关于新加坡南洋理工大学郑湃博士学术报告会的通知

时间:2019-04-28浏览:179设置

主题:IT-driven design innovation of smart product-service systems

报告人:Dr. Pai Zheng, Research Fellow in the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore

时间:2019430日,下午1:30

地点:玉泉校区,工业工程研究所三楼会议室(小白楼三楼)

主持:彭涛

Abstract

 With the prevailing introduction and implementation of the third-wave of IT innovation and the fourth Industrial Revolution, personalization, smart-connectedness, servitization and sustainability become the key factors to enable product innovation. Meanwhile, data-driven design, context-awareness and value co-creation are the core for design innovation success. This report embraces the state-of-the-art academic works, together with the speaker’s own understanding and research output, to elaborate the IT-driven design innovation of smart product-service systems in the following five aspects: 1) Recap of product design methodologies, consisting of three mainstreams of design process, viz. descriptive design, prescriptive design and computer-aided design. It is pointed out that in the smart, connected environment, data-driven design with IT support act as the major tendency. 2) Brief introduction of Smart, Connected Open Architecture Product (SCOAP). Product can be categorized into different domains based on three evaluation criteria, i.e. smartness, connectedness, and openness. SCOAP as a novel paradigm is further defined with its lifecycle personalization consideration. 3) Proposed a hybrid crowdsensing mechanism for smart product-service system (Smart PSS) innovation. It adopts the prevailing mobile crowdsensing paradigm by leveraging large-scale mobile devices and empowers users to contribute their generated/sensed data. Meanwhile, it is combined with physical sensors with static sensing nodes in the industrial environment for value co-creation purposes. 4) Data-driven platform-based methodologies to support design innovation. By exploiting graph embedding techniques and IoT platform, a systematic process to handle heterogenous data sources, various information fusion, implicit knowledge extraction, and eventual intelligent decision making should be established. 5) Application scenarios of Smart PSS. Lastly, the speaker provides some illustrative examples of the wide adoption/adaption of Smart PSS concepts in today’s smart manufacturing environment.

Biography

Dr. Pai Zheng is currently a Research Fellow in the Delta-NTU Corporate Laboratory for Cyber-Physical Systems, in the School of Electrical and Electronic Engineering, at Nanyang Technological University (NTU). He received his dual B.S. degrees in engineering from Huazhong University of Science and Technology, Wuhan, China, in 2010, the M.S. degree in mechanical engineering from Beihang University, Beijing, China, in 2013, and the Ph.D. degree in mechanical engineering at the University of Auckland, Auckland, New Zealand, in 2017. His research interest includes smart product-service systems, data-driven product design, and human-centric value co-creation. He is a member of IEEE, CMES, and ASME, and serves as the Guest Editor for the journal of Advanced Engineering Informatics, and referee for several high impact international journals in the manufacturing/industrial engineering field.


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