Jingshan Li

Prof. Dr. Jingshan Li


Research Focus & Metrics

Academic Career Length

35Years (1992-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
15 February 2021 in IISE Transactions on Healthcare Systems Engineering
Verified
Journal Article
Open access
JLJingshan Li
Jingshan Li
PCPascale Carayon
Pascale Carayon
Industry 4.0 has transformed manufacturing industry into a new paradigm. In a manner similar to manufacturing, health care delivery is at the dawn of a foundational change into the new era of smart and connected health care, referred to as Health Care 4.0. In this paper, we discuss the historical evolution of Health Care 1.0 to 4.0, describe the characteristics of smart and connected care in Health Care 4.0, identify multiple research challenges and opportunities of Health Care 4.0 in terms of data, model, dynamics, and integration, and outline the implications of people, process, system and health outcomes. Finally, conclusions and recommendations are presented in the areas of (1) involvement of multiple disciplines and perspectives, (2) development of technologies and methodologies with combination of quantitative and qualitative approaches, (3) closed-loop integration of sociotechnical system, and (4) design of person-centered system with specific attention to human needs and health equity.

1 January 2021 in Journal of Biomedical Informatics
Verified
Journal Article
Closed access
KGKaidi Gong
Kaidi Gong
HLHyo Kyung Lee
Hyo Kyung Lee
KYKaiye Yu
Kaiye Yu
XXXiaolei Xie
Xiaolei Xie
JLJingshan Li
Jingshan Li

28 May 2021 in IEEE Robotics and Automation Letters
Verified
Journal Article
Open access
SLSujee Lee
Sujee Lee
LLLi Liu
Li Liu
RRRobert Radwin
Robert Radwin
JLJingshan Li
Jingshan Li
The rapid development of machine learning (ML) technology has introduced substantial impact on ergonomics research in manufacturing. Numerous studies and practices have been carried out to apply ML techniques to address manufacturing ergonomics issues, which has brought extensive opportunities as well as significant challenges. To incentivize future research in this area, this letter reviews the recent advances of ML applications in manufacturing ergonomics, and discusses future research opportunities and challenges from ML, ergonomics, and manufacturing systems perspectives.

30 November 2011 in Health Care Management Science
Verified
Journal Article
Closed access
PDF file
JWJunwen Wang
Junwen Wang
SQShichuan Quan
Shichuan Quan
JLJingshan Li
Jingshan Li
AHAmy M. Hollis
Amy M. Hollis

18 May 2017 in Health Care Management Science
Verified
Journal Article
Closed access
PDF file
XZXiang Zhong
Xiang Zhong
PHPeter Hoonakker
Peter Hoonakker
PBPhilip A. Bain
Philip A. Bain
AMAlbert J. Musa
Albert J. Musa
JLJingshan Li
Jingshan Li

10 February 2011 in International Journal of Production Research
Verified
Journal Article
Closed access
CGClaudia Arenas Guerrero
Claudia Arenas Guerrero
JWJunwen Wang
Junwen Wang
JLJingshan Li
Jingshan Li
JAJorge Arinez
Jorge Arinez
SBStephan Biller
Stephan Biller
GXGuoxian Xiao
Guoxian Xiao
Vehicle painting typically consumes the largest amount of energy in an automotive assembly plant. Effective reduction of energy usage in paint shops will lead to significant savings. Substantial effort has been devoted to reducing energy usage in paint shops through renovating the painting process and equipment. In this paper, we introduce a case study at an automotive paint shop to show that the energy consumption can be reduced significantly through production system design. Specifically, by selecting the appropriate repair capacity, the number of repainted jobs can be reduced, and less material and energy will be consumed. In addition, less atmospheric emissions would be generated during the painting process. Such a technique does not need to invent new chemicals, new painting processes or new control systems in painting booths and ovens. It provides an alternative way for energy and emission reduction to achieve energy-efficient and environmentally friendly manufacturing.