Lot Completion Estimation Using Self-Configuring Equipment Model-based Applications

www.cimetrix.com
Lot Completion Estimation
Using Self-Configuring
Equipment Model-based Applications
15th European Advanced Process Control
and Manufacturing (APC|M) Conference
Freising, Germany, 13-15 April 2015
Alan Weber
Cimetrix, Incorporated
1

 Background and motivation
 Typical automation solution
 Context of proposed approach
 Lot completion estimation
 Other useful self-configuring applications
 Vision for manufacturing
Outline
2

 Inter-process wait times have direct negative
impact on yield for critical process steps
 Many advanced processes include a number of
direct tool-to-tool material delivery steps
 Productivity KPIs are also affected by inaccurate
carrier completion estimates
Background and motivation
3

 Dedicated status variables and events
 Provide estimated completion times for all active and
scheduled lots known to the tool
 Generate events at configurable timing threshold
 Updated continuously
 Use equipment-specific domain knowledge
 Internal substrate transfer/wait times
 Other process-specific timing information
 Require OEM support to modify algorithm
 Problematic after installation/acceptance
Typical automation solution
Custom development by each tool supplier
4

How much time are we talking about?
5
Time required for all operations – “Total Cycle Time”
Focus areas for carrier
completion estimation
Apr May Jun
600+ Operations

6
Context of proposed approach:
SEMI EDA* Basics
* Equipment Data Acquisition,
aka Interface A

 Ability to query the equipment for its metadata
 Multiple independent client application access
 Use of mainstream communications technologies
 Powerful event/alarm-based trace request structure
 Support for “data on demand”
 Provision for built-in data collection plans
 Performance monitoring and notification features
 Secure access (local and remote)
 …and
 Equipment-oriented application support !
What’s different about EDA?
Key distinctions from other standards
7

E132
E134
E125
E120/E125
E164
How the pieces work together
Operational sequence
8
E132

Data collection plans
Trace, event, and exception requests
9

Equipment modeling
E125 Equipment Self Description
10

 Consistent implementations of GEM300
 Increased metadata uniformity
 Less work to interpret metadata and results
 Commonality across equipment types
 Simplified EDA application client creation
 Self-configuring application possibilities!
Why is E164 so important?
Common metadata results in…
11
E164 is to EDA what GEM was to SECS-II

 State Machines
 Strict State Machine definitions
 Requires E157 State Machines for all process modules
 Requires E90 State Machines for all substrate locations
 Requires all Parameters, Events and Exceptions defined in Freeze II
standards to be present
 State and transition names must match GEM300 standards
 E120 Common Equipment Model usage/content
 Nodes and parameters must have meaningful descriptions
 Equipment element attributes for all E120 nodes must have meaningful
values
 All definitions (exceptions, SMs, parameter types, units, SEMI object
types) must be referenced
 Strict event name enforcement
What does E164 specify?
Structure and content of equipment metadata
12

Equipment Model Developer
A closer look…
Model
object / template
toolbox
Constructed
model
treeview pane
Selected model
element properties
Output
window
13

 Features
 Provide continuously updated estimates for current lot completion
and equipment idle time for MCS/AMHS dispatching decision support
 Provide notification events at configurable thresholds
 Maintain substrate process times per recipe
 E164 leverage (using required elements)
 Material Manager: E90 substrate transport events; E87 Carrier
instance attributes
 Job Manager: attributes for ControlJob and ProcessJob instances
 Process Module nodes: E157 module process events
E164 application example
Lot (or carrier) completion estimation
15

 Sum # of wafers to be processed
 For each Carrier SEMI Object instance select ControlJobs with CarrierInputSpec that
contains Carrier’s ObjID
 For each ControlJob, count the # of substrates listed in each ProcessJob’s PRMtlNameList
attribute
 Calculate average time to return substrate to destination carrier
 Record time when first AtWork-AtDestination event is reached
 When next AtWork-AtDestination event is reached, record difference as current average
time to return substrate to carrier
 Calculate initial carrier completion estimation
 = # remaining substrates * current average substrate return time
 Update carrier completion estimation
 When each AtWork-AtDestination event is reached, subtract timestamp of first event from
latest event, and divide by # of substrates
 Use this value as new average substrate return time in calculating new carrier completion
estimation
Algorithm summary
Carrier completion estimation
16

E164 required elements
Used in carrier completion algorithm (1)
Carrier ObjID
attribute
High-level
Equipment
structure
E90 Substrate
Transport
events
MaterialManager
Module
17

Used in carrier completion algorithm (2)
High-level
Equipment
structure
JobManager
Module
ControlJob
CarrierInputSpec
attribute
ProcessJob
PRMtlNameList
attribute
18

 Calculate substrate process times per chamber
 When first NotExecuting-GeneralExecution event is received from a process module,
record the timestamp
 When first GeneralExecution-NotExecuting event is received from the same process
module, record difference as current average substrate process time
 Update average substrate process time for each pair of NotExecuting-
GeneralExecution and GeneralExecution-NotExecuting events
 For a given substrate, perform the above steps for each process module visited
by the substrate before returning to carrier
 Assumes no substrate visits the same process module more than once
 Provides additional carrier pickup scheduling information when used in
conjunction with carrier completion estimation
Algorithm summary
Average substrate process times
19
Results can also be stored at factory level with associated context
to refine algorithms by equipment type and process recipe

Used in substrate processing time algorithm
High-level
Equipment
structure
Processing
Chamber
Node
SubstrateID
parameter
E157 Module Process
Tracking events
20

Lot completion estimation application
Additional user interface elements
Time to Equipment IdleTime to LP1 Carrier Complete 00:13:0400:12:5900:12:54 01:46:2201:46:1701:46:12
21

Other E164 Application Examples
22

 “Quick-connect” generic production monitor
 Dynamic sampling capability for wafer-level APC
 Process characterization and experiment automation
 Automated waveform analysis, “characteristic value” calculation
 “Golden run” analysis and related tool/chamber matching
 “Virtual signal” generation for complex components/subsystems
 Precision trace data framing for MVA-based FDC
 Equipment data mapping to fab structure/naming conventions
 Component behavior monitoring for variability reduction
 FMEA model refinement, fault isolation, root cause analysis
 Feature extraction for predictive maintenance algorithms
 Lot completion estimation (based on equipment metadata model)
 Product Time Measurement (Wait Time Waste analysis)
 Time-based component fingerprinting
 External sensor/subsystem integration
Factory applications
That directly leverage EDA
23

E164-based application examples
System components
E164-based GUI
+
EDAConnect
(EDA client)
GEM300
Equipment
Simulator
CIMPortal Plus
(EDA server)
Equipment
24

 Features
 Build tool production monitoring screen layout
 Generate required data collection plans (DCPs)
 Animate monitoring screen from collected data
 “Self-configuring” – no programming required
 E164 leverage
 Dictates model structure and node types
 Specifies standard parameter and event names
 Used E90 substrate movement and location status and E157
process module tracking events
 Used E87 Carrier and E90 Substrate SEMIObjects
E164-based application example
“Quick connect” generic production monitor
25

Used by “quick connect” production monitor
SubstrateLocation
state transition
events
Referenced in
auto-generated
DCP
26

Equipment simulator (GEM300 + E164)
27

28

29

30

Client software (EDAConnect + GUI app)
31

Data collection plans (DCPs)
Note substrate
and process
tracking DCPs
for each chamber
32

Screen layout…
33

Screen layout and animation
34

Screen layout and animation
35

 Give everything a voice: equipment, material, processes,
people
 Convert raw data to actionable information
 Know why things happen… or don’t
 Understand where all the time goes
 Attack variability, and minimize its impact
 Build manufacturing domain knowledge
 Reduce “time to money” for new products
EDA enables factories to…
Optimize performance, productivity, and profit
37

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
38

감사합니다
唔該
Merci
Danke
多謝
ありがとうございます
Thank you
39

Lot Completion Estimation Using Self-Configuring Equipment Model-based Applications

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