Keynote Speaker I
范治民 博士 Dr. Vincent Chih-Min Fan
Chief Data Scientist and BU Head, Big Data Solution, Foxconn - D Group
Title: Enable a Smart Factory: from Big Data to Human-Machine Augmented Intelligence
This talk will share our experience and vision to realize a smart factory.
With reference to Industry 4.0 and Made in China 2025, a Big-Data-driven application framework is firstly proposed, which consists of three layers: (Customer) Experience Co-creation, (Management) Digital Transformation, and (Shop Floor) Autonomous Control.
To turn any Big Data project into a success, our best practice with the 1C-2D-3E strategy is then introduced, where 1C refers to Case-based Value Proposition, 2D includes both Domain and Data Understanding, 3E covers the triple of End-to-End, Evolution, and Ecosystem.
Most Big Data projects are purely realized with various Machine Learning tools without Human Intelligence and Innovations. To bridge the gap between Big Data and real practices, an Enterprise Cognitive System (ECS) is in development to further conduct Human-Machine Augmented Intelligence. The ECS consists of five modules: Automated Speech Recognition, Spoken Language Understanding, Dialogue Management, Output Management, and Domain Ontology.
Finally, several examples of Smart Phone Diagnosis will be introduced to demonstrate the Big-Data-driven application framework, 1C-2D-3E strategy, and ECS. Some unsolved problems and open issues will also be addressed to seek academic collaborations.
Business Analytic with Big Data Evolution.pdf
Keynote Speaker II
Dr. Raimo P. Hämäläinen
Systems Analysis Laboratory
Aalto University, Finland
Title: On the Importance of Behavioural Operations Research
In this talk I will introduce the ideas and motivation for Behavioral Operational Research (BOR), a new emerging research area defined as the study of behavioral aspects related to the use of operational research (OR) methods in modeling, problem solving and decision support. In operational research the goal is to help people in problem solving but somehow we seem to have omitted the individuals, the problem owners and the OR experts, who are engaged in the process, from the picture. There is a long tradition of discussing best practices in OR but it is surprising to note that behavioral research on the process itself and on the role of the analyst and problem owner has been almost completely ignored. Descriptions of case studies are not enough. We also need controlled comparative studies and experiments. The OR supported problem solving process creates a system in which the OR expert plays an active role . So far we have ignored the fact that the modeler is also subject to the risk of cognitive biases which can have an effect on the problem solving process. Paying more attention to the analysis of the behavioral human factors related to the use of modeling in problem solving it is possible to integrate the insights of different approaches to improve the OR-practice of model-based problem solving. There is already a rapidly growing community of researchers involved in this field with the BOR website as a collaboration plattform: http://bor.aalto.fi/ .
On the Importance of Behavioural Operations Research.pdf