Global Test Operations Demand Transparency and Automation for Rapid

Leveraging of Data and Enhanced Competitiveness

Debbora AhlgrenVP Sales & Marketing

OptimalTest

Tutorial Outline

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• Trends/Pitfalls/Challenges

• Improved Business Model

• Define Control/Monitor For Test Operations

• Focus on Early Detection/Warning Process

• ‐Why/What/How/ROI

• Global Test Operations 

• ‐ IDM, Fabless, Foundry, OSAT

• IT Configuration Options

• Benefits/Risk Mitigation for Early Detection

• Low Risk/High Return Solution

• ‐ Yield, Cost, Operational Efficiency, TTM

• Summary

• Migration to Fabless Model with Multiple Foundries & OSATs

• Geographically Dispersed Integrated Enterprises

• Rising Complexity of Deep Sub Micron Devices

‐ Data Explosion: Device Size and Difficulty In 

Isolating Systematic Faults

• Increasing Consumer Driven Marketplace

Industry Trends

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• Hybrid IT Infrastructure – Networks, Databases &

Software Tools

• Home Brewed Software Fills The Gaps

• Data Integrity Always An Issue

• Sub‐optimized Supplier Approach VS End‐to‐End

Optimization

• Lack of Trust/Transparency Among Partners

Challenges With Today’s Model

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• Overall Operational Efficiency Suffers

• Lost/Incomplete Data/Data Not Used

• Delay In Reacting To Issues/Changes

• Problem Ownership/Resolution Not Crisp

• Impacts Yield, TT, TTM, Re‐test, Quality, etc.

Shortcomings With Current Model

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• Requires Software Based Solution To Turn Data Into Actionable Information On Demand

• Vision Must Be Shared Across Supply Chain Allowing Adequate Transparency

• Today’s IT Networks, Database Management, Software Analysis Tools Provide Mature Enablement

• Optimizes Entire Supply Chain Benefiting All Partners

Holistic Solution For Supply Chain

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• Real Time Control – Station Controller on Test Cell for Real Time TTR, Yield Reclamation, Efficiency, Outlier Detection

• Real Time Monitoring – Control Room View of Fleet of Testers in Real Time for Yield Degradation Prevention, Efficiency, Immediate Quality Attention

• Near Time Early Detection – Early Detection Engine, Notification Application & Dashboard for Product & Testing Issues: Yield, Degradation Prevention & Reclamation, Efficiency and Quality

• Off‐line Analysis & Simulation – All Test Results, All Products, All Testers, Processes. Simulation Analysis & Reporting Tool Applications for TTR, Yield, Efficiency, Outlier Detection, Quality

Levels of Control/Monitoring for Test Ops

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• Real Time Detection Is Great, But‐ Requires Station Controller‐ Lacks “Horizontal” Fleet Control

• Most Issues Detected Based On MANY Lots & Testers‐ 60% Found With Near Time Early Detection

• Implementation Less Intrusive Than Real Time• Provides Baseline of Fleet, Product & Process• Re‐evaluation of Test Results Across Other Devices and Testers

Focus On Early Detection Solution

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• Early Detection/Warning Process Leverages Actionable Data In Near Real Time

• Identifies Emerging Issues Prior To Significant Impact

• Early Detection Engine Automatically Scans Data To Identify Issues

• Automated Near Real Time Monitoring and Reporting

• Includes Next Step Recommendations

Transparency Across The Supply Chain

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• Re‐evaluation of All Test Results – Control, Quality & Health Check. Detects Issues & Inefficiencies for: Yield, TT, Productivity, Quality & Data Integrity

• Detects Outlier Equipment – Finds Trending & Marginal Equipment Before Becoming Significant

• Monitor Product Indicators – Test Program Instabilities & Marginalities, Bin Switching, Yields, etc

• Detects Operational Issues – Pauses, Set‐ups, Re‐test

• Verifies Correct Product Flow & Disposition

What Early Detection Solution Does

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• Data Logs Captured From Any Origin & Any Format Immediately After Each Run/Pass/Execution‐ Data Sources: Station Controller, Software Proxy On Tester Or Data Stream Such As STDF

• Data Scanned Using Automated Rule Engines‐ Product Level Rules After Each New Data Log‐ Cross Entity Rules After Each Shift or Per Day

• Automated Action Taken Once Issue Is Detected‐ Email or Alert Including Possible Corrective Action

How Early Detection Solution Works

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Architecture of Early detection solution

Data Scan Engines

Common DB

Rule FeedbackScheduled Analysis and 

Reports

Any Other Testers

Email Notification

Product Rule Engine

(End of Wafer or Lot)

Cross Entity 

Rule Engine(End of 

Shift or Day)

DispositionAutomatic Disposition(e.g. hold/release lot)

Eng. Defines Rules

Station Controller

With attached report

ProxyDashboard

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• Issue Within Test Cell‐ Data Log Completed At End of Wafer‐ Next Wafer Starts Test While Early Detection Engine Scans Data‐ If Issue Found on 1st Wafer, Warning Issued, Action Taken

• Issue With Fleet Comparison‐ Data Logs Are Captured From All Testers‐ At End of Shift or Daily, Early Detection Engine Looks For Outliers VSBaseline (i.e. Test Time Always Lower Than Rest of Fleet)‐ If Outlier Found, Warning Issued, Action Taken

• Possible Warning Methods‐ Email or Dashboard Alert‐ Connection To Work Flow System Issues a Hold‐ Proxy On Tester Can Stop Tester If Required

Early Detection Examples

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• Significantly Improves Data Integrity

• Provides Higher Overall Quality

• Fewer Test Escapes Without Alarming Customer

• Superior Operational Efficiency

• Tighter Control On Test Times, Test Program Releases

Early Detection Leverages Actionable Data

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• Prevents Yield Degradation

• Enables Yield Reclamation

• Significantly Lowers Retest

• Accelerates Yield Learning

• Reduces Capital Expenditures

Additional Early Detection Benefits

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• Previously Showed Early Detection/Warning Process For One Set of Products & One Test Floor Fleet

• Applies To Testing Sites Of IDMS, Fabless, Foundries & OSATs

• Value In Implementing Across Multiple Sites

• Provides Near‐time Capability Worldwide For Supply Chain Management

• Additional Off‐line Capability For Corporate Level To Monitor Business Units/Divisions Worldwide

Early Detection Across Global Operations

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IDM Europe• Near-Time• Off-Line

• Full Remote capabilities

Taiwan Operations•Real-Time•Near-Time

•Off-line

Singapore Operations•Real-Time•Near-Time

•Off-line

Korea Operations•Near-Time

•Off-line

China Operations•Near-Time

•Off-line

Early Detection across the IDMSite or supply chain

•Station Controller •Real-Time –Proxy

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Fabless US• Near-Time• Off-Line

Taiwan Operations•Near-Time

Foundries• Real-Time

OSATs• Real-Time

Singapore Operations•Near-Time

Foundries• Real-Time

OSATs• Real-Time

Korea Operations•Near-Time

Foundries• Real-Time

OSATs• Real-Time

China Operations•Near-Time

OSATs• Real-Time

US Operations•Near-Time

Foundries• Real-Time

Early Detection across the Fabless supply chain

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Foundry Taiwan• Near-Time• Off-Line

Taiwan OSAT-1 Singapore OSAT Korea OSAT

Taiwan OSAT-2

Early Detection across the Foundry:It’s Site or Supply chain - (Testing network)

Station Controller

China OSAT

Taiwan OSAT-3

STDFProxy

STDF

STDF

STDF

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OSAT Taiwan• Near-Time• Off-Line

Taiwan OSAT-1 Singapore OSAT Korea OSAT

Early Detection across the OSAT:It’s Site or Supply chain

Station Controller

China OSAT

STDFProxy

STDF

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Operationally – how does it work?Global Test Operations solution

• Headquarters • Servers, DB & Applications (Scan Engines, Reports or Dashboard)

• Clients to the Testing team & Operations team

• Regional operations–2 mode of communications:

• Terminal server via headquarters with remote access, OR

• Local regional installation - Servers, DB & Applications (Scan Engines, Reports, Dashboard) with Clients

• Data*: From Subcons/operations Headquarter : 3 options that can work all together• Station Controller (Meaning Subcon has Station Controllers installed on some of their testers at their site)

• Proxy originator (Meaning Subcon has Proxy installed on some/all of their testers at their site)

• Any Data-log from a Data Stream (STDF) (Meaning Subcon/Operations have some testers that don’t have controllers or a proxy)

• Turning the data into Actionable data • Once the data is in the Headquarters data-bases it is being processed and serves 2 purposes:

• Early detection solution : E-Mails ,Reports, Dashboard,

• Analysis & simulation: (i.e Adaptive TTR, Bin switching etc)

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Global Operations ‐IT Configurations options : 

Headquarters

Configuration 3Foundry/OSAT

Configuration 2Foundry/OSAT

Configuration 1Foundry/OSAT

TW, Kr, Ch, Sing Etc  

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• Time to Actionable Data Reduced From Hours or Days To Minutes

• Data Integrity Clarifies Cost Issues Within Supply Chain

• Early Detection Solution Scalable

‐ Real Time Advanced Adaptive Testing

‐ Aggressive Test Time Reduction

‐ Comprehensive Outlier Detection Solutions

Additional Supply Chain Optimization

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• Non‐Intrusive

• Easily To Implement With Legacy Systems

• Non Mission Critical

• Low Cost Support

• Immediate Benefits with Quick ROI

Risk Mitigation

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• Actionable Data Drives The Results

• Strategic Solution Scales With Business Model, Geography & Technical Requirements

• Benefits All Supply Chain Partners

• Significant Improvements To Key Metrics‐ Yield, Cost, Operational Efficiency, Time To Market

Low Risk/High Return Solution

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• Near Time Early Detection Solution Optimizes Entire Supply Chain With Adaptive Learning

• Accurate, Effective, Timely

• Data‐‐‐ Information‐‐‐ Knowledge‐‐‐ Action

• How Does Your Supply Chain Measure Up?

Summary

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