Topics and Abstracts: Product & System Level Testing Forum (Chairperson)

Transcription

1 (Chairperson) Session Chair Dr. Jeffrey LAM GLOBALFOUNDRIES Singapore Pte Ltd, Singapore Vice President, Product, Test & Failure Analysis (PTF) Dr. Jeffrey Lam received his B.S and M.S. in Chemical Engineering from UC Berkeley and UC Davis in 1979 and 1981 respectively. He obtained a second M.S in Electrical Engineering and Computer Science from the University of Santa Clara in In 2014, he received his PhD from the School of Physical and Mathematical Sciences, Nanyang Technological University. Dr Lam is currently Vice-President of Product, Test and Failure Analysis Division in GLOBALFOUNDRIES, Singapore. He possesses more than 35 years of experience in Process Module, Design Engineering, Product/Yield engineering, Failure Analysis and Test Development Engineering. He has 17 technical patents and more than 100 publications. He is also the chairman for SEMI SGP Product & Test Committee since 2009 and an adjunct associate professor at the National University of Singapore.

2 (Co-Chairperson) Session Co-Chair Mr. TAN Chun Sheng (CS TAN) STMicroelectronics Sdn Bhd, Malaysia Group Vice-President & General Manager CS Tan joined ST Microelectronics in March Prior to this, he has worked in many companies spreading across a multitude of industries such as National Semiconductor, Seagate, Soletron, Flextronics and ON Semiconductor. Including the last 13 years in General Management, he has more than 25 years of experience taking on different roles in said companies. CS currently manages ST's biggest assembly and test facility that specialises in Automotive semiconductors and Microcontrollers. Married with 3 daughters, CS Tan spends his free time with the family and likes to go for jogs and jungle treks. CS Tan has a Degree in Applied Physics and an MBA from USM. In 2017, he was appointed Adjunct Professor to the Faculty of Electrical and Electronics Engineering of Universiti Teknikal Malaysia.

3 (09:20-10:00hrs) Mr. Leslie KHOO & Mr. ONG Ban Seng STMicroelectronics Sdn Bhd, Malaysia Principal Engineer & Test Development Manager Big Data Application at Test & Robust Test Solution for Manufacturing Today, our KPI of defectivity detection has moved from ppm to ppb with key customers demanding 0 excursion. For years, we have expanded great effort to increase testing coverage. Over time, we found that these effort have not been repaid with significant reduction in customer returns. This has led us to take on a paradigm shift. We attempt to reduce customer returns employing predictive analytics. We mine the various test parameters (dimension) to gain insights if a particular lot is showing any maverick behavior and hold those lots from being ship to our customers. We do this by turning the multitude of data into useful insights. With the right data analytics algorithms and tools in place, we can uncover patterns and connections within the data that would not be obvious using the traditional statistical analysis. As one sift through millions of data points across hundreds or even thousands of dimensions for patterns, one encounters what is known as the curse of dimensionality. Data analysis gets harder as the dimensionality of the information increases. Machine learning is the science/ art of building algorithms that recognize patterns in data and improve as they learn. It employs algorithm that iteratively learn from data, allowing hidden insights to be found without explicitly being told where to look. We did a proof of concept looking in hindsight on 9 products where customer return was registered and try to understand how predictive analytics could have help us prevented the customer complaints in the first place. On the other hand, test contact & load board serve as a very important elements in testing, in recent years the focus on robust contactor in testing is becoming stronger, especially on automotive, medical and smart home applications. Durability and sustainability of contactor & error free load board has become a challenge to manufacturing for high power, high speed & system integration applications. Some concepts of predictive, preventable and robust solution to achieve durable life span of test contact and load board will be demonstrated. The implementation of this concept will require data analysis, predictive and preventive maintenance as well as adopting Industry 4.0 framework.

4 Leslie Khoo is a Product Engineer with STMicroelectronics. Leslie is currently collaborating with other professionals in leveraging big data analytics to predict maverick lots and reduce customer returns for the company. Leslie holds a degree with honours in Electrical and Electronic Engineering. He started his career as an Automation Engineer before moving on to Product Engineering in Leslie is directly involved in increasing efficiency and effectiveness of testing, lowering down test cost without compromising on product quality and bringing up the skills of engineers. Leslie is very much into coaching and believes in bringing out the best in others. A voracious reader, he enjoys biographies of the movers and shakers in the business world. In his free time, he loves spending time with his four-year-old daughter. Ban Seng is Test Development Manager in ST Microelectronics (Muar). He has 13 years of working experience in semiconductor IC testing. He started his career as a test engineer and currently he is heading a team of test development engineers drives for test package conversion/migration projects, test optimization, modernization projects and test cost & quality improvement projects. BS believes the most important asset is people, he coaches and develops junior engineers in term of technical knowhow and the right mindset to achieve a common goal. In his free time BS enjoy reading and jogging. To BS, success simply means Never Stop Learning.

5 (10:00-10:25hrs) Mr. Murad HUDDA Infineon Technologies Asia Pacific Pte Ltd, Singapore Principal, Test Technology Innovation Big Test Murad has more than 20 years of experiences in the roles of operational management and technical specialist in several semiconductor manufacturing and supply chain operations in US and Asia. In his current role as Principal for Test Technology & innovation at Infineon Technologies Asia Pacific, he is heavily involved in the topics of material handling automation, advanced equipment control and machine learning. On top of existing responsibilities, he also collaborates with business partners to shape the next generation of semiconductor handling solutions at Backend operation by leveraging the principles of Industry 4.0. Murad holds a Bachelor of Science in Physics, and he is trained on ISO principles and Lean Manufacturing.

6 (10:25-10:50hrs) Mr. TING Jia Wen & Mr. Adrain KWAN GLOBALFOUNDRIES Singapore Pte Ltd, Singapore & Advantest America Inc, USA Manager, Test Development Engineering & Business Development Manager 5G mmwave Future Testing Methodology at ATE level 5G riding on mmwave is the up-coming trend for broadband and mobile data networking by allocating more bandwidth to deliver faster, higher-quality video for multi-media content and service. Thus, there is an urgent need to enable the Testing methodology for mmwave application. This paper will talk about the challenge faced in testing environment for testing at such a high Frequency (30GHZ to 300GHZ). It will also cover the challenge and the feasibility of integrating this testing methodology into Production ATE Tester in the future. TING Jia Wen received his master degree in Electrical and Engineering in 2003 from I-Shou University, Taiwan. He is currently a Manager of Test Development Engineering in the Department of Product, Testing and Failure Analysis at GLOBALFOUNDRIES Singapore Pte Ltd, focusing on embedded Magnetoresistive Random Access Memory (MRAM), Radio Frequency (RF) and Power Management IC (PMIC) testing methodology development in leading technologies. In the last 15 years, he has built up a wide scope of semiconductor IC testing through hands-on experience in OSATs, Foundries and Design House. His expertise is mainly on wafer and package level product testing of System-on-Chip, RF and Memory devices, including coding development, probe card design, platform conversion and testing debug. In the Semiconductor Test industry for over 15 years, Adrian Kwan now leads the SOC Business Development Global RF/Wireless Market Segment in Advantest American Inc. He works with the sales team to drive business strategies and solutions to customers globally. With deep knowledge in the RF and Microwave technologies, he works closely with Product Marketing and R&D to define RF ATE solutions to address current and future technology evolution in this market space. He graduated with high honors from the University of Surrey, United Kingdom with major in RF/Microwave Communications and holds an MBA in Entrepreneurial Management.

7 (11:05-11:30hrs) Mr. SIEW Boon Ping, Alvin Advantest (Singapore) Pte Ltd, Singapore Staff Application Engineer Addressing the Robust Testing Needs of High-Power Analog ICs in Electric Vehicles Environment preservation and the control of emissions is a key concern for the Automotive Industry. Although we have seen vast advancements in Technology where Fuel consumption by typical transmission-driven car engines have improved over the years, we are nearing an inflexion point where alternative methods of transportation in the form of EV (Electrical Vehicles) are able to deliver equivalent performance but at much lower emissions. The challenge in EVs, however, lie in the High Voltage Battery requirements which are required to achieve ever-increasing demands in distance, and to power vast arrays of on-board safety, car-body and infotainment electronic equipment. The immediate challenge for the Test Industry is then, to address the robust requirement in such mission critical automotive product with high current, high voltage. This paper seeks to explain how ATE (Automated Test Equipment) can extend such HV coverage via Enhanced VI (Voltage & Current) and accuracy but at the same time lowering the COT (Cost of Test). Mr Siew is a Staff Application Engineer at Advantest (Singapore) with over 15 years of working experience in Semiconductor Testing. He graduated in 2002 from National University of Singapore, specializing in Electrical Engineering. He has extensive working experience on memory, digital and mixed signal testing. Currently he supports customers using the T2000 IPS test platform. He helps them in test program development and validation for automotive device testing and is also involved in yield improvement and test time reduction projects to help customers reduce their test costs.

8 (11:30-11:55hrs) Mr. Duncan LEE Intel Products (M) Sdn Bhd, Malaysia Manufacturing IT Principal Engineer Novel Ways of Using Data (Text and Images) from Intel s Assembly and Test Factory (ATM) Intel is constantly challenged with better quality product, faster process cycle time and units defect detection amidst an environment where our products are getting more complex. This scenario drove innovative approaches detecting early signals of issues to process, equipment issues and defects. Amongst the approach include, extracting data from various machines in the pipeline and using the information as warning signals to certain defects in the equipment or manufacturing process. Another effort leverages 2D images to detect defects and anomalies on units leveraging artificial intelligence. In my sharing, I will be sharing several examples of leveraging data to detect equipment defect and the usage of AI in detecting defects on images. Duncan Lee is a Principal Engineer in Intel Manufacturing IT with 25 years of IT experience. He currently focuses on manufacturing efficiency and quality through the usage industry 4.0 principles, integrating various AI/ Analytics/ IT / automation solution stack to improve the efficiency and productivity of Intel s Assembly and Test manufacturing. Recent successful projects include driving factory machine uptime through early defect signals detection and analysis to facilitate predictive preventive maintenance. The data collection is done via the machine controls and IoT devices. In addition, Duncan is also working in projects involving the usage of vision analysis and AI to identify potential problems or defects in units. Duncan s other accomplishments include converging chipset / cpu automation systems and surgically separating multi layered infrastructure and database of manufacturing execution systems and decision support systems in a life factory without impacting manufacturing, to facilitate individual factory operation autonomy. Duncan is also the committee member of Intel s Systems and Artificial Intelligence Patent approval Committee. Duncan Lee received his Masters of Science in Electrical Engineering from the Wichita State University in Kansas. Duncan joined Intel since 1994.

9 (13:35-14:00hrs) Mr. Gobinath Tamil VANAN National Instruments, Malaysia Field Marketing Engineer, Semiconductor Industry Advancing Semiconductor Industry with the Industrial Internet of Things Are you ready to implement the Industrial Internet of Things in the Semiconductor Industry? This technology revolution is more than just a vision or a trend. It is here today, and here to stay. IoT builds the central nervous system of a smarter world with devices that can sense and interact with us throughout our daily lives. The Industrial Internet of Things (IIoT) expands on this concept through advancement in connectivity and embeds more sensors, intelligence, analytics, and business insight into industrial systems, but this revolution does not come without challenges. Whether you call this trend the Industrial Internet of Things, Industry 4.0, or Cyber Physical Systems, there is an opportunity for each of us to add even more value to our companies and communities and to do some truly amazing things by building on a new wave of technology. Over 35,000 companies each year use NIs platform-based approach for applications that are making the Industrial IoT a reality; smart measurements at the edge, smart power generation, smart machines, smart tools and devices, smart test systems, and even smart factories. During this presentation, we will share some of our insights on key trends impacting the semiconductor industry due to the burst in these IoT technologies, and explore some innovative applications that are taking advantage of a platform-based approach and advancements in technologies such as processors and FPGAs, wireless connectivity, lowcost sensing, and software. As a Field Marketing Engineer in National Instruments specializing in Semiconductor Industry, Gobinath focuses on technology, marketing and content development activities related to semiconductor test across ASEAN, Australia & New Zealand. Working very closely with the Product Marketing Group, NI engineers, as well as customers throughout ASEAN and ANZ, Gobinath makes sure that all relevant customer needs in the industry are brought out well and early to enable not just the customers to be successful, but also to solve the grand cost challenges of the Semiconductor testing companies. He regularly works with customers and partners, developing content to enable technical consultants, and has presented at a variety of industry events including the NIDays Graphical System Design Conferences in Malaysia, Singapore, Thailand, Vietnam, Philippines and Australia, as well as the Semiconductor Industry VIP Roundtables. Gobinath graduated from Swinburne University of Technology with a Degree in Electrical and Electronics Engineering.

10 (14:00-14:25hrs) Keysight