This document discusses sensor data fusion and integration challenges in advanced wafer fabrication. It proposes a sensor data fusion architecture based on SEMI EDA standards to address these challenges. The key points are: 1. Advanced fabs increasingly use external sensors but custom integration solutions result in an impossible to support "trail mix" architecture. 2. The sensor data fusion architecture is based on SEMI EDA standards, which allow querying equipment metadata and accessing sensor data in a standardized way. 3. This architecture represents external sensors in the common equipment model and shares context data, addressing integration challenges like data scaling and association. 4. The vision is this approach enables more flexible applications like remote support by providing sensor data in

1. www.cimetrix.com
Symposium 2015 – eMDC and ISSM
Taipei, Taiwan, 2-3 September 2015
Alan Weber – Cimetrix, Incorporated
Data Fusion at the Source:
Standards and Technologies
for Seamless Sensor Integration
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2.  Background and motivation
 Typical sensor integration approach
 Sensor integration challenges
 Context of proposed solution
 Sensor data fusion architecture
 Vision for manufacturing
Outline
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3.  Advanced wafer fabs increasingly use external sensors to
improve process visibility and control
 The number and variety of sources for equipment and
process data is growing steadily
 The demand for more data will likewise accelerate as “big
data” analysis tools become commonplace
 Custom integration solutions result in a “trail mix” factory
architecture which is impossible to support
Background and motivation
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4. Insatiable demand for data
Node (nm) 800 600 350 250 180 130 90 45 32 22 14 10
Process
window (Cpk)
Key applications SPC R2R FDC VM PDM Big Data
Data generated 0.016 0.3 2.4 40 240 1500
(MB/sec)
Supporting SECS-II GEM GEM300 EDA I EDA II E164…
SEMI Standards
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5. Typical sensor integration approach
Factory
Systems
Process
Engineering
Database
Sensor
Interfac
e
Process
Tool
S S S
GEM
APC, FDC
SOA
TCP/IP
Equipment
Integration
Server
Local
DB
Equipmen
t
Controller
5

6. 1. Finding a sensor that works
2. Sampling/process synchronization
3. Dealing with multiple timestamps
4. Scaling and units conversion
5. Applying factory naming convention
6. Associating context and sensor data
7. Ensuring statistical validity
8. Aligning results in process database
Sensor integration challenges
6

7. Typical sensor integration approach
With challenge areas highlighted
2
3
4
5
6 7
1
8
Factory
Systems
Process
Engineering
Database
Sensor
Interfac
e
Process
Tool
S S S
GEM
APC, FDC
SOA
TCP/IP
Equipment
Integration
Server
Local
DB
Equipmen
t
Controller
7

8. Context of proposed approach:
SEMI EDA* Standards
* Equipment Data Acquisition,
aka Interface A
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9.  Ability to query equipment for its metadata model
 Multiple independent client applications
 Web-based communications technologies
 Powerful event/exception-based trace requests
 Support for “data on demand”
 Performance monitoring and notification features
 Secure access (local and remote)
What’s different about EDA?
Key distinctions from other standards
Get the data you want…
when and where you need it
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10. Unified equipment model
E164 Model
Configuration
Settings
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11.  Includes all required tool elements
 Consistent GEM implementations
 Commonality across equipment types
 Less work to interpret results
 Enables “plug and play” applications
 Unified context for all data sources
Importance of common metadata
Standards for equipment models
E164 is to EDA what GEM was to SECS-II
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12. EDA implementation architecture
Components and context
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13. Sensor Data Fusion Architecture
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14. External sensor integration example
Sensor data fusion architecture
OEM Tool
EDAGEM
Sensor/Actuator Gateway
Device Drivers
DP ATP S1
TP
Pump
I/F
FICS / MES
EDA Client
EDA Server
EDA Client
Smar
t
Data
Model
Raw Data
Metadata Model
Public
Data
DCIM*
DCI
M
Proprietary
Application
s
Process-specific
applications Factory-level
EDA Client Apps
(DOE, FDC, PHM, …)
Custom
or
EtherCAT
TCP/IP
HTTP
HTTP
HTTP
To factory-level systems
Context data
Synchronization data
S2 S1
* DCIM =
Data Collection
Interface Module
Synchronization signals
Process
Engineering
Database
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15. Shared equipment model
External sensors appear in same structure
Full Equipment Model Skeletal Equipment Model
Minimal
Equipment
Structure
High-level
Equipment
structure
Process
Chamber
Process
Chambers
Embedded
Sensors
External
Sensors
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16. Shared equipment model
Context information (required subset)
Sensor
Values
High-level
Equipment
structure
Context
Information
Process
Chamber
Full Equipment Model Skeletal Equipment Model
Context
Information
Synchronization
Signal
Integration
Conditions
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17. External sensor integration example
With challenge areas addressed
OEM Tool
EDAGEM
Sensor/Actuator Gateway
Device Drivers
DP ATP S1
TP
Pump
I/F
FICS / MES
EDA Client
EDA Server
EDA Client
Smar
t
Data
Model
Raw Data
Metadata Model
Public
Data
DCIM*
DCI
M
Proprietary
Application
s
Process-specific
applications Factory-level
EDA Client Apps
(DOE, FDC, PHM, …)
Custom
or
EtherCAT
TCP/IP
HTTP
HTTP HTTP
To factory-level systems
Context data
Synchronization data
S2 S1
* DCIM =
Data Collection
Interface Module
Synchronization signals
Process
Engineering
Database
2
3
4
5
6
7
1
8
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18. A Vision for Manufacturing
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19. Current factory system architecture
GEM interfaces for command and control
MES
Factory Information and Control Systems
AMHS
MES,
RMS
Other DB
Sensor
Gatewa
y
OEM Tool
S S S
GE
M
…
Equipment
Integration
Server
YMS
APC, FDC
RMS
SOA
TCP/IP
Equipment
Integration
Server
Local
DB
Local
DB
OEM Tool
GE
M
OEM Tool
GE
M
OEM Tool
GE
M
19

20. Current factory system architecture
GEM interfaces for command and control
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21. A vision for manufacturing
Evolutionary, demand-driven approach
S/W Test
Additional Applications
Modeling
PHM
DOE
Process
Development
Simulation
ACM
Remote Applications
Field Service
Support
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22. Thank you !
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