Keynote Speakers

Previous Keynote Speakers


Prof. Shi Jianjun

Georgia Tech, USA


Dr. Jianjun Shi is the Carolyn J. Stewart Chair and Professor in H. Milton Stewart School of Industrial and Systems Engineering, with a joint appointment in the George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology. Professor Shi’s research is in the area of system informatics and control. He is the founding chairperson of the Quality, Statistics and Reliability Subdivision of INFORMS. He is currently serving as the Editor-in-Chief of IISE Transactions. Dr. Shi received various awards, including the IISE David F. Baker Distinguished Research Award (2016), the IISE Albert G. Holzman Distinguished Educator Award (2011), Forging Achievement Award (2007), and Monroe-Brown Foundation Research Excellence Award (2007). He is a Fellow of four professional societies, including INFORMS, IISE, ASME, and ISI. He is an Academician of the International Academy for Quality (IAQ), and a member of National Academy of Engineering (NAE).

Speech Title--Machine Learning Enabled Quality Improvement in Samrt Manufacturing Systems

Speech Abstract--In a smart manufacturing system, a large number of sensors are installed to monitor machine status, process variables, product quality, and the overall system performance. It is always a challenging problem of how to analyze those massive amount of data effectively for cost reduction and quality improvements in all manufacturing companies. This presentation will discuss research opportunities, challenges, and advancements in this important research area, especially how machine learning concepts and algorithms can be used to solve challenging quality improvement problems. Examples of ongoing research projects will be used to articulate the frontiers of this research area. All examples come from real data and problem in industrial production systems. This presentation will emphasize the motivations of these research undertakings: challenges to be overcome, new methods that were developed, validation/implementation undertook, as well as the potential impacts.


Prof. Dr. Yongsheng Ma
University of Alberta, Canada


Y.-S. Ma has been a full Professor of the Dept. of Mechanical Engineering since 2013 with the University of Alberta. Dr. Ma has also been a registered Professional Engineer with APEGA, Canada since 2009. Currently he teaches capstone design projects, engineering economics and manufacturing processes. His research areas include interdisciplinary heavy oil recovery production tooling engineering, feature-based product and process modeling, plastic molding simulation and mold design optimization, CAD/CAE integration, CADCAM, ERP informatics modeling, and product lifecycle management. Dr. Ma received his B.Eng. degree from Tsinghua University, Beijing in 1986, M.Sc. and Ph.D. degrees from UMIST, UK in 1990 and 1994 respectively. Before joining U of A, from 2000 to 2007, he had been an Associate Professor with Nanyang Technological University, Singapore; and from 2007 to 2013, with University of Alberta. He served as an associate editor of IEEE Transaction of Automation Science and Engineering from 2009 to 2013; and since 2012, has been an editor of Advanced Engineering Informatics. Dr. Ma won ASTech award sponsored by Alberta Science and Technology Leadership Foundation jointly with Drader Custom Manufacturing Ltd in 2012. He started his career as a Lecturer from Ngee Ann Polytechnic, Singapore in 1993, and then from 1996 to 2000, he was a Senior Research Fellow and Group Manager at Singapore Institute of Manufacturing Technology (SIMTech).

Speech Title--Feature-based cyber-physics modeling in complex energy production systems

Speech Abstract--Cyber-Physics System (CPS) has been recognized as the core concept in modern industrial trends, especially related to manufacturing sector. It has been the new discovery by the author that the similar CPS concept, feature-based CPS, can be applied to complex energy production systems such as SAGD process in oilsands development in Canada. For example, bitumen production involves efficient performance of the underground tooling which again depends on the semantics knowledge about and the effective control of the physical world phenomenon – SAGD process. Virtual simulation could be helpful to understand and control the phenomenon. This presentation try to address the feature-based CPS approach with some in depth research results and multi-disciplinary collaboration. For example, computational fluid dynamics (CFD) is a powerful tool to analyze the flow field and then improve design. However, the use of CFD still requires strong expertise and extensive training, which places a barrier for its broader application. Feature-based CAD/CAE integration improves the usability via two new types of engineering features, fluid physics feature and dynamic physics feature. They convey the simulation intent and enable dynamic CFD solver setup automation and robust simulation model generation. Further, the association between simulation intent and design intent which is conveyed by another newly defined fluid functional feature is suggested to achieve seamless integration, which keeps the consistency in the complex product development process. Consequently, an optimal design could be possibly achieved by optimization coupling with production operation, manufacturability and cost analysis. A case study of steam assisted gravity drainage (SAGD) outflow control device (OCD) is presented at last to show the prospective benefit of the method.


Prof. Songgang Qiu,
West Virginia University, USA

Dr. Songgang Qiu began his professional career as a senior principal engineer at a Research and Development company in 1997. He was quickly promoted to Vice President. In 2004, he led to create a R&D division to pursue government projects. He joined Temple University as a full professor in 2012. Currently, he is the full professor at West Virginia University. Over the last twenty years, he has served as principal Investigator for several dozes of government and industrial sponsored research projects. His current sponsored research projects are focused on power generation, energy conversion, solar energy, and energy efficiency.


Speech Title--Study of Oscillating Flow in an Engine Regenerator

Speech Abstract--Regenerator is the key component in a high efficiency Stirling engine. Currently, most regenerators are made of either the random fibers or woven screens. However, these regenerators have high flow losses, leading to low engine performance. To alleviate this problem, a foil regenerator was implemented. In this research, a oscillating flow test rig was designed and manufactured. The test rig was designed to generate the sinusoidal flow motion as in typical Stirling engines. Foil regenerators were tested under oscillating flow conditions. Dynamic pressure transducers were implemented to determine the pressure drops. Testing was conducted over a few hundred cycles and the measured pressures were ensemble-averaged to generate cyclic variation of pressures at the inlet and outlet of the regenerator. The friction coefficient was calculated based on Darcy-Weisbach equation. The validity and the accuracy of the measurement were verified by CFD analysis and other codes.