Hybrid Conferencee

International Conference on Engineering Data Mining for Fault Detection (ICEDMFD - 26)

26th - 27th June 2026 | Taipei City, Taiwan
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Conference Brochure
Sample Full Paper
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Conference Notifications:

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Call for Papers Extended:
"The deadline for full paper submissions has been extended for the Research Plus International Conference in Taipei City. Submit your research by today to participate in one of the top conferences."
Certificate of Presentation:
"Present your research and receive a Certificate of Presentation to recognise your valuable contribution to the conference."
Abstract Submissions Open:
"Abstract submissions for the Taipei City event are now open! Don’t miss the chance to present your research. Submit now."
Networking with Global Experts:
"Engage with researchers and professionals from around the world at the Taipei City conference. Build collaborations and gain insights from leading experts."
Keynote Speaker Sessions:
"Don’t miss our Keynote Sessions in Taipei City, featuring global leaders and innovators sharing their knowledge."
Best Paper & Best Paper Presentation Award:
"Submit your paper and stand a chance to win the Best Paper Presentation Award. The winner will be recognized at the conference in Taipei City."
SDG-Inspired Conference Focus:
"Our conference will highlight research that addresses global sustainability, inclusive education, and solutions for environmental challenges."

Call for Paper

The ICEDMFD aims to explore emerging trends and future directions in research and innovation. It provides a collaborative platform for researchers and professionals to share ideas that shape the future of their respective domains.

The conference highlights advancements in Data Mining, encouraging innovative, solution-oriented research that addresses global challenges and technological evolution.

Authors are invited to submit papers addressing, but not limited to, the following areas:

01
Data mining for fault detection in engineering
02
Predictive analytics for fault diagnosis
03
Data mining techniques for system reliability
04
Machine learning for fault prediction
05
Data mining for anomaly detection in systems
06
Data-driven maintenance strategies in engineering
07
Data mining for safety improvements in systems
08
Real-time fault detection using data mining
09
Data mining for operational efficiency
10
Data mining for risk assessment in engineering
11
Data mining for equipment performance analysis
12
Data mining for process optimization in maintenance
13
Data mining for root cause analysis
14
Data mining for predictive maintenance scheduling
15
Data mining for quality control in fault detection
16
Future trends in fault detection technologies
17
Data mining for system diagnostics
18
Data mining for performance monitoring
19
Data mining for regulatory compliance in fault detection
20
Case studies of successful fault detection