Data Analytics for Semiconductor Industry Applications: Yield and Reliability Analysis

Application of data analytics in semiconductor industry and analysis of large industrial data contribute to improved operational efficiency and business processes. This course equips participants with knowledge about applications of data analytics in the field of yield and reliability analysis in semiconductor devices/systems.

Yield optimisation has been regarded as one of the critical goals in the semiconductor operations and IC manufacturing. Reliability issues in semiconductor devices/systems lead to failure of devices/systems in turn resulting in poor yield. Big data proves to be imperative in semiconductor industry and data processing requires specific data analytics with specific models for data visualisation and analysis.

Data analytics approach provides the ability to evaluate the impact of many variables affecting the reliability and yield in the semiconductor manufacturing process. Hands-on sessions with data analysis models/tools help participants to improve operational tasks and increase work productivity.

Who Should Attend

Engineers/Professionals from Semiconductor Industries
Graduates/Post-graduates/Poly graduates with Electrical/Electronics background
Educators teaching VLSI and semiconductor courses in Electrical/Electronics Engineering
Administrative staff and Marketing staff working in the Semiconductor Industry

Prerequisites

Basic knowledge of programming
Electronics/Semiconductor knowledge is beneficial

Programme Outline

Learning Objectives

Equip participants with knowledge of applications of data analysis in semiconductor industry applications
Learn to apply the data analysis models/tools for yield and reliability study and its optimisation
Provide hands-on sessions with the data analysis tools
Apply the skills and knowledge to develop relevant tools required for industrial data

Day 1

Introduction to data science and analytics
Relevance of data analytics in semiconductor industry applications
Yield analysis semiconductor manufacturing process
Data modelling/analysis tools for yield optimisation
Hands-on session in data visualisation and analysis

Day 2

Reliability and failure analysis of semiconductor devices and IC systems
Statistics and models related to reliability and failure analysis
Data modelling/analysis tools for reliability study
Hands-on session to analyse the impact of different variables

Assessment

Assignment
Activity session/project work
Presentation

Course Fees and Funding

Full course fee inclusive of prevailing GST	You pay S$2,180.00
SkillsFuture Course Fee subsidy (70%) For Singapore Citizens < 40 years old For Permanent Residents	You pay S$654.00
Mid-Career Enhanced Subsidy (90%) For Singapore Citizens ≥ 40 years old	You pay S$254.00
Enhanced Training Support for SMEs (90%) For SME - Sponsored employees	You pay S$254.00

The above module fee payable is inclusive of prevailing GST of 9%.

Instructors

Shubhakar Kalya
Lecturer, SMT
SUTD

Currently working as a Lecturer at Singapore University of Technology and Design, Shubhakar obtained his Master’s degree in Microelectronics from Indian Institute of Science (IISc), Bangalore, India in 2007 and PhD degree from Nanyang Technological University (NTU), Singapore in 2012/13.

During his doctoral studies at NTU, he worked on Nanoscale characterisation of High-κ gate dielectrics for reliability and failure analysis. He has also worked as a researcher at Institute of Materials and Research Engineering (IMRE), Singapore, from July 2009 to December 2011, where he was involved in research related to characterisation of High-κ gate dielectrics using scanning tunneling microscopy and atomic force microscopy. His research interests are in nanoscale characterisation and analysis of High-κ gate dielectrics for logic and memory devices, and failure analysis of nanoscale electronic devices. He was a Visiting Scientist at Massachusetts Institute of Technology (MIT), Cambridge, USA in Electrical Engineering and Computer Science (EECS) Department during January-June 2017.

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Nagarajan Raghavan
Associate Professor, EPD, Co-Director, NEED Programme
SUTD

Nagarajan is a tenured Associate Professor at the Singapore University of Technology and Design (SUTD) in the Engineering Product Development (EPD) pillar. He is also the Co-Director of the Nano-Electronic Engineering and Design (NEED) double master’s degree programme. He has been a faculty at SUTD since 2015. Prior to that, he was a postdoctoral fellow at the Massachusetts Institute of Technology (MIT) in Cambridge and at IMEC in Belgium, in joint association with the Katholieke Universiteit Leuven (KUL). He obtained his PhD (Microelectronics, 2012) at the Division of Microelectronics, Nanyang Technological University (NTU), Singapore.

His work focuses on reliability modelling of nanoelectronic devices (especially logic and non-volatile memory device technologies), prognostics and health management for batteries and LEDs, design for reliability, physics of failure, AI-enabled optimisation of electromechanical properties of polymer nanocomposites and AI-enabled design for additive manufacturing. He is the recipient of the SUTD Outstanding Researcher Award for 2022, IEEE EDS Early Career Award for 2016, Asia-Pacific recipient for the IEEE EDS PhD Student Fellowship in 2011 and the IEEE Reliability Society Graduate Scholarship Award in 2008. To-date, he has authored / co-authored more than 270 international peer-reviewed publications with 4300+ citations and a h-index of 31 and five invited book chapters as well. He served as the General Chair for IEEE IPFA 2021 at Singapore and has consistently served on the review committee for various IEEE journals and conferences including IRPS, IIRW, IPFA and ESREF. He is an Associate Editor of the IEEE Access and Microelectronic Engineering journals and sits in the Editorial Advisory Board for APL Machine Learning. He is currently a Member of IEEE (2005-present) and was an invited member of the IEEE GOLD committee (2012-2014).

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Policies and Financing Options

SSG Funding Terms and Conditions

Use of Personal Details

In consideration of the subsidy provided by SkillsFuture Singapore Agency (“SSG”) through the SUTD Academy for the Course,

I consent to:

The collection, use and disclosure to relevant third parties of my personal data by the SUTD Academy including but not limited to personal particulars, attendance records, assessment/performance records, for the following purposes:

Reporting of national statistics and conducting of holistic continuing education training research and analysis;
Facilitate the conduct of the relevant surveys and audits in relation to the Course;
General administration of the Course including but not limited to processing of the subsidy provided by SSG;
Publicity and marketing of the Course or other Courses to be provided by SSG or SUTD Academy; and
SSG or its Appointed Auditors or Nominated Representatives to directly contact Course Participant to obtain information deemed necessary for the purposes of conducting effectiveness survey or audits in relation to the Course.

I agree to:

Attend and complete all lectures, class exercises, workshops and assessments;
Complete the Course feedback at the end of the Course;
Complete the post Course survey sent about 3 to 6 months after class attendance; and
Sign up for a personal email account.

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Methods of Payment

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Cancellation & Refund Policy

If a written notification is sent to sutd_academy@sutd.edu.sg within 24 hours after course registration deadline there will be no cancellation charges. A full refund will be made.
No refund is provided if written notification is more than 24 hours after course registration deadline. SUTD Academy reserves the rights to collect the full fee amount from the participant.

Replacement Policy

Companies may replace participants who have signed up for the course by giving a 3-working day notice before the course commencement date to sutd_academy@sutd.edu.sg. Terms and conditions apply.

Registration Policy

Course may be cancelled due to insufficient participants. SUTD Academy will not be responsible or liable in any way for any claims, damages, losses, expenses, costs or liabilities whatsoever (including, without limitation, any direct or indirect damages for loss of profits, business interruption or loss of information) resulting or arising directly or indirectly from any course cancellation.
Course enrolment is based on a first-come, first-served basis.
SUTD Academy reserves the right to change or cancel any course or instructor due to unforeseen circumstances.

Types of Funding

Funding under Mid-Career Enhanced Subsidy ("MCES")

MCES is an enhanced Subsidy to encourage mid-career individuals to upskill and reskill, thereby helping them to remain competitive and resilient in the job market. With this, all Singaporeans aged 40 and above will receive higher subsidies of up to 90% course fee subsidy for SSG-funded certifiable courses.
Individuals/employers are not required to submit an application for the MCES. Those pursuing SSG-funded programmes will be charged the appropriate subsidised fees by SUTD Academy if they are eligible MCES. Individuals/employers will only need to pay the nett fee (full course fee after SSG's grant).

For more info, please visit SkillsFuture website at https://www.skillsfuture.gov.sg/enhancedsubsidy

Funding under Enhanced Training Support for SMEs ("ETSS")

ETSS is an enhanced funding to enable SMEs to send their employees for training.
SMEs will enjoy subsidies of up to 90% of the course fees when they sponsor their employees for SSG-funded certifiable courses.
In addition to higher course fee funding, SMEs can also claim absentee payroll funding of 80% of basic hourly salary at a higher cap of $7.50 per hour. SMEs may apply for the absentee payroll via the SkillsConnect system.
To qualify, SMEs must meet all of the following criteria:
- Organisation must be registered or incorporated in Singapore
- Employment size of not more than 200 or with annual sales turnover of not more than $100 million
- Trainees must be hired in accordance with the Employment Act and fully sponsored by their employers for the course
- Trainees must be Singapore Citizens or Singapore Permanent Residents

For more info, please visit SSG website at https://www.ssg.gov.sg/programmes-and-initiatives/funding/enhanced-training-support-for-smes1.html

Funding under Union Training Assistance Programme ("UTAP")

UTAP is a training benefit for NTUC members to defray their cost of training. This benefit is to encourage more union members to go for skills upgrading.

NTUC members enjoy 50% unfunded course fee support for up to $250 each year when you sign up for courses supported under UTAP (Union Training Assistance Programme).

For more info, please visit https://e2i.com.sg/individuals/ntuc-education-and-training-fund/.

Funding under Post-Secondary Education Account ("PSEA")

The Post-Secondary Education Account (PSEA) is part of the Post-Secondary Education Scheme to help pay for the post-secondary education of Singaporeans.

This is part of the Government’s efforts to encourage every Singaporean to complete their post-secondary education. It also underscores the Government’s commitment to support families in investing in the future education of their children and to prepare them for the economy of the future. PSEA is not a bank account.

It is administered by the Ministry of Education (MOE) and is opened automatically for all eligible Singaporeans.

Account holders can use their PSEA funds to pay for their own or their siblings’ approved fees and charges for approved programs conducted by approved institutions.

However, you will have to check your eligibility and balance by contacting MOE first.

Contact MOE at (65) 6260 0777

E-mail to MOE at contact@moe.edu.sg

Click here for MOE website.

Data Analytics: Semiconductor Industry