ISMI Symposium on Manufacturing Effectiveness 2011. 19th October - Advanced Process Control Session. Fault Detection & Classification (FDC) and Fault Prediction (FP) on Vacuum/Abatement Systems. Edwards Ltd. Michael Mooney, Shane Butler (NUI Maynooth)
ISMI Symposium on Manufacturing Effectiveness 201119th October – Advanced Process Control Session
Fault Detection & Classification (FDC) and Fault
Prediction (FP) on Vacuum/Abatement Systems
Authors: Michael Mooney, Shane Butler (NUI Maynooth, Ireland)
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ISMI Symposium on Manufacturing Effectiveness 2011. 19th October - Advanced Process Control Session. Fault Detection & Classification (FDC) and Fault Prediction (FP) on Vacuum/Abatement Systems. Edwards Ltd. Michael Mooney, Shane Butler (NUI Maynooth)
Contents
Edwards Introduction
Edwards FabWorks-iMS & EADS
EADS Detectable/Classifiable Faults
EADS Development Process
EADS Fault Detection Example – TPU Liner Deposition
Fault Prediction – Particle Filters
Summary & Research Moving Forward
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ISMI Symposium on Manufacturing Effectiveness 2011. 19th October - Advanced Process Control Session. Fault Detection & Classification (FDC) and Fault Prediction (FP) on Vacuum/Abatement Systems. Edwards Ltd. Michael Mooney, Shane Butler (NUI Maynooth)
Edwards - Vacuum & Abatement Systems Specialist
• Equipment installed
globally
• > 750,000 vacuum pumps
• > 250,000 pumps in
semiconductor
• > 8,500 Point Of Use (POU)
abatement devices
• Experienced global service
network
• 850 service support
engineers & specialists
• On-site & remote
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ISMI Symposium on Manufacturing Effectiveness 2011. 19th October - Advanced Process Control Session. Fault Detection & Classification (FDC) and Fault Prediction (FP) on Vacuum/Abatement Systems. Edwards Ltd. Michael Mooney, Shane Butler (NUI Maynooth)
Edwards FabWorks-iMS & EADS
• FabWorks iMS – Intelligent Monitoring System
• Networks all Edwards equipment
• >160 FabWorks systems, monitoring >100K vacuum & abatement devices
• EADS – Edwards Advanced Diagnostic Services
• Fault Detection & Classification (FDC) and Fault Prediction (FP)
• Utilized by experienced global service & product specialists network
• Users notified of alert situations via FabWorks display, pager, email, SMS
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ISMI Symposium on Manufacturing Effectiveness 2011. 19th October - Advanced Process Control Session. Fault Detection & Classification (FDC) and Fault Prediction (FP) on Vacuum/Abatement Systems. Edwards Ltd. Michael Mooney, Shane Butler (NUI Maynooth)
Contents
Edwards Introduction
Edwards FabWorks-iMS & EADS
EADS Detectable/Classifiable Faults
EADS Development Process
EADS Fault Detection Example – TPU Liner Deposition
Fault Prediction – Particle Filters
Summary & Research Moving Forward
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ISMI Symposium on Manufacturing Effectiveness 2011. 19th October - Advanced Process Control Session. Fault Detection & Classification (FDC) and Fault Prediction (FP) on Vacuum/Abatement Systems. Edwards Ltd. Michael Mooney, Shane Butler (NUI Maynooth)
Edwards Introduction
Edwards FabWorks-iMS & EADS
EADS Detectable/Classifiable Faults
EADS Development Process
EADS Fault Detection Example – TPU Liner Deposition
Fault Prediction – Particle Filters
Summary & Research Moving Forward
EADS Fault Detection & Classification (FDC) & Fault Prediction (FP) Capability
Warning – Predictive
Software Started
9 days before fault
Warning –
Recommend PM
4 days before fault
Alarm – Do Not
Commence Processing
8 hours before fault
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ISMI Symposium on Manufacturing Effectiveness 2011. 19th October - Advanced Process Control Session. Fault Detection & Classification (FDC) and Fault Prediction (FP) on Vacuum/Abatement Systems. Edwards Ltd. Michael Mooney, Shane Butler (NUI Maynooth)
EADS Fault Detection & Classification (FDC) & Fault Prediction (FP) Capability
Warning: Predictive
Software Started
9 days before fault
Warning:
Recommend PM
4 days before fault
Alarm: Do Not
Commence Processing
8 hours before fault
Model Optimization
Optimization of logged
parameters and logging
rates
Technical Evaluation
Global Applications Knowledge
Reports
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ISMI Symposium on Manufacturing Effectiveness 2011. 19th October - Advanced Process Control Session. Fault Detection & Classification (FDC) and Fault Prediction (FP) on Vacuum/Abatement Systems. Edwards Ltd. Michael Mooney, Shane Butler (NUI Maynooth)
FDC & FP Case Study – EADS Model on LPCVD Nitride
• A year prior to introduction of EADS multi-parameter deposition models (approx 60 pump scale)
• 5 catastrophic faults
• A year following introduction of multi-parameter EADS deposition models
• 1 catastrophic fault, 5 similar fault conditions predicted & proactively managed
• Benefits
• Significant wafer value savings derived, with improved security/yield of critical batch process
Warning – Recommend PM
15 days before swap-out
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ISMI Symposium on Manufacturing Effectiveness 2011. 19th October - Advanced Process Control Session. Fault Detection & Classification (FDC) and Fault Prediction (FP) on Vacuum/Abatement Systems. Edwards Ltd. Michael Mooney, Shane Butler (NUI Maynooth)
Contents
Edwards Introduction
Edwards FabWorks-iMS & EADS
EADS Detectable/Classifiable Faults
EADS Development Process
EADS Fault Detection Example – TPU Liner Deposition
Fault Prediction – Particle Filters
Summary & Research Moving Forward
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ISMI Symposium on Manufacturing Effectiveness 2011. 19th October - Advanced Process Control Session. Fault Detection & Classification (FDC) and Fault Prediction (FP) on Vacuum/Abatement Systems. Edwards Ltd. Michael Mooney, Shane Butler (NUI Maynooth)
EADS Detectable/Classifiable Faults
• Examples:
• Turbo Pump Deposition & Turbo Pump Leak Detection on Ion Implant• Catastrophic pump faults prevented & 33% extended PM intervals (24 pump sample).
• ALD High-K Dry Pump Process Deposition • 4 swaps & 200% lifetime extensions on some systems (20 pump sample).
• Trap/Pump Exhaust Blockage Models on LPCVD Nitride• >90% of unplanned stoppage events now prevented (60 pump sample).
• Solar Amorphous - Dry Pump Deposition, F & Cl Corrosion, Exhaust Blockage • 5 pump faults prevented,13 prevented unplanned production stops & 25 pump life time extensions
(180 pump sample).
• Abatement Combustor Blockage & Abatement Liner Deposition• Savings equate to 125 hours per CVD tool per year (8 tool sample).
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ISMI Symposium on Manufacturing Effectiveness 2011. 19th October - Advanced Process Control Session. Fault Detection & Classification (FDC) and Fault Prediction (FP) on Vacuum/Abatement Systems. Edwards Ltd. Michael Mooney, Shane Butler (NUI Maynooth)
Contents
Edwards Introduction
Edwards FabWorks-iMS & EADS
EADS Detectable/Classifiable Faults
EADS Development Process
EADS Fault Detection Example – TPU Liner Deposition
Fault Prediction – Particle Filters
Summary & Research Moving Forward
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ISMI Symposium on Manufacturing Effectiveness 2011. 19th October - Advanced Process Control Session. Fault Detection & Classification (FDC) and Fault Prediction (FP) on Vacuum/Abatement Systems. Edwards Ltd. Michael Mooney, Shane Butler (NUI Maynooth)
EADS project development requires:
• Identify probable FDC/FP models from Knowledge Base
• Data collection - optimisation of logged parameters and logging rates
• Data processing – data characterisation & transformation
• Data mining/modelling to configure models to customer process
• To distinguish normal operating characteristics from those associated with abnormal operation and fault based behaviour
• Training of the model: use of analytics, learning algorithms
• Testing of model using ‘unseen’ customer data
• System implementation of models
• Verification of success
• Reduced faults & downtime
• Fault/Technical analysis
EADS Iterative Development Process – Problem to Solution
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ISMI Symposium on Manufacturing Effectiveness 2011. 19th October - Advanced Process Control Session. Fault Detection & Classification (FDC) and Fault Prediction (FP) on Vacuum/Abatement Systems. Edwards Ltd. Michael Mooney, Shane Butler (NUI Maynooth)
EADS Model Development – Data Processing
• Data processing forms a key step in characterizing and
transforming the data in preparation for modeling, incorporating:
• Advanced moving window methods
• Smoothing, multiple time based differentials (gradient & variance)
• Event characterization (area & frequency)
• Gaussian Mixture Models (GMMs)
PUMP
FAULT
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ISMI Symposium on Manufacturing Effectiveness 2011. 19th October - Advanced Process Control Session. Fault Detection & Classification (FDC) and Fault Prediction (FP) on Vacuum/Abatement Systems. Edwards Ltd. Michael Mooney, Shane Butler (NUI Maynooth)
EADS Model Development – Machine Learning
• Machine Learning techniques have included:
• Artificial Neural Networks, Rule Induction/Decision Trees
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ISMI Symposium on Manufacturing Effectiveness 2011. 19th October - Advanced Process Control Session. Fault Detection & Classification (FDC) and Fault Prediction (FP) on Vacuum/Abatement Systems. Edwards Ltd. Michael Mooney, Shane Butler (NUI Maynooth)
EADS Model Development
Warning – Predictive Monitoring Started
1.5 months before fault
Warning - Recommend PM
15 days before fault
Alarm – Do not Start a New
Process
5 days before fault
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ISMI Symposium on Manufacturing Effectiveness 2011. 19th October - Advanced Process Control Session. Fault Detection & Classification (FDC) and Fault Prediction (FP) on Vacuum/Abatement Systems. Edwards Ltd. Michael Mooney, Shane Butler (NUI Maynooth)
Contents
Edwards Introduction
Edwards FabWorks-iMS & EADS
EADS Detectable/Classifiable Faults
EADS Development Process
EADS Fault Detection Example – TPU Liner Deposition
Fault Prediction – Particle Filters
Summary & Research Moving Forward
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ISMI Symposium on Manufacturing Effectiveness 2011. 19th October - Advanced Process Control Session. Fault Detection & Classification (FDC) and Fault Prediction (FP) on Vacuum/Abatement Systems. Edwards Ltd. Michael Mooney, Shane Butler (NUI Maynooth)
Edwards Thermal Processing Unit (TPU)
A. Head Unit
B. Combustion Chamber
C. Quench Unit
D. Cyclone Scrubber
E. Packed Tower Scrubber
POU Abatement Device
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ISMI Symposium on Manufacturing Effectiveness 2011. 19th October - Advanced Process Control Session. Fault Detection & Classification (FDC) and Fault Prediction (FP) on Vacuum/Abatement Systems. Edwards Ltd. Michael Mooney, Shane Butler (NUI Maynooth)
Equipment Layout & Fault Example
Fault example –
deposit build up on
Ceramic Liner,
aversely affecting
abatement efficiency.
1. Natural Gas & Oxygen
2. PFC Containing Process
Effluent
3. Radiation Exchange
4. Ceramic Liner
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ISMI Symposium on Manufacturing Effectiveness 2011. 19th October - Advanced Process Control Session. Fault Detection & Classification (FDC) and Fault Prediction (FP) on Vacuum/Abatement Systems. Edwards Ltd. Michael Mooney, Shane Butler (NUI Maynooth)
Gaussian Mixture Models
A probabilistic tool for density estimation
using a superposition of individual densities
where,
subject to,
Data Processing – Gaussian Mixture Models (GMMs)
• Gaussian Mixture Models (GMMs) have been applied as an
effective technique to detect TPU Liner Deposition faults
Component1
Component2
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ISMI Symposium on Manufacturing Effectiveness 2011. 19th October - Advanced Process Control Session. Fault Detection & Classification (FDC) and Fault Prediction (FP) on Vacuum/Abatement Systems. Edwards Ltd. Michael Mooney, Shane Butler (NUI Maynooth)
Abatement TPU Signal Tracking
• Distributions within two windows, before & after deposition
starts
T(oC)
Mode1
Mode2
Mode1Mode2
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ISMI Symposium on Manufacturing Effectiveness 2011. 19th October - Advanced Process Control Session. Fault Detection & Classification (FDC) and Fault Prediction (FP) on Vacuum/Abatement Systems. Edwards Ltd. Michael Mooney, Shane Butler (NUI Maynooth)
Abatement TPU GMMs by Operating Mode
Mode1 Mode2
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ISMI Symposium on Manufacturing Effectiveness 2011. 19th October - Advanced Process Control Session. Fault Detection & Classification (FDC) and Fault Prediction (FP) on Vacuum/Abatement Systems. Edwards Ltd. Michael Mooney, Shane Butler (NUI Maynooth)
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The content of this presentation is confidential and should not be distributed to a third party without prior authorization from Edwards. © Edwards Limited 2010
Abatement TPU GMM Signal Tracking
Mode1 – Component1 Tracking
Mode1 – Component2 Tracking
Mode2 – Component1 Tracking
Mode2 – Component2 Tracking
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ISMI Symposium on Manufacturing Effectiveness 2011. 19th October - Advanced Process Control Session. Fault Detection & Classification (FDC) and Fault Prediction (FP) on Vacuum/Abatement Systems. Edwards Ltd. Michael Mooney, Shane Butler (NUI Maynooth)
EADS Fault Detection Example – TPU Inlet Blockage
Alarm – Do Not Start A
New Process
3 days before unplanned
stoppage
Warning –
Recommend PM
5 days before unplanned
stoppage
Warning –
Predictive Monitoring Started
10 days before unplanned
stoppage
T(oC)
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ISMI Symposium on Manufacturing Effectiveness 2011. 19th October - Advanced Process Control Session. Fault Detection & Classification (FDC) and Fault Prediction (FP) on Vacuum/Abatement Systems. Edwards Ltd. Michael Mooney, Shane Butler (NUI Maynooth)
Contents
Edwards Introduction
FabWorks-iMS & EADS
EADS Detectable/Classifiable Faults
EADS Development Process
EADS Fault Detection Example – TPU Liner Deposition
Fault Prediction – Particle Filters
Summary & Research Moving Forward
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ISMI Symposium on Manufacturing Effectiveness 2011. 19th October - Advanced Process Control Session. Fault Detection & Classification (FDC) and Fault Prediction (FP) on Vacuum/Abatement Systems. Edwards Ltd. Michael Mooney, Shane Butler (NUI Maynooth)
Fault Prediction – Particle Filters – An Introduction
• By predicting evolution of the TPU fault indicator measurement
into the future, we can estimate the Remaining Useful Life (RUL)
• To address prognostic uncertainty it makes sense to represent the
TPU degradation level as a random variable, with an associated
probability density
• Suggests use of recursive Bayesian estimation techniques for prognostics
• Particle Filters implement a recursive Bayesian filter via Monte
Carlo sampling
• Approximates the state pdf as a set of particles and weights
• Capable of handling non-linear models and/or non Gaussian noise
processes
• Application to fault diagnosis and prognostic problems growing in recent
years. Examples include fatigue crack growth estimation [Orchard, 2007]
and lithium-ion battery degradation [Saha et al, 2009]
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ISMI Symposium on Manufacturing Effectiveness 2011. 19th October - Advanced Process Control Session. Fault Detection & Classification (FDC) and Fault Prediction (FP) on Vacuum/Abatement Systems. Edwards Ltd. Michael Mooney, Shane Butler (NUI Maynooth)
Fault Prediction – Model Based Prognostics
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ISMI Symposium on Manufacturing Effectiveness 2011. 19th October - Advanced Process Control Session. Fault Detection & Classification (FDC) and Fault Prediction (FP) on Vacuum/Abatement Systems. Edwards Ltd. Michael Mooney, Shane Butler (NUI Maynooth)
Fault Prediction – Particle Filters – Projecting Current State
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ISMI Symposium on Manufacturing Effectiveness 2011. 19th October - Advanced Process Control Session. Fault Detection & Classification (FDC) and Fault Prediction (FP) on Vacuum/Abatement Systems. Edwards Ltd. Michael Mooney, Shane Butler (NUI Maynooth)
Fault Prediction – Particle Filters – Estimate Remaining Useful Life (RUL)
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ISMI Symposium on Manufacturing Effectiveness 2011. 19th October - Advanced Process Control Session. Fault Detection & Classification (FDC) and Fault Prediction (FP) on Vacuum/Abatement Systems. Edwards Ltd. Michael Mooney, Shane Butler (NUI Maynooth)
Contents
Edwards Introduction
FabWorks-iMS & EADS
EADS Detectable/Classifiable Faults
EADS Development Process
EADS Fault Detection Example – TPU Liner Deposition
Fault Prediction – Particle Filters
Summary & Research Moving Forward
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ISMI Symposium on Manufacturing Effectiveness 2011. 19th October - Advanced Process Control Session. Fault Detection & Classification (FDC) and Fault Prediction (FP) on Vacuum/Abatement Systems. Edwards Ltd. Michael Mooney, Shane Butler (NUI Maynooth)
Summary & Research Moving Forward
• Edwards Advanced Diagnostics Services (EADS) successfully employs
FDC/FP techniques optimized for the behavior of vacuum & abatement
equipment in semiconductor applications
• Fault Detection & Classification (FDC) and Fault Prediction (FP)
• Multi-parameter rule-based system
• Gaussian Mixture Models – highly suitable with emerging ‘green’ modes
• Particle filters – for Remaining Useful Life estimates (RUL) & adaptable for different
processes
• FDC/FP techniques used reduce failures, downtime, improve maintenance
scheduling & pooling
• Research moving forward includes:
• Multi-model particle filters
• Predictions based on Process Count information
• Automated Learning
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ISMI Symposium on Manufacturing Effectiveness 2011. 19th October - Advanced Process Control Session. Fault Detection & Classification (FDC) and Fault Prediction (FP) on Vacuum/Abatement Systems. Edwards Ltd. Michael Mooney, Shane Butler (NUI Maynooth)
End
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