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半導體生產自動化與
智慧工廠
UMC/IT 王邦明
5/22/2012
P. 2
半導體產業資訊系統
半導體生產自動化系統
半導體智慧工廠的需求
半導體智慧工廠的新挑戰
Contents
EQ Online
Equipment Automation
APC FDC RCMS/
ECMS
Transport Automation
Interbay/Intrabay & STK
FOUP/
ID
MCS/
RMS Sorter
Manufacturing Execution System
SPC RTD WFA
Manufacturing Execution
Infrastructure
Network
Hardware
Service
Software
Service
Planning
Applications
MRP
Fab
Scheduling
Fab
Planning
Supply Chain
Planning
Strategic
Planning
Enterprise
Applications
ERP
CRM
EIS/CIS
Portal/KM
e-Business
Production Data Warehouse
EDA AMAS Reporting
Production Information
Information System of Foundry
Office
Automation
E-Procurement
E-HR
P. 4
半導體產業資訊系統
半導體生產自動化系統
半導體智慧工廠的需求
半導體智慧工廠的新挑戰
Contents
Production Automation Introduction
to replace all human operations and decisions by
means of computer hardware and software.
to develop intelligent systems which can simplify
human works.
Major Benefits: 1. Eliminate the human operation cost in Fab
2. Increasing the throughput and reducing cycle-
time
3. Help yield control and advanced process
development
4. Support more flexible and complex
manufacturing operations
5. Optimizing and standardizing business process
to reducing waste and miss-operation
Production Automation Scope
Operation Automation
Replace Human Efforts
=>Reduce HR Cost, Reduce M/O,
Improve CT, Improve Productivity,
Increase MM ratio
Engineering Automation
Support Engineer do job better and
smarter
=>Sustain EQ variance, Improve
quality, Yield, Support RD, Reduce
Engineering Cost, Improve Time-to-
Market
EAP (Eqp Automation Program)
Equipment
CIM System Overview
MCS (Material Control System)
EQ
Intrabay Interbay
Sto
cker
EQ
EQ
EQ
EQ
EQ
EQ
EQ
Sto
cker
Sto
cker
Sto
cker
Sto
cker
Sto
cker
MES (Manufacturing Execution System)
Continuous
Loader
Views
Views
Views Views
eFAB
Reports
Reports Reports
EDA
Loader
EDA GUI
SDB (Summarized
Database)
MES DB
EDA (Klarity
ACE XP)
RCMS (Recipe Ctrl Mgmt)
FDC (Fault Detection
& Classfication)
APC (Advance Process Ctrl)
SPC RTD (Dispatching &
u-Scheduling)
AM (Activity manager)
Operation Automation
Job Prep. (Lot selection)
Transfer Lot
To Eq. Job In
Activate
Process
Data
Collection Job Out
Transfer Lot
To next Dest.
Verify Eq. &
Lot Status
Semi-Auto
Auto-2
Auto-3
Definition of Automation Modes
Job Prep. Transfer
Lot to Eq.
Verify
Eq&Lot
Status
Job In Start
Process
Data
Collection
Job Out Transfer
Lot to next
Dest.
Manual Mode Human Human Human Human Human Human Human Human
Semi-Auto Mode Human Human System System System System System Human
Full Auto-2 Mode Human System System System System System System System
Full Auto-3 Mode System System System System System System System System
OHT (Intrabay) Stocker
Interbay rail
1FL
2FL
3FL
OHB (Overhead Buffer)
Automatic Material Handing System
Engineering Automation
Automatic Engineering System
EDA
Offline
Historical
Engineering Data
Analysis
SPC Product
SPC
Monitor SPC
WAT SPC
EQ SPC
FE SPC
Process Control
via past data
Online
Equipment Automation Avoid Human MO
APC
CMP
APC
PH APC
ETCH
APC
Process Control
via previous
processed results
FDC
Micro-view
Historical Analysis
Real time
In site Control
Intelligent Factory
Very high use of APC and Yield systems
Manufacturing Execution Systems
Some Wafer Level Tracking &
Recipe/Parameter Changes
100% AMHS
Storage and
Intrabay Transport
Systems in place
Equipment Performance
Tracking (EPT) Data
Syste
ms S
cale
d
for
> 1
00k
Aggressive focus
on lot cycle time
reduction
All lots and wafers
tracked and processed
using the MES Some use of
E-Diagnostics
Data
SPC R2R FDC
Yield PCS EPT
APC, Yield, and E-Manufacturing
Capabilities (EEC)
Recipes
E-Diag
On-line Equipment Control Systems
Partner, Customer
Or Supplier
High product mix
operations enabled
using automation
FOUP carrier
tracking using ID
tags at load ports
Pervasive use of Standards for
carriers, equipment interfaces,
and software systems
Factory Scheduler And Material Control
Most equipment data feed through SECS/GEM & IF/A communications
Achievement of FAB automation Today
P. 15
半導體智慧工廠的新挑戰
Contents
P. 16
Predicable PM
Virtual metrology
Waste Time reduction
Material consumption
Intelligent Data mining
半導體智慧工廠的新挑戰
Q&A
P. 17