Hybrid Conferencee

International Conference on Industrial Engineering and Data Mining Applications (ICIEDMA - 26)

7th - 8th July 2026 | Vienna, Austria
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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 Vienna. 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 Vienna 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 Vienna conference. Build collaborations and gain insights from leading experts."
Keynote Speaker Sessions:
"Don’t miss our Keynote Sessions in Vienna, 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 Vienna."
SDG-Inspired Conference Focus:
"Our conference will highlight research that addresses global sustainability, inclusive education, and solutions for environmental challenges."

Call for Paper

The ICIEDMA 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
Industrial applications of data mining techniques
02
Data mining for process optimization in industry
03
Machine learning in industrial engineering
04
Data mining for supply chain optimization
05
Data mining for quality assurance in manufacturing
06
Data mining for production efficiency
07
Data mining for safety improvements in industry
08
Data mining for resource management in industry
09
Data mining for customer behavior analysis
10
Data mining for predictive maintenance in industry
11
Data mining for operational excellence in manufacturing
12
Data mining for innovation in industrial processes
13
Data mining for environmental sustainability in industry
14
Data mining for workforce optimization
15
Data mining for regulatory compliance in industry
16
Future trends in industrial data mining
17
Data mining for cost reduction in manufacturing
18
Data mining for performance monitoring in industry
19
Data mining for risk management in industrial projects
20
Case studies of data mining in industrial applications