Data Science and Industrial AI for Maintenance & Reliability Optimization
- Face to Face Training Delivery – Live Training Sessions
- In-Person Attendance for 2 Days Training
- Guided Learning Hours – 16 (8 Hrs x 2 Days)
- Comprehensive Learning Kit
- Pre-Course Preparation: Assignment, Assessment/li>
Course Overview
This 2 Day Face to Face 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
Trainer’s Profile
Our Expert 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. Dr. Galar’s work is highly regarded in the maintenance field and has over 30+ years of experience. His research has been widely cited, influencing the development of new methodologies and tools for predictive maintenance and condition monitoring.
Actively involved in national and international committees for standardization and R&D in reliability and maintenance like European Federation of National Maintenance Societies (EFNMS), and so on. He has been instrumental in developing standards and guidelines that have been widely adopted across various industries.
A Full time 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.
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
- Maintenance Managers
- Reliability Engineers
- Data Scientists
- MRO Specialists
- AI and ML Engineers
- Asset Management Professionals
For participation details contact
Mithun Siddartha
+1 780 851 7197 (Canada)