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SIMTech

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Dr Li Xiang is a Senior Scientist and Team Lead at the Singapore Institute of Manufacturing Technology, A*STAR. Dr Li has more than 20 years of experience in research on computational intelligence, data mining and statistical analysis, such as neural networks, fuzzy logic systems, expert systems and multiple regression models. Her research interests include big data analytics, data warehousing, data mining and machine learning, decision support systems, knowledge-based systems and energy efficiency analytics. She has led and was involved in many projects, such as density-grid hybrid clustering method for multivariate anomaly detection to achieve zero defective product with minimum false reject rate in Semiconductor test process, data stream clustering for online fault detection on work piece in

milling machining process, smart recipe predictive modelling and tuning for Nitride coating process quality control, fuzzy regression modelling for tool degradation detection in milling machining process, advanced techniques for handling imbalanced and unlabeled data for classification for Aerospace MRO, pogo pin anomaly detection in Semiconductor test process, Semiconductor production data warehousing. She is an IEEE member.

Mr Eugene Ghe is the Managing Director of Gnosis Analytics Pte Ltd. He has over 18 years of experience in IT/Operations and has held key positions in several local and global IT Companies. He is specialised in Big Data applications, consultancy and training. He has managed teams that handle several clients including local government agencies in digitisation, website creation and system automation. He is also a co-inventor in several patents (Mobile SMS and Internet Technology) that were filed in both US and Singapore. He has led some of the key big data consultancy projects in various verticals, including IoT project for monitoring parameters of wafer manufacturing as the processes generate high amount of data; energy management project for big data consultancy in building an end-

to-end big data platform; education project that provide consultancy in real-time/batch gathering of multiple external sources (websites and Social Media) and merging with internal data sources to produce real-time ranking visualization with analytics. When and WhereDates: 22 - 23 November 2016 (Tuesday & Wednesday)Venue: Singapore Institute of Manufacturing Technology 4 Fusionopolis Way, Kinesis, Level 6, Seminar Room 2 Singapore 138635

Course Fee• The full course fee is S$2,000 (excluding GST).• The nett course fee for Singaporeans and Permanent Residents is S$642.00, inclusive of

GST with 70% course fee subsidy from the SkillsFuture Singapore (SSG) Agency.

RegistrationPlease register online at KTO.SIMTech.a-star.edu.sg

Contact UsFor general enquiries, please contact: Mr Wong Ming Mao, Deputy Director at mmwong@SIMTech.a-star.edu.sg For technical information, please contact: Dr Li Xiang, Senior Scientist at xli@SIMTech.a-star.edu.sg

Trainers’ Profile

Master Class in Predictive Manufacturing & Services

22 - 23 November 2016

Big Data Analytics & Management in Manufacturing

Singapore Institute of Manufacturing Technology Knowledge Transfer Office

2 Fusionopolis Way Innovis #08-04 Singapore 138634 Tel: (65) 6590 3193 | Email: KTO-enquiry@SIMTech.a-star.edu.sg | Website: KTO.SIMTech.a-star.edu.sg

Scan the QR code to visit our website

Course IntroductionBig Data Analytics is becoming increasingly important as Singapore progresses towards high-value data-intensive manufacturing. The popularity of Big Data Analytics is also facilitated by the push towards Industry 4.0 and Industry Internet of Things (IIoT) in which data is more readily collected. Data-intensive industries such as semiconductor companies today, will face numerous challenges in handling multi-dimensional as well as huge volume of data.

Big Data Analytics can be used to enable these data-intensive industries improve productivity and product quality, and at the same time, reduce cost and time. It can be potentially used in various areas including product quality inconsistencies, equipment and material condition variations, root cause discoveries, process performance prediction and process parameters or recipe auto tuning, etc.

This unique Master Class will give a good overview on the infrastructure needed for Big Data Management. It will also make use of industry case studies to demonstrate how Big Data Analytics can help resolve key concerns such as yield, quality, consistency and reliability issues.

Course ObjectivesThis Master Class aims to provide a good understanding of the concept and challenges of Big Data Analytics and Big Data Management in manufacturing. The course covers the fundamentals of Big Data Analytics including machine learning and data mining techniques for different manufacturing applications. Big Data Management will be introduced to big data platforms, Hadoop ecosystem and distributions. Participants will learn techniques including statistical modelling and characterisation in semiconductor manufacturing process. Participants will get to experience the power and speed of big data platforms and different data mining methods.

Who Should AttendThis course is designed for Operation Directors and Managers, Production/Process Engineers, R&D Engineers and IT support staff working on processes, production, and quality improvement in manufacturing industries such as Electronics, Precision Engineering, Pharmaceutical, Biomedical, MedTech, Chemicals, General Manufacturing, Aerospace, Food Manufacturing, etc.

Why This Course• Specially designed to cater to local industry demand• Two intensive hands-on sessions • Learn about the latest big data analytics techniques and technologies• Uses case studies that highlights industrial applications• Trained by experts with industrial experience

Trainers’ Profile

To view the Programme Agenda, visit KTO.SIMTech.a-star.edu.sg

Professor Thomas Gulledge is the President of Enterprise Integration, Inc. and Enterprise Integration Pte Ltd (Singapore). He is also the co-director of Enterprise Consulting Alliance, a consulting organisation that operates in the USA, Asia-Pacific, and Australia. He is also the Professor Emeritus of Public Policy and Engineering at George Mason University and Director of the Policy Analysis Center within the School of Public Policy. Professor Gulledge’s competence areas are in Logistics, Extended Enterprise Integration, Product Lifecycle Management, Engineering Management, Logistics, and Supply Chain Integration & Management. He directed the Ph.D. Program in the School of Public Policy, and he was a co-founder of the MS programme in Enterprise Engineering & Policy, a joint

sponsored program by the School of Public Policy and the School of Information Technology and Engineering. Professor Gulledge has led many technology-related projects, most relating to information technology-enabled organisational transformation. He was Director of the corporate-sponsored International Electronic Commerce project (project Pathfinder) with the Oracle Corporation, which focused on B2B e-Commerce and the development of the first generation Oracle e-Hub, which evolved into the Customer Data Hub. He also developed the Enterprise Engineering & Policy Laboratory, sponsored by Microsoft, IDS Scheer, Oracle, ILOG, and SAP. He is also the Programme Manager for a series of on-going initiatives relating to supply chain integration and electronic commerce including initiatives in Europe and Asia. Some of these initiatives are large-scale, including a complex project that required working with Boeing Company to implement an eHub for Boeing suppliers in Asia. Professor Gulledge also conceptualised, launched, and managed the Fairfax Electronic Commerce Resource Center, which focused on implementing electronic commerce solutions.

Professor Gulledge’s research was supported by the Office of Naval Research, the Air Force Office of Scientific Research, Office of the Assistant Secretary of Defence (C3I), Defence Information Systems Agency, Office of the Director of Defence Information, National Science Foundation, Defence Advanced Research Projects Agency, and the US Navy.

Professor Gulledge was the President of the Military Applications Society and was also the Vice president of Institute for Operations Research and the Management Sciences. He is currently the Head of Intelligent Manufacturing Systems Network of Excellence Group on Supply Chain Integration & Management and the Vice Chairman for the Americas of the IFIP Working Group on Integrated Production Management. He is also a senior editor for International Journal of Management & Enterprise Development and an associate editor for others, including Electronic Government and for Industrial Management and Data Systems. Professor Gulledge was an associate editor for Management Science, Naval Research Logistics, and the International Journal of Production Economics.

Associate Professor Xin Li received his Ph.D. degree in Electrical and Computer Engineering from Carnegie Mellon University, Pittsburgh, PA in 2005. He is currently an Associate Professor in the Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA. Associate Professor Xin Li co-founded Xigmix Inc. in 2005, to commercialise his PhD research, and served as the Chief Technical Officer. Xigmix Inc. was acquired by Extreme DA in 2007. From 2009 to 2012, he was the Assistant Director for FCRP Focus Research Center for Circuit & System Solutions (C2S2), a national consortium working on next-generation integrated circuit design challenges. His research interests include integrated circuit, signal processing and data analytics.

Associate Professor Xin Li was an Associate Editor of IEEE TBME, IEEE TCAD, ACM TODAES, IEEE D&T, and JOLPE. He served on the Executive Committee of ACM SIGDA, IEEE TCCPS, and IEEE TCVLSI. He was the General Chair of ISVLSI, iNIS and FAC, and the Technical Program Chair of CAD/Graphics. He received the NSF CAREER Award in 2012, two IEEE Donald O. Pederson Best Paper Awards in 2013 and 2016, the DAC Best Paper Award in 2010, two ICCAD Best Paper Awards in 2004 and 2011, and the ISIC Best Paper Award in 2014. He also received six Best Paper Nominations from DAC, ICCAD and CICC.

Data Mining Software

Correlation Modeling & Process Parameter Tuning

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