Solutions for Agile Semiconductor Manufacturing. Sanjiv Mittal Applied Global Services Applied Materials October 6, 2009

Transcription

1 Solutions for Agile Semiconductor Manufacturing Sanjiv Mittal Applied Global Services Applied Materials October 6, 2009

2 What Is Agile Semiconductor Manufacturing? Agile (dictionary) 1: marked by ready ability to move quickly and easily 2: having a quick resourceful and adaptable character Agile semiconductor manufacturing: Ability to switch products and processes rapidly to changing customer demand

3 How to Achieve Agile Semiconductor Manufacturing Fast cycle time Integrated planning systems Connect customer demand to factory loading & lot prioritization Equipment control and predictability Rapidly switch products & processes Flexible cost structure

4 Factory Solutions for Agile Semiconductor Manufacturing Automation technology Integrated planning Cycle time Equipment control Predictability Process control Flexible cost structure

5 Automation Technology

6 Best Practices Automation Technology Integrating automation solutions onto common platforms Full material automation Dispatching software to manage cycle time Prioritizing lots based on customer demand Integration with supply chain Pervasive equipment control Online SPC Future trends Advanced scheduling Investment in 200mm productivity

7 Integrated Platforms Shorten Implementation Time Reduce CoO Reduce Waste EXECUTION AND MATERIAL CONTROL MES Material Control Enable quick changes to manufacturing strategies ADVANCED PRODUCTIVITY Real-Time Dispatching Short Interval Scheduling Factory Simulators Optimize operations Lower cycle time EQUIPMENT AND PROCESS CONTROL Fault Detection Run-to-Run Control Equipment Performance Tracking Equipment Diagnostics Increase control Reduce excursions Increase OEE

8 Dispatching and Scheduling Reduces Cycle Time and Improves On-Time Delivery Matches upstream material flow with downstream availability in real time Incorporates multistep constraints and objectives Identifies Implementing multiple Real-Time paths for Dispatch near optimal decisions Integrated planning ensuring on-time delivery Incoming WIP Real-Time Dispatch Implemented Current Production Downstream Availability Total No. Lots Cycle Time M01 M02 M03 M04 M05 M06 M07 M08 M09 M10 M11 M12 M13 M14 M15 M16 M17 M18 M19 M20 M21 M22 M23 M24 M25 M26

9 Equipment Control Technology

10 Equipment Control Technology Best Practices Fault detection & classification (FDC)for excursion control Run-to-Run process control to improve Cpk and control process drift Reduce set up time & test wafer usage Strict PM practices, measure PM success rate Tool & chamber matching & use of golden tools Future trends Advanced equipment control Virtual metrology

11 E3 Equipment Control Platform Fault Detection & Classification Tool Component level FDC Failure Predictions ( CMMS) Tool Interdictions ( MES / Tool) FDC Notifications LCL Run-to-Run APC Model Development Lot & Recipe Control ( MES / RMS) DC Power (KW) Rs Tool/ Ch Equipment Management Maintenance Planning Durables Tracking Equipment Performance Tracking Equipment Automation Layer

12 FDC Detects RF Noise Excursion on Etch Chamber RF noise causes wrong temperature readout and fluctuations during process Chamber A Chamber B When roof temperature goes down, roof heater power goes up to bring temperature back to set point

13 FDC Facilitates Chamber Matching 50V difference in electrostatic chucks Chamber A Chamber B 4 second difference in rampdown time

14 PM Best Practices Improve Equipment Control Key Enablers for 1 st Time PM Success: Parts management Following parts cleaning BKM s Adherence to strict PM procedures Unscheduled Downtime Improvement Under Performance Service Agreement Quarterly Average of Unscheduled Downtime, % 14.0% 12.0% 10.0% 8.0% 6.0% 4.0% 2.0% 0.0% Ave All Process Tools Ave All Tools of the Platform With the Worst Initial UDT Q1-08 Q2-08 Q3-08 Q4-08 Q1-09 Data set: All process tools data set = chamber. Worst tool data set = chambers

15 Cost Flexibility

16 Best Practices Cost Flexibility Tie tool running cost to factory loadings Shift to usage-based PMs Maximize savings from tool idling strategies Remote diagnostics for rapid troubleshooting Future trends Increased adoption of remote diagnostics Predictive maintenance Tie subfab equipment usage to process tool usage

17 Remote Diagnostics Speeds Repair Time Complete Support Local Secure, customerconfigured data access Regional Escalation matches expertise to situation Global Central knowledge network enables precise labor and parts usage >1,300 tools connected

18 Remote Diagnostics Helps Variabilize and Reduce Cost Idle Resources Overtime / Lost availability Production Support Level Time Traditional Fab Model Time Variable Service Model Improved response time Improved repair time Better uptime Reduced parts usage Flexible workforce

19 Variabilizing Utility Cost Problem: Fab energy consumption does not track fab loading Solution: Systematize the sub-fab: facility usage tied to process tool usage reduced utility consumption Source: 1997, 2000, 2002 SEMATECH Energy Research, presented at SEMICON Europa 2005 KWH Usage Without Sub-fab System With Sub-fab System

20 Summary Rapidly changing customer demand requires manufacturing agility Agility can be achieved by leveraging automation and equipment control technologies Increased collaboration can increase agility

21 Collaboration Increases Agility: The New Business Model With Infrastructure Companies With WFE and Automation Companies With Customers OS Components Process & Integration Enterprise Components R&D Collaboration Best Practices & Known Methods Hardware Components Hardware & Software Customer Support