Research Output per year
Fingerprint Dive into the research topics where Soundar Rajan Tirupatikumara is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
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Planning
Engineering & Materials Science
Neural networks
Engineering & Materials Science
Multi agent systems
Engineering & Materials Science
Supply chains
Engineering & Materials Science
Wear of materials
Engineering & Materials Science
Sensors
Engineering & Materials Science
Product design
Engineering & Materials Science
Logistics
Engineering & Materials Science
Network
Recent external collaboration on country level. Dive into details by clicking on the dots.
Research Output 1985 2019
Machine learning and AI for long-term fault prognosis in complex manufacturing systems
Bukkapatnam, S. T. S., Afrin, K., Dave, D. & Tirupatikumara, S. R., Jan 1 2019, In : CIRP Annals. 68, 1, p. 459-462 4 p.Research output: Contribution to journal › Article
Learning systems
Electric fuses
Information systems
Automation
Sensors
SuperOrder: Provider order recommendation system for outpatient clinics
Sung, Y. S., Dravenstott, R. W., Darer, J. D., Devapriya, P. D. & Tirupatikumara, S. R., Jan 1 2019, In : Health Informatics Journal.Research output: Contribution to journal › Article
Rural Health
Electronic Health Records
Health Facilities
Ambulatory Care Facilities
Appointments and Schedules
3
Citations
(Scopus)
The internet of things for smart manufacturing: A review
Yang, H., Tirupatikumara, S. R., Bukkapatnam, S. T. S. & Tsung, F., Jan 1 2019, In : IISE Transactions.Research output: Contribution to journal › Article
Internet
Cloud computing
Industry
Internet of things
Innovation
1
Citation
(Scopus)
An Unsupervised Machine Learning Approach to Assessing Designer Performance during Physical Prototyping
Dering, M. L., Tucker, C. S. & Tirupatikumara, S. R., Mar 1 2018, In : Journal of Computing and Information Science in Engineering. 18, 1, 011002.Research output: Contribution to journal › Article
Learning systems
Clustering algorithms
Learning algorithms
12
Citations
(Scopus)
Cloud-Based Parallel Machine Learning for Tool Wear Prediction
Wu, D., Jennings, C., Terpenny, J., Kumara, S. & Gao, R. X., Jan 1 2018, In : Journal of Manufacturing Science and Engineering, Transactions of the ASME. 140, 4, 041005.Research output: Contribution to journal › Article
Learning systems
Wear of materials
Health
Cloud computing
Condition monitoring