Leveraging Cross-Operational Test Data for Manufacturing Yield and DPPM/RMA Improvements

LEVERAGING CROSS-OPERATIONAL TEST DATA FOR MANUFACTURING YIELD AND DPPM/RMA IMPROVEMENTS

NVIDIA — The Visual Computing Company Since 1993, NVIDIA has pioneered the art and science of visual computing. Our passionate work has resulted in thousands of patented inventions, breakthrough technologies, deep industry relationships and a powerful brand.

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FACTS Founded in 1993

Jen-Hsun Huang is co-founder, president and CEO

Listed with NASDAQ under the symbol NVDA in 1999

Invented the GPU in 1999 and has shipped more than 1 billion to date

FY13: $4.3 billion in revenue

8,200 employees worldwide

5,500 patents issued, allowed, or filed

Ranked #6 “greenest” company in America by Newsweek in 2012

Headquartered in Santa Clara, Calif.

NVIDIA Confidential Information, OptimalTest / ITC 2013 conference only.

Manage the manufacturing and testing of the chips that support all of these markets

Test subcontractors in Taiwan and Hong Kong Large diverse product and package portfolio NVIDIA Test and Product engineers expanding globally in Taiwan, Bangalore, Bristol, Richardson, and Santa Clara

NVIDIA Silicon Operations


Problem Statement: Our existing yield solutions have become less effective in improving yields and quality Test data was spread out across multiple tools

Difficult for everyone to access globally Tedious to combine & analyze data from different operations (many custom scripts)

Could not easily use data from one operation to take action at another operation

NVIDIA Silicon Operations


WAT CP FT Functional Test

RMA

Yield Tool #2 (no unit ID)

Yield Tool #3 (w/ unit ID)

• Yield Monitoring • Target Yield Analysis

• Special Yield Analysis inclusive of unit ID tracking

Utilization Tool

RMA Database

• Track customer returns

• Planning Optimization • Financial reconciliation

Production Data Flow Earlier This Year


WAT CP

Initial Success with OptimalTest

Objectives: Acceleration of yield learning

Faster access to accurate data Develop Best Known Methods across our global teams Early detection of excursions

Results

Increase in yield and productivity Common yield improvement practices across different groups

• CP Yield Monitoring • Target Yield Analysis


ISUM Histogram

ISUM Tester Box Charts

Using OT WAT and CP Analysis

Hard Bin Distribution

Site-to-Site Issues


WAT CP FT Functional Test

RMA

Consolidating Data Under OptimalTest

Enable WAT+CP+ FT + Functional Test + RMA to OptimalTest Improve time it takes to access data, improve quality of data Support End-to-End Analysis and Correlation Unified Source for Operations Manufacturing Test Data

Cross-Operational Analysis leads to better yields and quality


OptimalTest at NVIDIA Today

Operational Efficiency

Simulate yield impact of limit changes Improve success rate in meeting prime SKU demand

Create less unwanted inventory

DPPM & RMA Improvements

Better RMA Correlation Across all operations

Screen Excessive Drift or Temperature Dependencies


Utilizing Cross Functional Data


Ex: Burn-in Drift for Automotive Products

ATE Measurement is taken at a pre-Burn-In Final Test step, FT1 Data is loaded into OT Database At the post-burn in Final Test step FT2, OT runs a process (OTProxy) on each tester which waits for a request from the OT API OT queries and downloads the pre-BI data from the remote server to the workstation New ATE Measurement is taken at this FT2 step and the ATE program will then determine pass/fail based on delta drift between the two FT insertions, FT2 – FT1


Test program running

FT1 operation

OPTIMALTEST Database

Tester with OT-PROXY

Unique ID

Using Data-Feed-Forward (for Drift)

FT1 Measurements FT1 Data



FT1 operation



Unique ID


FT1 Data


FT2 operation

Unique ID

FT1 Measurements





FT1 Data

Drift Test FT2-FT1= pass/fail

Real-time Data-Feed-Forward. No test time impact!

FT1 Measurements


FT2 operation


Ongoing Collaboration With OptimalTest Virtual Tests

Build custom parameters and calculations within OT Rules to augment part-level data (ex. median ISUM) Combine multiple custom parameters to gauge the quality of a part

Data Feed Forward Preventative signature profile with “Escape Prevention” rules Real-time bin-switching infrastructure to create a “safety net” to avoid future RMA’s Simulate screening of escapes based on RMA analysis learnings, update rules if effective

OptimalTest = Disruptive Innovation

Perf

orm

ance

Time

Long-Term ROI

Traditional manufacturing

operations tools


Cycle For Preventing Future RMAs

Collect data on RMA across all operations

Correlate RMA to Real and Virtual Test

Establish “Signature Profile”

Simulate effectiveness “Did it catch RMA?”

Finalize “Signature Profile” Update Rules deck

Escape Prevention flags a unit with “Signature Profile”

Data Feed Forward Bin switch the good part to fail at

future step

No, Improve Correlation


Summary

Partnering with OptimalTest is:

Providing NVIDIA with a unified source for all mfg. test data Supporting our goal for making real-time manufacturing decisions

Using Data Feed Forward to create new binning tests

Enabling us to resolve manufacturing problems and errors faster CONTINUING TO IMPROVE OUR YIELDS AND QUALITY

More ideas to come, this is only the tip of the iceberg!

Date post:	27-Jul-2015
Category:	Technology
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Leveraging Cross-Operational Test Data for Manufacturing Yield and DPPM/RMA Improvements

Technology