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Sho Okazaki
ResearcherPublications, citations & collaboration network
Sho Okazaki is a researcher indexed in ScholarIQ from OpenAlex & ORCID. ScholarIQ records 4 works, 6 citations, an h-index of 2 and an i10-index of 0.
4
Works
6
Citations
2
h-index
0
i10-index
IDs:OpenAlex
How has Sho Okazaki's publication output changed over time?
ScholarIQpublication output · 2023–2026
Output grew0% over the shown period — from 1 works in 2023 to 1 in 2026.
1
1
1
1
2023202420252026
What are the most-cited papers on Sho Okazaki?
ScholarIQmost cited works
A Framework to Support Failure Cause Identification in Manufacturing Systems through Generalization of Past FMEAs
Sho Okazaki, Shouhei Shirafuji, Toshinori Yasui, Jun Ota
20234 Citations
Description Method and Failure Ontology for Utilizing Maintenance Logs with FMEA in Failure Cause Inference of Manufacturing Systems
Takuma Fujiu, Toshinori Yasui, Sho Okazaki, Kohei Kaminishi, Jun Ota
20242 Citations
A spatio-temporal anomaly detection system to support understanding of abnormal phenomena in automated manufacturing lines
Sho Okazaki, Kohei Kaminishi, Yusheng Wang, Takuma Fujiu, Yuji Nakata, S. Hamamoto, Kenshin Yokose, Tatsunori Hara, Yasushi Umeda, Jun Ota
Computers in Industry. 20260 CitationsOPEN ACCESS
Fault Cause Identification across Manufacturing Lines through Ontology-Guided and Process-Aware FMEA Graph Learning with LLMs
Sho Okazaki, Kohei Kaminishi, Takuma Fujiu, Yusheng Wang, Manu Sasidharan, Jun Ota
arXiv (Cornell University). 20250 CitationsOPEN ACCESS
Related on ScholarIQ
The University of Tokyo
Institution
A Framework to Support Failure Cause Identification in Manufacturing Systems through Generalization of Past FMEAs
Paper
Description Method and Failure Ontology for Utilizing Maintenance Logs with FMEA in Failure Cause Inference of Manufacturing Systems
Paper
A spatio-temporal anomaly detection system to support understanding of abnormal phenomena in automated manufacturing lines
Paper
Fault Cause Identification across Manufacturing Lines through Ontology-Guided and Process-Aware FMEA Graph Learning with LLMs
Paper
Digital Transformation in Industry
Topic