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Simulation
ROCHESTER INSTITUTE OF TECHNOLOGY
MICROELECTRONIC ENGINEERING
Computer Simulation of Factory
Performance
Katie McConky
ISE Graduate Student
Rochester Institute of Technology
82 Lomb Memorial Drive
Rochester, NY 14623-5604
[email protected]
Rochester Institute of Technology
Microelectronic Engineering
© January 27, 2006 Dr. Lynn Fuller, Motorola Professor
Page 1
Simulation
OUTLINE
Overview of Modeling
Verification and Validation of Models
Model Accuracy
Statistical Analysis
AutoSched AP – Brooks Automation
AutoMod– Brooks Automation
Example Simulation Problems
Rochester Institute of Technology
Microelectronic Engineering
© January 27, 2006 Dr. Lynn Fuller, Motorola Professor
Page 2
Simulation
Overview of Modeling
•Semiconductor Fabs are extremely complex
•Reentrant Manufacturing
•High variability
•Long Process Routes
•Complicated batching and sequencing criteria
•Simulation modeling can take everything into account in order to
answer questions about the fab.
Rochester Institute of Technology
Microelectronic Engineering
© January 27, 2006 Dr. Lynn Fuller, Motorola Professor
Page 3
Simulation
Verification and Validation
Verification
- Check that the model is acting how you expect it to act.
- Dispatching Rules
- Processing Times and other fundamentals
Validation
-Model results must resemble the actual fab:
-Cycle Time
-Total WIP Levels
-WIP by Area
-Model Outs
-Tool Throughput
Rochester Institute of Technology
Microelectronic Engineering
© January 27, 2006 Dr. Lynn Fuller, Motorola Professor
Page 4
Rochester Institute of Technology
Microelectronic Engineering
WIP
Starts
Fiscal Week
Model Outs
© January 27, 2006 Dr. Lynn Fuller, Motorola Professor
Actual Outs
Page 5
2005_37
2005_35
2005_33
2005_31
2005_29
2005_27
2005_25
2005_23
2005_21
2005_19
2005_17
2005_15
2005_13
2005_11
2005_09
Validation
2005_07
2005_05
Model OutsSimulation
vs. Actual Outs
100%
2004_41
2004_42
2004_43
2004_44
2004_45
2004_46
2004_47
2004_48
2004_49
2004_50
2004_51
2004_52
2004_53
2005_01
2005_02
2005_03
2005_04
2005_05
2005_06
2005_07
2005_08
2005_09
2005_10
2005_11
2005_12
2005_13
2005_14
2005_15
2005_16
2005_17
2005_18
2005_19
2005_20
2005_21
2005_22
2005_23
2005_24
2005_25
2005_26
2005_27
2005_28
2005_29
2005_30
2005_31
2005_32
2005_33
2005_34
2005_35
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2005_37
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2005_41
2005_42
2005_43
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2005_48
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2005_50
2005_51
2005_52
Percent of Wafers
Simulation
Validation
Model Data
CMP
Diff
Area WIP for Part: ALL
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
Etch
Films
Imp
Litho
PLY
© January 27, 2006 Dr. Lynn Fuller, Motorola Professor
Wets
Rochester Institute of Technology
Microelectronic Engineering
Page 6
Simulation
Validation
Actual Data
Rochester Institute of Technology
Microelectronic Engineering
© January 27, 2006 Dr. Lynn Fuller, Motorola Professor
Page 7
Simulation
Model Accuracy
§ Models can be very accurate for short periods of time
Rochester Institute of Technology
Microelectronic Engineering
© January 27, 2006 Dr. Lynn Fuller, Motorola Professor
Page 8
Simulation
Model Accuracy: Common Misconception
Parameter
Starting off with conditions that are 80%
correct in the fab does not lead to a model
that is 80% correct.
Rochester Institute of Technology
Microelectronic Engineering
Time
© January 27, 2006 Dr. Lynn Fuller, Motorola Professor
Page 9
Simulation
Model Accuracy
Parameter
Obtain the most accurate picture of the fab as possible.
Rochester Institute of Technology
Microelectronic Engineering
Time
© January 27, 2006 Dr. Lynn Fuller, Motorola Professor
Page 10
Simulation
Model Accuracy
§ To maintain an accurate / valid model you must:
§ Generate route and station files very quickly
§ Load a snapshot of the WIP into your model
§ Collect and update process times and other parameters frequently
§ How do we accomplish all this?
§ Create an automated system to generate an entirely new model on a
regular basis.
Rochester Institute of Technology
Microelectronic Engineering
© January 27, 2006 Dr. Lynn Fuller, Motorola Professor
Page 11
Simulation
Statistical Analysis
§ Models can account for process variability. (models
include some random event generators, for example:
when equipment goes down)
§ It is therefore important to run a simulation more than
once.
§ Multiple Replications
§ Simulation results should be reported as confidence
intervals on a mean value.
Rochester Institute of Technology
Microelectronic Engineering
© January 27, 2006 Dr. Lynn Fuller, Motorola Professor
Page 12
Simulation
AUTOSCHED from Brooks Automation Inc.
Rochester Institute of Technology
Microelectronic Engineering
© January 27, 2006 Dr. Lynn Fuller, Motorola Professor
Page 13
Simulation
AutoSched AP and AutoMod
§ AutoSched AP:
§ Is an object-oriented modeling tool.
§ Uses a Windows-based Excel spreadsheet interface.
§ Is integrated with the APF Repository, APF Reporter, and Real Time
Dispatcher.
§ AutoMod:
§ 3-D graphics
§ Automated Material Handling Systems (AMHS)
§ Can be integrated with AutoSched AP models
Rochester Institute of Technology
Microelectronic Engineering
© January 27, 2006 Dr. Lynn Fuller, Motorola Professor
Page 14
Simulation
AutoSched AP
Excel File
Rochester Institute of Technology
Microelectronic Engineering
© January 27, 2006 Dr. Lynn Fuller, Motorola Professor
Page 15
Simulation
AutoMod Fab Partial Fab Model
Rochester Institute of Technology
Microelectronic Engineering
www.ismi.sematech.org/modeling/simulation
© January 27, 2006 Dr. Lynn Fuller, Motorola Professor
Page 16
Simulation
Typical Problems
§ How many tools should I purchase for a new step?
§ Depends on Desired Queue Length
§ Depends on Desired Queue Time
§ Importance:
§ Simulation results were used to justify the purchase of an extra tool in
order to keep queuing times and queue lengths at a desired minimum.
Rochester Institute of Technology
Microelectronic Engineering
© January 27, 2006 Dr. Lynn Fuller, Motorola Professor
Page 17
Simulation
Typical Problems
§ If I remove tool dedication from one step, will I get
increased tool utilization or a decrease in cycle time?
DT
AA
ARF 1
ARF 1
ARF 1
ARF 1
ARF 2
ARF 2
ARF 2
ARF 2
ARF 3
ARF 3
ARF 3
ARF 3
GC
M0
Rochester Institute of Technology
Microelectronic Engineering
© January 27, 2006 Dr. Lynn Fuller, Motorola Professor
Page 18
Simulation
Results of M0 Dedication Removal
D11 Cycle Time With and Without M0 Dedication
(SSU RULE)
65.66
65.64
37.62
D11 w /o M0
37.60
Days
Days
65.62
D11 w /M0
65.6
w ithout M0
w ith M0
37.58
65.58
65.56
65.54
0
1
2
3
4
5
6
7
8
9
Run Num ber
Rochester Institute of Technology
Microelectronic Engineering
© January 27, 2006 Dr. Lynn Fuller, Motorola Professor
Page 19
10
Simulation
Results of M0 Dedication Removal
§ Importance of Dedication Study:
§ If we could show through simulation that tool utilization or cycle time
would improve the pilot lots for M0 dedication removal could have
been prioritized, to make the change happen faster.
Rochester Institute of Technology
Microelectronic Engineering
© January 27, 2006 Dr. Lynn Fuller, Motorola Professor
Page 20
Simulation
Typical Problems
§ Forecasting wafer outs:
§ What will be my outs of each product at the end of the week?
§ Importance:
§ Notify backend facilities of expected shipments.
§ Update financial people on fab productivity.
§ Time consuming to do forecasts by hand.
Rochester Institute of Technology
Microelectronic Engineering
© January 27, 2006 Dr. Lynn Fuller, Motorola Professor
Page 21
Simulation
Typical Problems
§ What recipes should I pair together on my etch or films
tool so that my robot is not overworked?
§ Special software exists called ToolSim to model individual tools such
as cluster tools and litho tracks
§ Importance
§ You can test different recipe variations and combinations before
implementing them in the fab.
B
C
D
A
Rochester Institute of Technology
Microelectronic Engineering
Load
Port
1
© January 27, 2006 Dr. Lynn Fuller, Motorola Professor
Load
Port
2
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Simulation
References
§ www.sematech.org
§ www.Brooks.com
Rochester Institute of Technology
Microelectronic Engineering
© January 27, 2006 Dr. Lynn Fuller, Motorola Professor
Page 23