CODE: PE04
DURATION: 5 Days/10 Days
CERTIFICATIONS: CPD
This course offers a practical understanding of predictive maintenance principles, diagnostic methods, and troubleshooting for electrical systems and networks. The course covers AI-driven analytics, IoT sensors, and digital twin technologies that shift maintenance from reactive to predictive. Participants will learn to apply tools such as vibration analysis, thermal imaging, oil analysis, MCSA, ESA, and partial discharge testing. Through case studies, hands-on sessions, and global standards (IEC, IEEE, ISO 55000), delegates will build the skills to optimize maintenance strategies for safety, efficiency, and compliance.
This course is available in the following formats:
Virtual
Classroom
Request this course in a different delivery format.
Course Outcomes
Delegates will gain the knowledge and skills to:
Understand the core principles and benefits of predictive maintenance in electrical systems.
Identify key failure modes and degradation patterns in motors, switchgears, transformers, and cables.
Implement predictive maintenance strategies using condition-monitoring tools and technologies.
Analyze data trends to predict and prevent electrical equipment failures.
Conduct root cause failure analysis (RCFA) and reliability-centered maintenance (RCM).
Apply advanced troubleshooting methodologies to restore equipment performance efficiently.
At the end of this course, you’ll understand:
This course is designed for electrical engineers, technicians, maintenance and reliability engineers, power system engineers and operators, plant maintenance managers, and industrial automation engineers. It is equally valuable for assets management specialists, energy and utility engineers, safety inspection and compliance officers, technical supervisors, project engineers, engineering trainers and consultants.
✓ Modern facilities
✓ Course materials and certificate
✓ Accredited international trainers
✓ Training materials and workbook
✓ Access to online resources
