Research Output per year
Fingerprint Fingerprint is based on mining the text of the experts' scientific documents to create an index of weighted terms, which defines the key subjects of each individual researcher.
- 1 Similar Profiles
Electric vehicles
Engineering & Materials Science
Energy storage
Engineering & Materials Science
Transient analysis
Engineering & Materials Science
Productivity
Engineering & Materials Science
Repair
Engineering & Materials Science
Inspection
Engineering & Materials Science
Degradation
Engineering & Materials Science
Markov processes
Engineering & Materials Science
Network
Recent external collaboration on country level. Dive into details by clicking on the dots.
Research Output 2009 2019
Integrated analysis of productivity and machine condition degradation: Performance evaluation and bottleneck identification
Kang, Y. & Ju, F., Jan 1 2019, (Accepted/In press) In : IISE Transactions.Research output: Contribution to journal › Article
Productivity
Degradation
Industrial plants
Agglomeration
Decision making
Transient analysis and real-time control of geometric serial lines with residence time constraints
Wang, F., Ju, F. & Kang, N., Jan 1 2019, (Accepted/In press) In : IISE Transactions.Research output: Contribution to journal › Article
Real time control
Transient analysis
Markov processes
Learning algorithms
Structural properties
2
Citations
(Scopus)
A study on performance evaluation and status-based decision for cyber-physical production systems
Wang, F., Ju, F. & Lu, Y., Jan 12 2018, 2017 13th IEEE Conference on Automation Science and Engineering, CASE 2017. IEEE Computer Society, Vol. 2017-August. p. 1000-1005 6 p.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Industrial plants
Real time control
Web services
Decision making
Control systems
Condition-based Real-time Production Control for Smart Manufacturing Systems
Wang, F., Lu, Y. & Ju, F., Dec 4 2018, 2018 IEEE 14th International Conference on Automation Science and Engineering, CASE 2018. IEEE Computer Society, Vol. 2018-August. p. 1052-1057 6 p. 8560389Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Production control
Degradation
Condition monitoring
Markov processes
Processing
Maintenance decision model for a two-machine production line with multistage degradation machines
Kang, Y. & Ju, F., Jan 1 2018, Manufacturing Equipment and Systems. American Society of Mechanical Engineers (ASME), Vol. 3.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Degradation
Experiments
Projects 2016 2020
- 2 Active
EAGER: CMMI: OE: Exploring Discrete Event Dynamics to model and control intelligent systems
6/1/18 → 5/31/20
Project: Research project
CRISP Type 2: Collaborative Research: Harnessing Interdependency for Resilience: Creating an "Energy Sponge" with Cloud Electric Vehicle Sharing
9/1/16 → 8/31/20
Project: Research project