Pdf Solutions, Inc. · NASDAQ:PDFS
Pdf Solutions — 16th Annual PDF Solutions Users Conference 2019
23 slides from Pdf Solutions's conference presentation, Oct 15, 2019
Slide 1: S1.2 – Exensio Platform
16th Annual PDF Solutions Users Conference S1.2 – Exensio Platform October 15, 2019 Said Akar, GM
Slide 2: Forward-looking statements
This presentation contains forward-looking statements regarding PDF Solutions’ future products and business prospects that involve risk and uncertainty. Actual results could differ materially from those discussed. You should review PDF Solutions’ SEC filings, including its annual report on Form 10-K
Slide 3: Exensio Platform: Big Data Analytics and Control for Semiconductors
Exensio Platform: Big Data Analytics and Control for Semiconductors Process Control Detect and identify process or tool Process problems in manufacturing in real time Control Test Operations OEE optimization, escape prevention, and yield recovery Test Assembly Manufacturing Analytics Operations Oper
Slide 4: Exensio as a Platform
Exensio as a Platform Platform Exensio Platform Exensio Exensio Exensio Exensio Exensio Products Fabless IDM Foundry OSAT … • Manufacturing • Manufacturing • Manufacturing • Test • Future Analytics Analytics Analytics Operations Configurations • Test • Test • Process • Assembly Main Operations Opera
Slide 5: Motivation – Fabless Example
Motivation – Fabless Example Exensio Fabless Manufacturing Analytics Test Operations Assembly Operations Advanced Capabilities Advanced Capabilities Advanced Capabilities Monitoring Monitoring Monitoring Data collection / Control Data collection / Control Fabless Solutions Reporting Big Data Targete
Slide 6: Early Life Failure Detection (ELF)
Early Life Failure Detection (ELF) Machine Learning based solution to decide reliability risk – likelihood of Signature Collaborative “Expert” Library Learning Early Life failure in the field SYL PCM/WAT Spatial SBL Outlier Final Test Ensemble STL Manual Review SPL Sort Test Outlier Equipment ML A G
Slide 7: Point Solutions not Sufficient
Point Solutions not Sufficient FDC / APC TOOL FDC MES METROLOGY WIP E-MAIL / FTP / data files COMSUMABLES FAB Team ENVIRONMENTAL YMS MAINTENANCE SCHEDULES (PM) WAT Defect DESIGN Team YIELD/QUALITY EDAS TEST Team WAFER SORT/ FINAL TEST PACKAGE PROD ASSY Team Multiple Databases – Multiple User Interfa
Slide 8: Point Solutions not Sufficient – Tool Vs. Process Optimization
Point Solutions not Sufficient – Tool Vs. Process Optimization YieldAware Approach to Tool Control Traditional FDC/APC Sensor/Tool Audit: Approach Does the toolSensor achieve tool capability? Prioritization: APC/SPC Limits: Configuration Efficiency YieldAware Approach Exensio Unified Big Data Infras
Slide 9: Raw Files in a Data Lake Also Not Sufficient
Raw Files in a Data Lake Also Not Sufficient Intelligence Domain Knowledge Solutions Unique Data Machine Learning Unique Analytics Efficiency Ease of Use Semantic Models Collaboration Quality ROI Yield Infrastructure Data Quality Time to Performance Mkt End-to-End Control Trace
Slide 10: Semantic Models - A Key Element for Advanced Analytics and Control
Semantic Models - A Key Element for Advanced Analytics and Control • Semantic models allow for automatically cleaning, aligning, and interpreting data • Examples: – Aligning events in a fab with wafer data to answer question like “which wafers were processed with the new batch of resist”? – Mapping
Slide 11: Data Quality – End-to-End
Data Quality – End-to-End IC Design Fab Sort Assembly Final Test System Material MES/ WIP Fault Detection Descriptions and Control Defect & Equipment and Assembly / External Data Meta Data Equipment Product History Metrology Non-Lot System Sources In Hierarchy (FDC) Technology Equipment Equipment In
Slide 12: Data Quality – Completeness/Consistency – Data Collection/DEX
Data Quality – Completeness/Consistency – Data Collection/DEX Data Exchange Network - DEX FDC Assembly Data Collection and Data Collection and Control Control Analytics …….. …….. Data Collection and Data Collection and Control Control Test Exensio Characterization Platform Data Collection and Data C
Slide 13: Edge Deployment - Smart Testing
Edge Deployment - Smart Testing Foundry testers OSAT testers Event Trigger Feature TXT EXN Generation GPU/CPU Monitoring Table Join Execution Service Parquet Input Prediction Service Data Directory Exchange Platform Decision: Cassandra/Spark (output spec) Output EXN Test Directory OSAT testers No-Te
Slide 14: Direct Data Collection and Control
Direct Data Collection and Control >40 vendors and > 100 equipment models for manufacturing > 50 vendors and > 150 equipment models for assembly > 20 vendors and > 50 tester / prober / handler models for test Continuously Adding to the Supported Platforms PDF Solutions, All Rights Reserved 14
Slide 15: Data Quality – Traceability - Single Device Tracking without ECID
Data Quality – Traceability - Single Device Tracking without ECID o Required – Die Attach Assembly Exensio Operations – Record Wafer ID + XY to Strip ID + XY – Device Mark – Mark package with unique ID Assembly Equipment Integration – Upload strip map with ID + XY + Device ID – Singulation – Singula
Slide 16: Infrastructure – Performance
Infrastructure – Performance Exensio Big-Data as measured against Pure RDBMS architecture - Systems with same cost 45 RDBMS 40 (All Data) 35 40 X Performance Multipliers 30 25 Cluster 20 RDBMS 15 Cassandra (Meta Data) 10 (Data) 5 8X 8X Spark 0 Data Ingestion Data Retrieval Server Side Analytics Para
Slide 17: Example Benefits of Exensio Cloud Deployment
Example Benefits of Exensio Cloud Deployment Acquired company in 2015 that was one of the first to o Reduced costs compared to on-premise deploy web-native analytics capabilities for the o For deployed projects range is between 18% and 34% semiconductor industry on the cloud and integrated its capab
Slide 18: Domain Knowledge – Unique Data
Domain Knowledge – Unique Data Inline E-test Wafer Sort Final Test / Burn-in In-System DFI CV Core CVi Front End Optimization+Control Back End Optimization+Control In-Field Optimization+Control Exensio Enterprise Analytics Semantic model and AI-Enabled analytics Better Reliability (dppm, predictive
Slide 19: Ease of Use - Guided and Linked Analyses
Ease of Use - Guided and Linked Analyses L0 L1 Guided Guided Analysis Dashboard Analysis Drilldowns always be available form high level Top Level report. Bin Paretos, trends, etc. Dashboards What are top signals to be concerned L2 Guided about? Analysis Full Drill Down As needed, user can enter into
Slide 20: Solutions: Combining Products & Expertise to Deliver Results
Solutions: Combining Products & Expertise to Deliver Results Advanced Insights for Manufacturing (AIM) Process & Test – PDF’s primary Solutions infrastructure Hardware – Exensio SW Platform + ML + Change management Software – Drive specific outcomes IP DATA Users User System Decision Configuration L
Slide 21: Embedding Best-In-Class Technologies for a Complete Solution
Embedding Best-In-Class Technologies for a Complete Solution o PDF Focuses its development efforts on the areas where it can deliver value o We license and OEM best in class components to leverage the expertise of others, including the open source community o We handle all of the licensing from our
Slide 22: Exensio – The Organizing Principles
Exensio – The Organizing Principles PDF Domain Knowledge Fully scalable, big Automated Machine data system / analytics Learning Solutions End-to-End Data Unique data types End-to-End Analytics & Control For IC manufacturing IC Design Fab Sort Assembly Test System PDF Solutions, All Rights Reserved 2
Slide 23: Thank You
Thank You pdf-solutions pdfsolutionsinc pdfs.inc pdf_solutions pdf_cn
PDF Solutions — 16th Annual PDF Solutions Users Conference 2019 on 6ix