iot solution conference 2016

Striving for Zero DPPMMichael Schuldenfrei, CTO

2

Optimal+ is the Leader in Semiconductor Big Data Analytics

© Optimal+ 2016, All Rights Reserved

Over 90%Foundry &

OSAT coverage

YieldUp to 2%

Quality50% less escapes

Efficiency

Up to 20%

35B+Chips (in 2015)

TTRUp to 30%

And others ….

3

Going Beyond Semiconductors…


TestReworkGenealogy

IC & Multi Chip

…

1

N

3

2

Boards Systems In Use ReturnsRework

Test & Process data

Usage Data

Performance data

Reliability Data

Automotive

Game Consoles

Super

Computing

Graphic Cards

Lead design partner

4

Much More than “Just” MES Data


Across the value chainBoards & Systems

Deep Parametric Test DataGenealogy

Repair/ReworkMES (=Process) Data

RMAs

Collection

Big Data AnalyticsAdvanced Algorithms

Machine LearningAutomated Rule Engine

Detection

AutomaticDistributedControlled

Fully integrated into existing systems

Action

Optimal+ looks at the combination of PROCESS and PRODUCT dataDeep Parametric data (unavailable in MES) is a KEY ingredient when striving for zero DPPM

Clean Augmented Data = Common Language across the Organization

5

From Analytics to Action


Source: Gartner

Optimal+ provides the entire spectrum from Data to Action through Prescriptive Analytics

O+

O+

O+

6

“The New World” Driving New Needs


Connected & Autonomous

Cars

Smart Wearables

Internet of

Things

HWSecurity

SiP & 3D ICs

Industry 4.0Stretching the Performance Envelope

System complexity, Performance margins

Superior Quality No-Fail, DPPB, Mission-critical

In-use ConfigurabilityFunctionality-on-demand, OTA..

Brand ProtectionDevice DNA, in-use Authentication

7

Focus on Quality


Systems are becoming Mission Critical Shifting from “Defects per Million” to “Defects per Billion”

8

RMA & Failure Analysis


No Problem Found32%

Fab Process28%

Test Program10%

Test Operation4%

Test Equipment26%

No Problem Found Fab Process Test Program Test Operation Test Equipment

Source: One of the top-five fabless semiconductor manufacturers

9

The Quality Question…


IS “GOOD” REALLY GOOD?

10

It All Starts with the Data


The “3 C’s” for data collection

Complete

Clean

Consistent

11

Making it Actionable


To be Actionable, data must:Be available quicklyBe processed immediately and automaticallyBe connected to business processes

Looking at each Manufacturing Step

12© Optimal+ 2016, All Rights Reserved

Examples…

Escape Prevention – Freeze A freeze occurs when a tester instrument becomes “stuck” and repeatedly returns the same or similar result for a sequence of parts

14

Escape Prevention – Test Process


A so-called “good” part was subjected to just 363 tests while the rest of the good parts had over 2460 tests

The number of tests executed on good devices should be relatively stable

15

Escape Prevention – Test Program


~95 Sigma

~95 Sigma

Extremely loose test limits may mask real test performance problems

16

Station Health


Aggregated performance across the actual station locations is shown belowIt is clear that a Temperature Test parameter is significantly impacted by the actual station location

TemperatureSpeed

Power

This is a quality issue because the boards were not tested at the right temperature!

17

Outlier Detection


Measurements that are within spec. limits but are well outside the typical range for similar devices are suspectThese devices must be detected and prevented from shipping

Combining Data from Multiple Steps


19

Cross Operation Analysis and Correlation


Connect data from across multiple operations to find hidden relationships:• Root cause analysis and RMA

investigation• Bi-variate and multi-variate outlier

detection• Explanation of “No Problem Found”

Paste ICT AOI AXI FCT1 FCT2 FCT3 … ShipDB RMA

20

Data Feed Forward – Make it Actionable



ImplementationsWithin a single factory (OSAT, CM, etc.)Between multiple factoriesReal-time (test program integration)

Example scenariosOutlier Detection – drift analysisPairing – cherry-picking for power & speed combinationsTest program tuningTest step reduction

21

Data Feed Forward (DFF) for Drift



Collect detailed product, test and process data from the assembly line

Apply advanced analytics as data is collected

Provide the resulting data to subsequent steps in real-time (“Data Feed Forward”)

FCT Tester

1. Board ID

2. Previous Measurements

Test Program runningFunctional test

Real-time data!No test time impact!

O+ DB at EMS

Example of parametric drift detection between operations

Looking Across the Supply Chain


23

“No Trouble Found”


IC3

IC2

PCB

IC1

Combinations of chips causing issues:

24

DFF/DFB between Industries


Distributed Supply Chain

Electronics OEM

Supplier 1

Supplier 2

Supplier 3

Is this possible???

25

What Data Sharing can Achieve


Lower RMA CostsBoard-to-Chip correlationsFast Root Cause analysisOn-line RMA Prevention RulesReduced NTF rates

Improved Quality and Time-to-QualityReduced time to reach board level DPPM goalsOn-line Quality link between chips and boardsEscape Prevention and Outlier Detection RulesEnhanced Functional Safety (ISO 26262)

More Efficient Test Processes – Adaptive Test

Test “suspect” parts moreTest “perfect” parts less

Better System PerformanceAvoid in-Spec Chips with marginal performance at boardSmart Pairing – Select the right chips for the right system board

26




Other Supplier

Automotive

Game

Consoles

Super

Computing

Graphic Cards

The simple case – the OEM also manufactures chips

27




Electronics OEM

Supplier 1

Supplier 2

Supplier 3 But what about between an electronics OEM and its

suppliers?

28

Cisco & Optimal+


Source: Cisco, Southwest DFT Conference, Austin 2016

29




Electronics OEM

Supplier 1

Supplier 2

Supplier 3 By enabling just board level data to chip suppliers, quality levels can

be dramatically enhanced

Board data

Board data

Board da

ta

30

Summary


Achieving quality starts with high quality dataAdvanced statistical processing can detect anomalies in manufacturing and prevent bad products reaching customersBreaking down test silos has tremendous benefits for• Quality, Efficiency, Yield

Data Feed Forward, Quality Index already a reality for major chip manufacturers within their supply chainData Feed Backwards from electronics to semi is coming soon…What are YOU doing to achieve zero DPPM?

31

Thank You!

iot solution conference 2016

Data & Analytics