Data Science and Industrial AI for Maintenance & Reliability Optimization
- Real Time Online Delivery – Live Training Sessions
- Virtual Attendance for 4 Days Training
- Guided Learning Hours – 16 (4 Hrs x 4 Days)
- Comprehensive Learning Kit
Course Overview
This 4 Day online course dives into the cutting-edge application of data science and AI to optimize Maintenance & Reliability processes. Designed for professionals in high-value asset- intensive sectors, it explores diagnostics, prognostics, predictive maintenance, and advanced analytics.
The total 16hrs sessions will have key topics which will include the integration of digital twins, hybrid models, and context-aware systems, as well as managing black swan events and leveraging prescriptive analytics for proactive decision-making. Case Studies and Real-World examples will be discussed too during this interactive and immersive training.
Trainer’s Profile
Our Expert is a Full Professor in the Division of Operation and Maintenance Engineering at Luleå University of Technology (LTU), where he significantly contributes to the fields of maintenance, reliability, and industrial technologies. Additionally, he serves as the Research & Technology Director at Sisteplant (Spain), specializing in predictive maintenance solutions and condition monitoring.
Our Trainer has played a crucial role in coordinating numerous European projects, emphasizing cyber-physical systems, Industry 4.0, IoT, and Industrial AI and Big Data. His collaborative efforts with the Swedish industry and national agencies, including Vinnova, have advanced maintenance technologies and practices. These projects often involve multi-disciplinary teams and international partners, reflecting Dr. Galar’s ability to lead complex research initiatives.
Key Takeaways
- Recognize the importance of diagnostics and prognostics in M & R.
- Apply data science, machine learning, and AI techniques to predictive maintenance.
- Understand black swan events and strategies to mitigate them.
- Develop skills in hybrid modelling, digital twins, and context-driven diagnostics.
- Implement prescriptive analytics to enhance decision-making in M & R.
Who Should Attend
Job Titles:
- Maintenance Managers
- Reliability Engineers
- Data Scientists
- MRO Specialists
- AI and ML Engineers
- Asset Management Professionals
Job Industries:
- Oil & Gas
- Manufacturing
- Transportation
- Energy
- and sectors focused on Asset Reliability, Maintenance & Reliability and MRO optimization.
For participation details contact
Mithun Siddartha
+1 780 851 7197 (Canada)