbying

.

– This information is provided " as is "

. The authors, contributors and presenters of this information disclaim any and all loss or liability, incurred either directly or indirectly as a consequence of applying or using the information presented herein

. Neither ISMI, nor SIA, nor any of their members, employees or officers, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information disclosed or discussed herein

.

– The estimates, assessments, analyses, views and opinions of document authors and contributors and the presenters, whether expressed herein or expressed orally during the presentation and related meetings, do not necessarily state or reflect those of any individual entity or company, including, without limitation, ISMI, the SIA or any of their member companies

.

• Disclaimer of Forward

- looking Statements

– Portions of this presentation contain forward

- looking statements that are based on the authors’ and contributors’ current expectations, estimates, projections and assumptions

. These statements are based on assessment of uncertain factors and therefore are not guarantees of future events and outcomes

. Actual future results may differ materially from what is forecast

. All forward

- looking statements speak only as of the date of this presentation

.

– All related written and oral forward

- looking statements attributable to the authors, presenters, ISMI, SIA or any person acting on behalf of those entities are qualified by the cautionary statements in this section

.

– The authors, contributors and presenters do not undertake any obligation to update or publicly release any revisions to forward

- looking statements to reflect events, circumstances or changes in expectations after the date

4 November 17, 20115 

# Key Takeaways

November 17, 2011 5 

### • This analysis was undertaken to identify the best etch emissions calculation model. The 2 factor model is the most appropriate method to estimate semiconductor etch emissions.

– Improved precision vs. EPA Tier 2c and 2d;

– Avoids technical feasibility and intellectual property issues associated with current Subpart I Rule;

– Provides additional data that feed into the IPCC process to ensure increased accuracy of semiconductor emissions estimates world

- wide.



### • The ISMI database is sufficiently robust to provide representative emissions factors for Gas/Wafer Size.

– 976 data sets.

– Emission factors provided for 99.7% of etch gas usage.



### • ISMI expects additional etch data sets in 2012.

• Industry recommends allocating byproducts using both single

- and multi

- gas data.

• Wafer cleans do not differ substantively from etch and do not warrant a separate process category.

• The AP

- 42 update process can be used to update emission factors and develop industry factors for future 450mm wafer fabs.

• Industry has developed proposals to address technical feasibility and cost concerns of gas apportioning and POU abatement uptime tracking and testing.

# Precision and Accuracy

Analysis

6 November 17, 2011

# Precision and Accuracy 

# Analysis Overview

• For consistent evaluation of errors, we calculated emission factors and relative errors for each data set.

– IPCC Tier 2b

– EPA Tier 2c

– ISMI Refined (2 models)



### • 2009 and 2010 F

- gas usage data collected from 12 fabs.

– 7

- 200 mm

– 5

- 300 mm



### • Emissions estimated for the 12 fabs using the four different emission factor data models.

• Emissions and error are calculated for four models, using the same modeling and error methodology.

– Upper and lower estimates on emissions are calculated and compared for these four.

– Industry level and Facility level are calculated.



### • A similar comparison is done with Tier 3.

7 November 17, 2011

# Precision and Accuracy Analysis Overview (cont’d.)

• Separately, etch emissions (main and byproduct) are then calculated and compared for these emissions factors sets at the industry level:

– IPCC Tier 2b (using published EF as listed in IPCC 2006),

– EPA Tier 2c (using published EF as listed in Subpart I),

– ISMI 2

- and 3

- factor models.



## • This was repeated for Tier 3 facilities.



## • All methods use EPA Tier 2c defaults to calculate non

- etch emissions (i.e., emissions from chamber cleans and wafer cleans).

• Byproduct assignment methodologies are compared, for the ISMI 2 factor model, when the source data contains:

– Single

- gas etches only;



### – Both single

- and multi

- gas etches.

8 November 17, 2011

# Summary: Data Sets & Models 

# for Comparison
Name Data Model(s) Data Sets IPCC Tier 2B Original IPCC Tier 2B only 1 Factor 79
EPA Tier 2C Total NODA data set

– IPCC

Tier 2B + data submitted to EPA in 2010 2 Factor 93

ISMI Refined EPA Tier 2C data + ISMI

collected data with duplicates removed 2 Factor 3 Factor 976

Tier 3 3 Facilities

– one 200 mm,

two 300 mm

November 17, 2011 9 

### • Data sets used to calculate EF and relative errors.

# Emissions Calculations

For each gas: CO2e = Gas Used (kg) * Emission Factor * GWP100 +

Gas Used (kg) * Byproduct Emission Factor * Byproduct GWP100

... (repeat for additional byproducts)
MTCO2e = CO2e/1000

• Upper and Lower possible CO2e are calculated by

– replacing the emission factors with the appropriate upper and lower possible emission factors



## – Replacing gas used by upper and lower gas used, if appropriate

10 November 17, 2011

# Calculated Emission Factor 

# Tables
– 2 Parameter (partial view)

11 November 17, 2011

# Calculated Emission Factor Tables
– 3 Parameter (partial view)

ATTORNEY WORK PRODUCT PREPARED FOR LITIGATION; PRIVILEGED & CONFIDENTIAL ISMI Confidential
12 November 17, 2011

# Calculated EF Relative Errors

13

November 17, 2011 

## • Calculated emission factors and relative errors shown for:

– IPCC Tier 2b

– EPA Tier 2c

– ISMI Refined 2

- Factor Model

• Due to larger data set, ISMI 2

- factor EF have smaller relative errors.

# Calculating Error

• Error calculations consist of:

– Error or uncertainty in the etch emissions factors.

– Error or uncertainty in the etch gas apportioning for 3 factor and Tier 3 models.



# • And:

– Dealing with missing emissions factors.

– Dealing with emissions factors that have no error terms. Example: a single data set for a gas/wafer size or 

# gas/wafer size/film.

14 November 17, 2011

# Emission Factor Error 

# Calculations
Lower and upper possible emission factors are calculated as 

### Industry Level:

• +/

- 1.96 * Std Dev / sqrt (N)

• Where:

– N is the number of data sets for the specific factor.

– Std Dev is the standard deviation of the data sets associated with that factor

.

– This is equivalent to the standard error ( std err). 

### which is equivalent to:



### • +/

- 1.96 * std err of the mean emission factor Data Level:

• +/

- 1.96 * Std Dev Facility Level:

• +/

- 1.96 * Std Dev / sqrt (Modified N)



### • Where:

– Modified N ranges between 1 and N of the appropriate data set for that factor, based on how close industry level models facility level.

15 November 17, 2011

# Calculating Error: Initially Choosing 

# Error Propagation vs. Monte Carlo

• ISMI used error propagation, accepted method in IPCC guidance, to estimate the precision of the average etch emission factors that 

## underlie the estimates of industry

- and facility

- level emissions.

– The mean value of X is approximately normally distributed, even if X itself is not.



## • IPCC gives guidelines for its applicability, but says: “In practice, however, the approach will give informative results even if this criterion (relative errors <0.3 of the mean) is not strictly met and some correlations remain.”

• The analytical process has been very dynamic, considering different data sets, emission factors, emission models and 

## estimation methods.

– The error propagation model has flexibility to quickly test different approaches.

– The Monte Carlo was considered too slow to produce results for multiple analyses on a compressed timeline.

16 November 17, 2011

# Calculating Error: Initially choosing 

# Error Propagation vs. Monte Carlo

• P urpose of precision estimates is to compare and rank different etch estimation models. E rror propagation method 

# provides an appropriate level of rigor for this purpose.

• Monte Carlo method has its own limitations:

– Requires simplifying assumptions to deal with complex distributions of the emission factor data.

– Offers a different, but not necessarily better, approach to analyzing relative precision and accuracy.



# • P erform a limited number of Monte Carlo analyses once a consensus has developed.

– Purpose will be to confirm the precision estimates made using 

## error propagation

.

17 November 17, 2011

# Replacing Missing Factors: 

# Main Gas

• Missing emissions factors:

– E mission factor is set to 1 (based on Final Rule)



## – Upper possible emission factor is set to 1

– Lower possible emission factor is set to 0



# • Emission factor exists but missing lower and upper due to no error terms: (following a similar objective as above):

– For emission factors > 0.50

• Upper Possible = 1

• Lower Possible = 2 * Emission Factor

– 1



## – For emission factors <= 0.50

• Upper possible = 2 * Emission Factor

• Lower possible = 0



## – Std Dev is set to the Emission Factor / 1.96

18 November 17, 2011

# Replacing Missing Factors: 

# Byproducts

• Missing emissions factors:

– Emission factor is set to 0 (based on Final Rule).

– Upper possible emission factor is set to 0

– Lower possible emission factor is set to 0



# • Emission factor exists but missing lower and upper due to no error terms:

– Same procedure as used for the main emission factors

19 November 17, 2011

# Gas Apportioning Error

• Data generated from 8 facilities for 2009 and 

# 2010.

– 3 of these facilities are included in the 12 used for precision/accuracy analysis.

– 105 data points

.


# • Error calculation based on modeled consumption 

# versus actual consumption for each year.

– Actual consumption based on removing heel from purchased gas.

– Apportioning error calculated by gas type.



# • Apportioning error shows difficulty in meeting validation requirement of 5%.

20 November 17, 2011

# Gas Apportioning Error

• Std. Dev. is high because it is difficult to model gas 

# consumption in a semiconductor facility.

• Gas apportioning is required for ISMI 3

- factor and Tier 3 models and is an additional source of uncertainty.

21



## Table of % Error by Etch F

- gas.

November 17, 2011

# Data Sets & Models for 

# Comparison

22 Methodology Emissions

Factor Dataset Number of

Facilities Evaluated Number of

300 mm Facilities EF Model

Factors EF

Rounding EF

Uncertainty Apportioning

Uncertainty

IPCC Tier 2b IPCC 2006 12 5 Gas 1 digit Yes No EPA Tier 2c (Subpart I Small Facility Method IPCC 2006

and 2010 NODA Data 12 5 Gas and Wafer Size 2 digit Yes No

SIA/ISMI Gas and Wafer Size Method IPCC 2006,

2010 NODA, and ISMI Data 12 5 Gas and Wafer Size None Yes No

SIA/ISMI Gas, Wafer Size, and 4 Film Category Method IPCC 2006,

2010 NODA, and ISMI Data 12 5 Gas, Wafer Size and 4 etch Films: Silicon, Silicon Oxide, Nitride, and Metal None Yes Yes

Tier 3 Model Intel

Specific Data 3 2 Process Type None Yes Yes

November 17, 2011

# Etch Error Comparison Across 

# Models - Industry Level

23 November 17, 2011 

## • The ISMI Refined 2 factor model achieves substantially better precision for etch than the earlier IPCC Tier 2b and EPA Tier 2c methods and is 

## better than the ISMI Refined 3 factor model.

Notes: Upper and lower % error are vs. etch total F

- gas.

ISMI Refined uses full set of single

- and multi

- gas byproduct data. Calculated, not published, emission factors.

# Etch Error Comparison Across 

# Models
– EF Data Level

24 November 17, 2011 

## • Gas usage at a facility level used to determine error based on std dev of the individual emission factors. Note: ISMI Refined uses full set of single

- and multi

- gas byproduct data.

# From Individual Data to Facility to 

# Industry Error: Summary

• Industry Level Error: ~ +/

- 20%

• Data Level Error: ~ +/

- 84%

• Facility level error lies between the above two points:

– Each facility will have an effective subset of the industry database; less than the industry but greater than a single point.



## – This allows a calculation of error at the facility level using a Modified N or Number of Data sets in the error calculation.

– Note: Facility error can never be better than industry error. Facility Level error Calculation:

• +/

- 1.96 * Std Dev / sqrt (Modified N)



## • Where:

– Modified N ranges between 1 and N of the appropriate date set for that factor, based on how close industry level models facility level

.

25 November 17, 2011

# From Individual Data to Facility to 

# Industry Error: Error Curve

26 November 17, 2011 

## • Data point aggregation as a % of industry level.

• Facility is an aggregation of individual data points (tool/gas combinations).



# Individual Data

Facility Industry

# Estimation of the Facility 

# Level Etch Error

• ISMI has collected a set of etch data which is representative of equipment type/gas type/wafer size installed base.

– Current distribution is provided on next slide.



### – Analyzing results vs. F

- gas usage to determine if additional data is necessary (see representativeness discussion).



## • Each facility has a subset of the etch equipment type/gas type/wafer size data set that makes up the industry wide database.

– To the extent that the ISMI database contains data for the equipment/gas type/wafer 

### size, it reduces the Facility Level uncertainty towards the National level uncertainty.

– The chart shows that if there is a 20

- 30% facility level coverage the uncertainty will be less than the 30% Subpart L facility level threshold.

– ISMI data evaluation is intended to assure that 20

- 35% facility level coverage is achieved.



## • Demonstrates that the 2 factor model provides acceptable facility level accuracy.

November 17, 2011

## • 4 primary suppliers of etch equipment: TEL, Applied Materials, LAM, Hitachi.

• ISMI database provides emission factors for 99.7% of etch F

- gas use. 

# Industry Coverage of ISMI Database

November 17, 2011

# Now shifting from calculated emission factors to published factors for IPCC Tier 2b and 

# EPA Tier 2c.

29

# Comparison of Emissions by 

# Etch Model: Industry Level

30 November 17, 2011 

## • 300mm F

- gas emissions are substantially reduced compared to 200mm because lower F

- gas emission chamber cleans have been implemented at 300mm.

– Etch emissions are a higher percent of all F

- gas emissions at 300 mm. Note: ISMI Refined uses full set including single

- and multi

- gas byproduct data.

# Comparison of Emissions for 

# Tier 3 Facilities Only

31 November 17, 2011 

## • For the 200mm fab, the ISMI 2 factor model is closest to the Tier 3 result.

• For the 300mm fabs, all four methods are similar in comparison to Tier 3.

• ISMI 2

- factor model has the best precision of the methods presented here.

Notes: Only facilities with Tier 3 data are used here as proxy for EPA Tier 2d. 200 mm: 1 facility 300 mm: 2 facilities ISMI Refined uses full set including single

- and multi

- gas byproduct data. Emissions are reported in MTCO2e.

# Etch Error Comparison Across Models: Tier 3 Facilities

32 November 17, 2011 

## • Tier 3 variability is driven by gas apportioning.

• The additional error introduced by apportioning offsets any gain in precision from the use of 3

- factor, Subpart I Tier 2d, and IPCC Tier 3. Notes: Only facilities with Tier 3 data are used here as proxy for EPA Tier 2d. 200 mm: 1 facility 300 mm: 2 facilities ISMI Refined uses full set including single

- and multi

- gas byproduct data. Emissions are reported in MTCO2e.

# Byproduct Methodology Comparisons
– ISMI 2 Factor

33 November 17, 2011 

## • ISMI 2 factor includes single

- and multi

- gas byproducts data.



## • For comparison:

– New byproduct emissions factors are calculated using only single

- gas byproduct data (multi

- gas data excluded).

– Byproduct emissions are calculated.

# Precision and Accuracy 

# Analysis Conclusions

• The etch emissions factor database is robust and representative:

– Emission factors are provided for 99.7% of etch F

- gas usage.



### – Anticipate additional data will be available in early 2012.



## • The precision and accuracy analysis provides a substantive assessment of the relative errors of the etch models:

– Analysis done on 12 facilities with two years each of use data

- provides an accurate representative of US fab operations. 

### Analysis finds the Gas/Wafer Size model provides the best level of accuracy and precision when considering all errors.

– Use of two factor model is logical given the consistency, by gas, of the plasma physics and chemistry.

34 November 17, 2011

# Recommendations

• Adopt the ISMI Refined 2 Factor Model for 

# etch.

• Include both single

- and multi

- gas byproducts in calculation of byproduct factors.

• Follow

- up with Monte Carlo calculation once a consensus has developed on emission factor 

# data and methods.

35 November 17, 2011

# Industry Proposals to Address

Other Outstanding Issues

36 November 17, 2011

# Apportioning Validation: 

# 2 Alternatives

• SIA will propose a hierarchy of options by which to perform apportionment

– Examples:

• Gas use based on systems which supply a single emissions categories

• Use of gas MFC or valve data to apportion across a categories on a single supply system.

• Use of maximum gas use by tool to apportion over a system



### – Estimated Apportioning Error will Be Determined for Each Option.

– Options will be Exercised From Least to Greatest Apportioning Error.



## • Increase validation error for highest use etch gas to 20%.

– Preliminary error assessment work indicates wide range of errors.

• Gas manufacturing facilities are allowed an uncertainty of 30%

• SIA/ISMI will provide examples of apportioning error

– At a Facility Level

– Around Groups of Tools:

» Stack Testing Analysis

» Others



## • Further discussion of two options and their proposed supporting data is needed.

37 November 17, 201138 

# ISMI Database Emission 

# Factor Representativeness

• ISMI Has Collected Over 976 Etch Emissions Factors

– 10 Times the Data in the NODA and IPCC Database

– Broad Coverage of Etch Process Types and Gases



### – EPA has Acknowledged Improvement in Data

– Statistical Analysis of Data Shows Good Correlations with:

• 2 Factor Model: Gas Type and Wafer Size

• 3 Factor Model: Gas Type, Wafer Size, and Film Type

• Detailed Analysis Provided in 8/11/2011 Presentation to EPA.



### • Tool Manufacturers Use Similar Process Chemistry to Accomplish the Various Etches

– F

- Gas Emissions and Byproducts Driven by the Interaction of the Chemical and Physical Properties and Interactions Between the Plasma and the Gas or Gas Mixtures.

– Gas Type and Wafer Size Serve as Proxies for Other Process Parameters

• Equipment Mfr. & FR Generator is Addressed by Gas Type

• Wafer Size Addresses Equipment Age



### – Etch Processes are the Same for Memory, Logic, and Other Product Types

• Manufacturers do not Make Specific Tools for A Product Type

• Increasingly, Memory and Logic Functions are Integrated.

• Cross Industry Collaboration in Process Development for 300 mm Equipment

– Sematech

– Multi

- Company Development Consortiums

November 17, 2011

# ISMI Database Emission Factor 

# Representativeness

• In response to EPA’s question, ISMI has assessed methods to demonstrate representativeness.



# • ISMI is surveying U.S. fabs to identify what F

- gases are used on the four major suppliers’ equipment.

– Survey will identify data gaps.

– Coupled with F

- gas usage, results can be used to prioritize any data gaps and collect additional etch emissions data as necessary.

November 17, 201140 

# Emission Factor Representativeness

• ISMI database contains emissions data from all major etch supplier toolsets.

• Emission factors derived from ISMI database cover 99.7% of etch F

- gas usage.

• ISMI anticipates additional data will be added to the database in early 2012.

40 November 17, 2011

# Combining Wafer Cleaning 

# With Etch

• SIA proposes to combine the wafer cleaning category with etch to minimize additional error and take advantage of very similar data

• Etch is defined by EPA as “a process type that consists of any production process 

## using fluorinated GHG reagents to selectively remove materials from a substrate during electronics manufacturing.”

– This is the same purpose as wafer cleaning, to remove selective portions of material from the wafer

– The tools specifically designated for wafer cleaning are using the same gasses in plasma to remove these materials



## • Wafer cleaning currently represents 1% or less of the gas use for the 12 facilities 

## analyzed for precision and accuracy

• A significant amount of apportioning (and apportioning error) can be eliminated as the gasses in question are only used for etch and wafer cleaning except NF3

• The wafer cleaning factors tend to be similar for SF6 and CF4.

• Additional EF data may be made available if categories were combined

41 November 17, 2011 Etch/Cleaning Gas EPA Etch EF (300mm) ISMI Etch EF (300mm) Wafer Cleaning EF CF4 0.80 0.63 0.77 CH2F2 0.14 0.14 0.24 NF3 0.32 0.17 0.23 SF6 0.37 0.23 0.20

# Emission Factor Management

• Emissions Factors:

– AP

- 42 update process is an established EPA process.



## – Need to develop process and timing for updating factors:

• Propose formation of an SIA/EPA task group;

• Establish evaluation criteria.



## – Allows input of individual emissions factor results: process needs to 

## address CBI concerns.



# • Future technologies (450 mm) will use same gas/wafer size approach.

– Need to establish process to populate Emissions Factors database 

## for 450 mm:

• Avoid first fab carrying full burden of data development;

• Plan orderly development of emissions factors.

42 November 17, 2011

# Alternative Abatement System 

# Options

• SIA is Preparing Alternative Testing Requirements for Consideration by EPA. Key aspects of the proposal:

– Abatement Systems Grouped by Emissions Estimation Categories

– Testing of Representative Sample Over a Defined Period:

• Testing of Representative Sample Over a 2 Year Period to Set Baseline DRE by Emissions Category.

• Testing of Representative Sample Over a 5 Year Period After Baseline Period.

• Abatement Unit Types Tested in Proportion to Their Numbers in the Site 

### Inventory.

• Proposal will be Based on Statistical Analysis of Group Sizes and Test Data.



## – Average DRE for the Emissions Category Will Be Applied to Emissions Category Gas Use Estimates.

– Revisions to the Uptime Calculation and Application of Uptime at the Emissions Category Level



## – Submittal of Summary Table to EPA on Abatement System O&M and Test Results.

• Detailed Documentation will be Maintained at the Facility.

43 November 17, 2011

# Abatement System Data Collection

• Inventory of abatement systems at 5 facilities for 3 manufacturers.

– Inventory data collected by Manufacturer and Model Number

– Emissions category process type abated.



# • Test Data:

– One Year of testing at a Facility to Subpart I Requirements:

• 50+ Tests, 20% sample or 3 by Mfg/Model/Gas (>30% of Units Tested) as currently required by Subpart I.

• Performed to EPA Method 1.



## – Testing Data Grouped by Device Type:

• 20

- 30 Tests

• Performed in general accordance with EPA Method 2: Testing after plasma processing of gas.

44 November 17, 2011

# Abatement System Testing 

# Proposal

• SIA/ISMI will use testing data to show:

– Use of baseline period to identify and correct O&M Issues



## – Appropriateness of use of representative sample for testing over 5 year period:

• Subpart I requires testing of 30

- 50% of abatement units annually.

• Inconsistent with testing requirements for CAA systems and Subpart L.

• SIA to complete statistical analysis of inventory and test data to establish criteria for setting representative sample size.



## – Logic of applying average DRE to gas use for each emissions process category

– Properly maintained equipment continues to perform to 

## Manufacturer’s expected DRE.

45 November 17, 2011

# Abatement System O&M and 

# Documentation Submittal

• Create summary report for submittal to EPA:

– List of equipment



## – Uptime of each unit

– Last test data and DRE results for the Individual units

– Applicable category, average category DRE & uptime.



# • Self certification statement provided to EPA.

• O&M, install documentation and test reports maintained at facility.

46 November 17, 2011

# Benefits of Revised 

# Abatement Approach

• Testing by emissions category:

– Simplifies Apportionment

– Simplifies the Uptime Calculations

– Enables Larger Groupings of Systems

– Matches Gas Types to Abatement Units



## • Use of representative samples:

– Most Facilities with Abatement Units Have Large Inventory.

– Initial Baseline Testing Sets Average DRE’s by Category



## – Representative Sample is Consistent with CAA Requirements

• Provides Check on Performance

• Enable Appropriate Corrective Action on Installed Base



## • Documentation of facility reduces burden:

– Consistent with CAA Permit Requirements



## – Reduces Documentation Management for EPA and Facilities



## • Reset default DRE in rule based on overall DRE testing data Collected by ISMI.

47 November 17, 201149 

# Key Takeaways

• This analysis was undertaken to identify the best etch emissions calculation model. The 2 factor model is the most appropriate method to estimate semiconductor etch emissions.

– I mproved precision vs. EPA Tier 2c and 2d;

– Avoids technical feasibility and intellectual property issues associated with current Subpart I Rule;

– Provides additional data that feed into the IPCC process to ensure increased accuracy of semiconductor emissions estimates world

- wide.



### • The ISMI database is sufficiently robust to provide representative emissions factors for Gas/Wafer Size.

– 976 data sets.

– Emission factors provided for 99.7% of etch gas usage.



### • ISMI expects additional etch data sets in 2012.

• Industry recommends allocating byproducts using both single

- and multi

- gas data.

• Wafer cleans do not differ substantively from etch and do not warrant a separate process category.

• The AP

- 42 update process can be used to update emission factors and develop industry factors for future 450mm wafer fabs

.

• Industry has developed proposals to address technical feasibility and cost concerns of gas apportioning and POU abatement uptime tracking and testing.

November 17, 2011 49

# Methods Used to Apportion 

# Gas Usage
– 200mm Fabs

• Fab A

- We used the 100 most frequently run GHG

- utilizing recipes to develop an engineering model to apportion gas consumption between the 5 categories. Total gas consumption (based on actual consumption for 2009 and 2010) was apportioned using nominal recipe gas flow and time for 2009. There is some CF4 used for ashing ; however, the amount is believed to be relatively small compared to CVD chamber cleaning and etch.

• Fab B

- 1. Used heel factors for each cylinder type based on change

- out triggers. 2. Applied heel factors to gas disbursement data to obtain total usage of each gas for the year. 3. Assigned each tool/gas combination to a process group. 4. Where multiple processes are performed by the same gas on the same tool: a. Chose the predominant one, or b. If judged to be equal, distributed gas for that tool/process equally across categories. 3. Matched tool/gas process groups with gas distribution system information to assign process group(s) to each cylinder stati on. 4. Where >1 process group on a cylinder station, prorated gas usage per cylinder across groups based on number of tools in th at group. 5. Multiplied by actual cylinder changes at each station for the year, and summed up gas consumption by process groups to generate apportioning factors.

• FAB C

– The Purchasing Department supplies the amount of full cylinders used/ year. The heel and amount of gas used is based on full cylinder amounts (weight/ pressure). Production supplies estimated cc of each gas used per tool per product rec ipe

. We are using 98% of product, but we are required to measure each cylinder for less than 20 lbs. of material left in the cylinder.

• Fab D

- Apportioning between the different CVD processes was based on estimates taking into account number of chambers using RPC/In

- Situ, NF3 volumetric flows, NF3 flow duration, NF3 flow length, and approximate cleans/day of the tools.

• Fab E

- Used model where each PFC gas consumption is in lbs./wafer start for each recipe. Created % gas split by dividing lbs / ws for each category by the total for that gas.

• Fab F

- Apportioning between the different CVD processes was based on estimates taking into account number of chambers using RPC/In

- Situ, NF3 volumetric flows, NF3 flow duration, NF3 flow length, and approximate cleans/day of the tools.

• Fab G

- Gas usage is measured to the tool or, in some cases for etch, groups of like tools (i.e., etching similar film stacks or features).

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# Methods Used to Apportion 

# Gas Usage
– 300mm Fabs

• Fab 300 - A

- Apportioning between the different CVD processes was based on estimates taking into account number of chambers using RPC/In

- Situ, NF3 volumetric flows, NF3 flow duration, NF3 flow length, and approximate cleans/day of the tools.

• Fab 300 - B

- Used model where each PFC gas consumption is in lbs./wafer start for each recipe. Created % gas split by dividing lbs./wafer start for each category by the total for that gas.

• Fab 300 - C

- CF4, SF6, and NF3 are used in other applications than etch. All other gases are used strictly in plasma etch. CF4 and SF6 are used in etch and wafer cleaning. Design data were used to estimate quantity of CF4 and SF6 used in wafer cleaning. Etch CF4 and SF6 were determined by difference. Design data were used to quantify of NF3 used in plasma etch processes. Chamber cleaning NF3 is partitioned by design data between that used in plasma etching and in chamber cleaning. The allocation between the different chamber cleaning methods are based on actual data.

• Fab 300 - D

- The actual use of each gas for each chamber was estimated by taking the authorization level of a specific chamber divided by the total authorized use of all chambers times the total actual use for the fab. The estimated actual usage for etch tools was then summed.

• Fab 300 - E

- The actual use of each gas for each chamber was estimated by taking the authorization level of a specific chamber divided by the total authorized use of all chambers times the total actual use for the fab. The estimated actual usage for etch tools was then summed.

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# Modified N Calculation

Modified N =

N

– {(N

- 1) * (100

– Degree of Averaging)/100}
Thus , Modified N ranges between 1 and N.

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