Hybrid Conferencee

International Conference on Data Analytics Applications in Industrial Engineering (ICDAAIE - 26)

6th - 7th July 2026 | Oshawa, Canada
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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 Oshawa. 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 Oshawa 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 Oshawa conference. Build collaborations and gain insights from leading experts."
Keynote Speaker Sessions:
"Don’t miss our Keynote Sessions in Oshawa, 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 Oshawa."
SDG-Inspired Conference Focus:
"Our conference will highlight research that addresses global sustainability, inclusive education, and solutions for environmental challenges."

Call for Paper

The ICDAAIE 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 Industrial Engineering, 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 analytics applications in industrial engineering
02
Big data technologies in industry
03
Predictive analytics for operational efficiency
04
Data-driven decision making in engineering
05
Case studies on data analytics success
06
Role of machine learning in analytics
07
Data visualization techniques for engineers
08
Integrating analytics into production processes
09
Challenges in data analytics implementation
10
Future trends in data analytics
11
Data governance and management practices
12
Impact of analytics on supply chains
13
Collaborative analytics approaches
14
Real-time data analytics applications
15
Ethical considerations in data analytics
16
Training for data analytics professionals
17
Data analytics in quality control
18
Analytics for maintenance management
19
Impact of IoT on data analytics
20
Innovations in data analytics tools