SIMTech is organising a hands-on workshop on correlation modelling in data mining for intelligent condition monitoring with emphasis on statistical correlation methods and neural network learning techniques. The objective of the workshop is to introduce the necessary skills in analysing data for prediction of machinery health condition and in-situ product quality monitoring.
In this workshop, participants will learn how to establish correlation models for machine/component health condition analysis and remaining useful life prediction to ensure high product quality. This workshop includes an introduction of statistical regression modeling and basics of neural networks with assessment on correlation modeling. Practical hands-on sessions on the MatLab software will be conducted to guide participants build up correlation models using multiple regression method and back-propagation neural networks. The sessions will enable participants to understand the advanced techniques in intelligent condition monitoring.
There will also be a case study to illustrate the use of Hybrid Wavelet Neural Networks (HWNN) for tool condition monitoring and tool life prediction with a CNC high speed milling machine.
9.00am – 10.30am : Introduction of regression modelling (by Ms Zhou Junhong)
· Why Correlation Modelling
· Statistical Regression Modelling (SRM)
· Correlation Modelling with SRM
· Class Assignment
10.30am - 10.45am : Tea Break
10.45am - 12.30pm : Introduction of neural networks (by Dr Li Xiang)
· Neural Network Learning Algorithms
· Correlation Modelling with BP Neural Networks
· Class Assignment
12.30pm - 1.30pm : Lunch
1.30pm - 3.15pm : Hands–on of MatLab Software (by Ms Zhou Junhong)
· Build up a multiple regression model using MatLab
· Build up a BP neural network using MatLab
3.15pm - 3.30pm : Tea Break
3.30pm - 5.00pm : Hands–on Case Study using SIMTech Intelligent Predictive Monitoring System (IPMS) Software (by Mr Zhao Yi Zhi)
Wavelet Neural Nets for Tool Life Prediction
• Introduction and Motivation
• Hybrid Wavelet Neural Net (HWNN)
• Network Optimisation
• Experimental Results and Discussion
• Industrial Applicability
·Hands-on section to run HWNN
About Course Leaders
Dr Li Xiang received her BEng and MEng from the North-Eastern University, ShenYang (PRC) and PhD from Nanyang Technological University, Singapore. She taught at the North-Eastern University in 1982-87. In 1987-1989, and did research work as Visiting Research Fellow at Tohoku University, Japan. She is currently a Research Scientist at Singapore Institute of Manufacturing Technology. Dr Li has more than 15 years of experience in research on artificial intelligence, data mining and statistical analysis, such as neural networks, fuzzy logic systems, expert systems and multiple regression models. She has led and was involved in many industrial projects, including: Web-based intelligent forecasting system; Auto-mould designs using intelligent optimisation & simulation; Data warehousing; Rule-based AEC object library; Customer demand discovery in new product design; Intelligent predictive monitoring system for machining process, defects and failure detection in semiconductor. Dr Li’s research interests include data and text mining, decision support systems, intelligent forecasting, knowledge-based systems and real time equipment/process prognostic monitoring. She is a member of the Decision Sciences Institute, USA and member of IEEE.
Ms Zhou Junhong joined SIMTech in 1996. Ms Zhou obtained her Master of Engineering from the National University of Singapore for her research into process adaptive control and monitoring. Since joining SIMTech, Ms Zhou has been actively involved with a number of research and industry projects in the areas of process monitoring & control, sensing and advanced signal processing. Ms Zhou’s experience includes the SCADA system, sensing & measurement for machine tooling condition, and Intelligent Systems to maintain serviceability of manufacturing equipment.
Mr Zhao Yi Zhi a Senior Research Engineer of SIMTech. He has led and taken part in many in-house and industry projects that involved in manufacturing execution and control and equipment prognosis and failure prediction and prevention. He started his research work in the area of artificial intelligence and neural networks for various applications 20 years ago, and published a number of research papers in this area. He participated in a few of award-winning large scale industry projects in recent 10 years. His current research interests include knowledge discovery and neural networks for equipment diagnostics and prognostics; rule-based active technologies for event management; dynamic reconfiguration for complex systems modelling; intelligent & automated control for air-cargo handling system; wireless sensor networks and RFID for network-centric monitoring and control systems.
Who Should Attend
Senior Management, Production / Process Managers, Engineers & IT support staff from the Semiconductor, Electronics, Precision Engineering, Automation, Aerospace and Logistic industries, etc.
Registration Fee : S$200 (including 7% GST) per participant
Please register online.
Technical :Dr Li Xiang at Tel: 6793 8264
Email: email@example.com )
General : Ms Samantha Sukiyama Chan at Tel: 6793 8423