半導體生產自動化與 智慧工廠 UMC/IT 王邦明 5/22/2012

Transcription

1 半導體生產自動化與 智慧工廠 UMC/IT 王邦明 5/22/2012

2 Contents 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 P. 2

3 Information System of Foundry Planning Applications Production Information EDA AMAS Reporting Enterprise Applications Strategic Planning Supply Chain Planning Fab Planning Fab Scheduling MRP APC SPC RTD WFA Equipment Automation FDC Manufacturing Execution System EQ Online Hardware Service Production Data Warehouse Manufacturing Execution RCMS/ ECMS Transport Automation FOUP/ ID Infrastructure Network MCS/ RMS Sorter Interbay/Intrabay & STK Software Service EIS/CIS CRM e-business ERP E-Procurement E-HR Office Automation Portal/KM

4 Contents 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 P. 4

5 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 cycletime 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

6 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

7 CIM System Overview AM (Activity manager) RTD (Dispatching & u-scheduling) MES (Manufacturing Execution System) MES DB Continuous Loader SPC RCMS (Recipe Ctrl Mgmt) APC (Advance Process Ctrl) EAP (Eqp Automation Program) MCS (Material Control System) Intrabay Interbay SDB (Summarized Database) Views Views Views Views EDA Loader EDA (Klarity ACE XP) FDC (Fault Detection & Classfication) EQ EQ EQ EQ EQ EQ EQ EQ Stocker Stocker Stocker Stocker Stocker Stocker Reports Reports Reports EDA GUI Equipment efab

8 Operation Automation

9 Definition of Automation Modes Job Prep. (Lot selection) Transfer Lot To Eq. Verify Eq. & Lot Status Job In Activate Process Data Collection Job Out Transfer Lot To next Dest. Semi-Auto Auto-2 Auto-3 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

10 Automatic Material Handing System Interbay rail 3FL 2FL 1FL Stocker OHT (Intrabay) OHB (Overhead Buffer)

11 Engineering Automation

12 Automatic Engineering System Offline Micro-view Historical Analysis Real time In site Control FDC Online APC CMP APC PH APC ETCH APC EDA SPC Product SPC Monitor SPC WAT SPC EQ SPC FE SPC Equipment Automation Historical Engineering Data Analysis Process Control via previous processed results Process Control via past data Avoid Human MO

13 Intelligent Factory

14 Achievement of FAB automation Today Systems Scaled for > 100k High product mix operations enabled using automation Pervasive use of Standards for carriers, equipment interfaces, and software systems Some Wafer Level Tracking & Recipe/Parameter Changes Aggressive focus on lot cycle time reduction 100% AMHS Storage and Intrabay Transport Systems in place FOUP carrier tracking using ID tags at load ports Very high use of APC and Yield systems APC, Yield, and E-Manufacturing Capabilities (EEC) Data R2R Partner, Customer Or Supplier FDC SPC Recipes Yield PCS E-Diag EPT Some use of E-Diagnostics Most equipment data feed through SECS/GEM & IF/A communications Equipment Performance Tracking (EPT) Data Factory Scheduler And Material Control On-line Equipment Control Systems Manufacturing Execution Systems All lots and wafers tracked and processed using the MES

15 Contents 半導體智慧工廠的新挑戰 P. 15

16 半導體智慧工廠的新挑戰 Predicable PM Virtual metrology Waste Time reduction Material consumption Intelligent Data mining P. 16

17 P. 17 Q&A