Master maintenance strategies, failure analysis, and predictive techniques to optimise reliability and reduce operational costs.
Predictive diagnostic techniques
Full Code
MTN0102215
Module Type
E-learning
Description
Short description:
Learn how predictive diagnostic techniques detect equipment deterioration and support proactive maintenance decisions.
Long description:
Designed for maintenance and reliability professionals, this module provides an in-depth overview of predictive diagnostic techniques used to monitor equipment condition and detect early signs of deterioration without interrupting operations. Learners will explore how non-destructive predictive methods such as vibration analysis, thermography, lubricant oil analysis, acoustic emission testing, penetrating liquids, magnetoscopy, optical inspection, and radiography are applied across industrial environments to improve reliability and reduce unexpected failures. Through practical examples, technical explanations, and diagnostic scenarios, participants will interpret deterioration indicators, analyse equipment behaviour, and identify the most suitable predictive technique according to the type of equipment and failure mode involved. The module also examines the advantages, limitations, operational requirements, and real-world applications of each technology, supporting informed maintenance decision-making and proactive equipment management. This module supports the development of condition-based maintenance competencies within modern industrial operations.
What you will learn
- Identify predictive diagnostic techniques used to monitor equipment condition in industrial environments.
- Analyse vibration data to detect early-stage mechanical faults in rotating equipment.
- Interpret thermographic and oil analysis results to assess equipment deterioration and failure risks.
- Select appropriate predictive techniques based on equipment characteristics and failure modes.
- Evaluate diagnostic data trends to support proactive maintenance interventions.
Module content
Related Occupations
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