SEMICON West 2006 STEP
Methods to Measure/Improve
Equipment Productivity
SEMI Equipment
Performance Standards
Integration
Sal DiIorio
Semi-Tech Group
sdiiorio@semitechgroup.com
Equipment Performance Metrics Process
• Factory sources (automated and/or human) provide the
inputs
• Standards define the process and equations
• Metrics are output consistently
– Same meaning for all metrics regardless of location
Factory Data
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SEMI
Standard
SemiCon West 2006
Metrics
Factory Data Sources
• Automated Systems
–
–
–
–
Production data, state history
Equipment Maintenance and state history
Equipment Cell Controllers
Equipment E116 or E58 state information
• Non-automated Systems
– Manual state change histories
– Manual input to support E58
– Other state and history logs
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Eq. Performance Standards Relationship
Equipment
Driven Data
E79
E116
OEE
EPT
E10
E35
RAM
E58
COO
E124
ARAMS
OFE
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SemiCon West 2006
E10 RAM
• Central to all Equipment Metrics Standards
• First developed in 1986 and continuously
improved to meet new requirements of the
semiconductor industry
• Defines the basic equipment states and
metrics which act as input to other
performance metrics
– E79 Overall Equipment Efficiency
– E35 Cost of Ownership
– E124 Factory Level Productivity
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E10 Process
MES
CMMS
Data Logs
E10 State
Logic
E10
RAM
E116
E58
Data
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SemiCon West 2006
Availability
Uptime
Utilization
MTBFp
MTTR
TFR
CT-RAM
E116 Process
E116
State
Data
E10 State
Data
E10 State
Logic
MES
Input
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Mapping the States
NON-SCHEDULED (MES) AND ANY STATE* (EPT)
MANUFACTURING (MES) AND BLOCKED (EPT)
ENGINEERING (MES) AND BLOCKED (EPT)
UNSCHEDULED DOWN (MES) AND ANY STATE* (EPT)
E10 States
NON-SCHEDULED
TIME
UNSCHEDULED
DOWNTIME
SCHEDULED DOWN (MES) AND ANY STATE* (EPT)
SCHEDULED
DOWNTIME
ENGINEERING
TIME
ENGINEERING (MES) AND BUSY (EPT)
ENGINEERING (MES) AND IDLE (EPT)
STANDBY
TIME
PRODUCTIVE
TIME
MANUFACTURING (MES) AND IDLE (EPT)
MANUFACTURING (MES) AND BUSY (EPT)
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*ANY STATE (EPT) means that the
EPT state is not a factor in
determining the E10 state.
E58 Process
E58
State
Data
E58
External
Input
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E10 State
Data
E58 vs. E10 State Examples
• Equipment tracks its own E58 state...
• But… it doesn’t know its own E10 state details
• User input is required, in order to provide accurate data
E10 State
Productive
Standby
Engineerng
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E58 State
1000
1100
1200
1300
1400
2000
2100
2200
2300
2400
3000
3100
3200
Comment
Default Productive
Regular Production
Production for third party
Production for rework
Production for Engineering
Default Standby
No operator
No product for production
No support tool
Associated cluster module down
Default Engineering
Process Experiments
Equipment Experiments
SemiCon West 2006
E58 – How it works
Information
exchange
regarding
equipment
downtime state
and material
type.
Host
Computer
Metrics
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Operator input to trigger
E58 state changes.
MES
E58 state transition
Event reports.
Host input to trigger
E58 state changes.
SemiCon West 2006
Equipment
Now that we have E10 Metrics, what do
we do with them?
E79
OEE
E116
Continuous
Improvement
Activities
EPT
E35
E10
COO
RAM
E58
ARAMS
E124
OFE
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• Lean Mfg
• TPM
• RCM
• 6 Sigma
• Rel Eng
• Etc.
Using E10 Metrics
• Use them in purchase acceptance specifications
– MTBFp, Uptime, MTTR, etc.
• Monitor our own performance and drive continuous
improvement activities
– Look for improvements in metrics when new procedures or
processes are implemented.
• Benchmarking functions with other companies or
between factories
• Use them as inputs to other SEMI Standards for a
better understanding of equipment COO or
productivity
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SEMI E35 COO
• COO = The full cost of embedding, operating,
and decommissioning in a factory environment
equipment needed to accommodate the required
volume of production units.
• Among the many inputs used by E35, two come
from E10
– Operational Uptime
– E10 metrics (MTBF, MTTR) to calculate maintenance
labor hours required for scheduled and unscheduled
downtime
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E79 OEE
• OEE calculations are stated in terms that are consistent
with SEMI E10.
OEE = Availability Efficiency x Operational Efficiency
x Rate Efficiency x Quality Efficiency
Where E10 directly provides the values for:
• Availability Efficiency = Equipment Uptime / Total Time
• Operational Efficiency = Production Time / Equipment Uptime
• Rate Efficiency = Theoretical Production Time for Actual Units
/ Production Time
• Quality Efficiency = Theoretical Production Time for Effective
Units / Theoretical Production Time for Actual Units
Notes:
Production Time is not defined in E10, but happens in Productive
Time.
Rate Efficiency x Operational Efficiency = Performance Efficiency
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The Relationship Between OEE and E10
Total Time
Availability
Efficiency
Non-Scheduled Time
•Unworked shifts, days
•Installation, modification
rebuild, or upgrade
•Off-line training
•Shutdown/Startup
Downtime
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Uptime
Unscheduled Downtime
Scheduled Downtime
Engineering Time
•Maintenance delay
•Repair time
•Change of consumables/
chemicals
•Out of spec input
•Facilities related
•Maintenance delay
•Production tests
•Preventive maintenance
•Change of consumables
chemicals
•Setup
•Facilities related
•Process experiments
•Equipment experiments
Rate Efficiency
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Operational
Efficiency
Operations Time
Not specified in
SEMI E10 but occurs
during Productive Time
SemiCon West 2006
Manufacturing Time
•Software qualification
Productive Time
•Regular production
•Work for 3rd party
•Engineering runs
•Rework
•Scrap
Standby Time
•No operator
•No product
•No support tool
•Associated cluster
module down
Quality Efficiency
E79 Process
E10 Times
Uptime,
Productive
Time,
Total Time
E79
Other Data:
Theoretical
Production
Time, Units
produced, etc.
In addition to OEE several other
efficiencies are also defined to enable
users to assess more specific aspects
of equipment productivity.
Other data can
come from MES or
other Factory
sources.
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OEE
Reference OEE
Engineering OEE
Value-Added In-Process OEE
Production Eqpt Efficiency
Demand Equipment Efficiency
Intrinsic Eqpt Efficiency
Rate Efficiency
Quality Efficiency
SemiCon West 2006
What is needed to determine E10 State?
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State
Data Needed
Unscheduled
Downtime
Start/stop (duration) of unscheduled downtime
Reason for failure (equipment/non-equipment dependent
failures)
Scheduled
Downtime
Start/stop (duration) of scheduled downtime
Reason for downtime
Engineering
Start/stop (duration) of engineering work
Type of engineering work
Productive
Start/stop (duration) of actual productive time
Manufacturing state of equipment
Type of units run
Standby
Start/stop (duration) of idle time
Units or support equipment available
Linked equipment down
CIM system providing input
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SemiCon West 2006
What is needed to calculate E10 Metrics?
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Metric
Data Needed
MTBFp
E-MTBFp
# of failures that occurred while in or while trying to transition
to productive state
Productive Time
Reason for failure (equipment/non-equipment dependent
failures)
MTTR
E-MTTR
# of failures (equipment/non-equipment dependent failures)
Duration of Unscheduled Downtime
Operational
Uptime
Uptime (Productive Time + Standby Time + Engineering Time)
Operations Time (Total Time – Non-Scheduled Time)
Equipment
Dependent
Uptime
Uptime
All Maintenance-Delay Time (waiting for parts, people, etc.)
Facilities-Related Downtime (scheduled and unscheduled)
Out-of-Spec Input (consumables, chemicals, test results, etc.)
Total
Utilization
Productive Time
Total Time
Julu 12, 2006
SemiCon West 2006
Automation vs. Manual Data Collection
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What data do people capture
best?
What data do people capture
worst?
• Transition to and from
SCHEDULED DOWNTIME
• NON-SCHEDULED time
• Reason for Failures
– Equipment dependent vs.
non-equipment
dependent
• Transition and reasons for
Maintenance Delay
• Transition from STANDBY to
PRODUCTIVE
• Transition from PRODUCTIVE
to STANDBY
• Transition to UNSCHEDULED
DOWNTIME
• Wafer/Cycle Counts
• Failures
• Cluster Tool Module level
states
Julu 12, 2006
SemiCon West 2006
Automation vs. Manual Data Collection
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What data does automation
capture best?
What data does automation
capture worst?
• Transition from STANDBY to
PRODUCTIVE
• Transition from
PRODUCTIVE to STANDBY
• Transition to
UNSCHEDULED
DOWNTIME
• Wafer/Cycle Counts
• Failures
• Cluster Tool Module level
states
• Transition to and from
SCHEDULED DOWNTIME
• NON-SCHEDULED time
• Reason for Failures
Julu 12, 2006
SemiCon West 2006
– Equipment dependent
vs. non-equipment
dependent
• Transition and reasons for
Maintenance Delay
Is automation absolutely necessary?
• Automation is superior for the following:
– Accurate data regarding Productive / Standby time
• More accurate OEE Operational Efficiency values
– Accurate data about cluster tool module level state
• Essential for CT RAM and CT OEE metrics
– Accurate quantitative data about units processed and
other parametric data for scheduling maintenance.
• Some level of automation is absolutely preferable,
even if limited.
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Do we really need automation?
• Yes, primarily if:
– Detailed information is absolutely required.
• CT RAM and OEE metrics
– The cost of implementing and supporting automation can be
justified.
• Full automation requires large investments in HW, SW and IT
and is never “done”; it continually needs updates and ongoing
commitment of resources (people and $$$).
• Lesser degrees of automation can provide significant
improvements in data accuracy.
– MES and CMMS (CIM) systems provide excellent sources for
E10 data.
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What if full automation is not possible?
• Equipment level E10 metrics can be maintained.
– Daily and Weekly summaries can be analyzed.
– Look for changes and trends
• Equipment to equipment
• Time period to time period
• Simple OEE metric may be possible.
– Even if detailed rate and quality data are not available
• COO calculations are still meaningful.
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Conclusions
• SEMI equipment performance metrics standards
work together to provide meaningful information
about the RAM, utilization, productivity, and COO of
semiconductor equipment.
• While high levels of automation are required for the
most accurate data and many detailed metrics,
manual data can still provide useful information.
– For newer, multi-billion dollar factories the return provided
by small increases in productivity may quickly exceed the
cost of automation.
– Older, smaller factories can achieve meaningful results
with less automation, as long as absolute accuracy is not
needed.
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