An Intensive 5-day Training Course
Asset Management Maintenance in the New Digital Era
Harnessing IoT Technologies and Artificial Intelligence in Asset Management
CLASSROOM DATES
INTRODUCTION
Asset management and maintenance practices are transforming rapidly through the integration of digital technologies. Traditional reactive and preventive approaches are being replaced by data-driven, predictive methods that improve reliability, efficiency, and long-term sustainability. This Asset Management Maintenance in the New Digital Era training course provides participants with the knowledge, tools, and strategies to harness AI, IoT, and predictive analytics for optimized asset performance.
Delegates will explore ISO 55000-aligned frameworks that connect maintenance with business strategy, ensuring that asset-related decisions deliver measurable organizational value. Participants will also learn about condition-based maintenance (CBM) technologies, including:
- Vibration analysis and acoustic monitoring
- Infrared thermography and lubricant diagnostics
- Predictive analytics using AI and Machine Learning
- CMMS data analysis for strategic decision-making
- IoT-enabled real-time monitoring systems
- Explainable AI (Ex-AI) for enhanced reliability
By engaging with practical case studies and simulation exercises, delegates will see how advanced digital tools can be applied to real-world maintenance challenges. This training enables professionals to design strategies that balance performance, cost, and risk, while fostering a culture of continuous improvement and innovation. Ultimately, participants will leave prepared to lead digital transformation initiatives that reduce downtime, extend asset lifecycles, and improve overall organizational resilience.
TRAINING OBJECTIVES
By the end of this Asset Management Maintenance training course, participants will be able to:
- Understand asset management frameworks aligned with ISO 55000.
- Apply predictive and condition-based maintenance (CBM) strategies.
- Integrate AI and machine learning in maintenance decision-making.
- Analyze CMMS data to improve reliability and reduce costs.
- Utilize IoT and smart sensors for real-time fault detection.
- Evaluate maintenance strategies using case-based learning.
- Apply advanced diagnostics to detect early equipment failures.
- Promote a culture of proactive asset performance optimization.
WHO SHOULD ATTEND?
This EuroMaTech Asset Management Maintenance Course is designed for professionals involved in maintenance, reliability, and digital transformation, including:
- Asset, Maintenance, and Reliability Managers
- Operations and Project Engineers
- Plant Managers and Technical Directors
- Reliability Engineers and CMMS Specialists
- IT and Data Analysts Supporting Maintenance Systems
- Engineering Consultants and Performance Analysts
TRAINING METHODOLOGY
This EuroMaTech training course uses a highly practical methodology combining expert-led presentations with interactive workshops, case studies, and group activities. Delegates will engage in simulation-based exercises and scenario analysis that reflect real workplace challenges. By working with CMMS data, participants will learn how to convert information into actionable insights for predictive maintenance and strategic decision-making.
Hands-on practice with AI, IoT, and condition-based technologies ensures participants gain confidence in applying advanced tools to optimize asset performance. Collaborative discussions will allow delegates to share their own organizational experiences, enriching the learning process. This blended methodology ensures a strong link between theory and practice, preparing professionals to implement improvements immediately in their work environments.
TRAINING SUMMARY
The Asset Management Maintenance in the New Digital Era training course delivers a comprehensive understanding of how digital transformation is reshaping maintenance strategies. It equips professionals with the ability to implement predictive maintenance technologies, apply ISO 55000 frameworks, and foster continuous improvement cultures.
Delegates will leave with a toolbox of practical skills, ranging from AI-powered analytics to IoT-enabled monitoring, enabling them to reduce unplanned downtime and extend asset lifecycles. This EuroMaTech course ensures participants are ready to meet modern maintenance challenges, optimize costs, and align asset strategies with organizational goals.
TRAINING OUTLINE
Day 1: Principals of Asset Management and Introduction to Predictive Maintenance and AI Fundamentals
- Asset Management as a Business Process
- Asset Management Scope & Definitions
- ISO550000 – The International Standard on Asset Management
- What is Predictive Maintenance (PdM) and Focus of Research in CBM?
- Traditional Maintenance vs. Predictive Maintenance: The P-F Curve
- Introduction to AI, Machine Learning (ML), and Deep Learning (DL)
- The Role of AI in Predictive Maintenance
Day 2: Assessing & Managing Asset Management Risks
- Risk in Asset Management
- Risk on Business Level
- Stakeholder Risks
- Risk on Asset Level – Risk Based Maintenance
- Learning from Failures – Decision Analysis of Major Disasters
Day 3: Asset Management Policy, Strategy and Planning and Reliability Centred Maintenance (RCM)
- Asset Management Policy
- Developing (Strategic) Asset Management Plan(s)
- Implementing (Strategic) Asset Management Plan(s)
- Failure Mode and Effect Analysis
- Fault Tree Analysis
- Reliability Block Diagrams
Day 4: Managing Asset Lifecycle Decisions & Activities and Artificial Intelligence in Maintenance Decision Analysis
- Life Cycle of Assets and Its Aspects
- Repair – Replace Decision Analysis Through the Bathtub Curve
- The Concept of Fuzzy Logic
- Benefits that Can Result from the Application of CMMS
- Evidence of ‘Black Holes’ ) Phenomena in CMMSs
- The Decision-Making Grid (DMG): Part 1 – Strategy Selection (Effectiveness)
- The Decision-Making Grid (DMG): Part 2 – Focused Actions (Efficiency)
- The Decision-Making Grid (DMG): Part 3 – Cost / Benefit Analysis
- Case Studies of Applying the DMG Framework from Industry
Day 5: Financial & Business Impact of Asset Management and Model Deployment, Maintenance, and Future Trends
- Integration with Existing Maintenance Systems Such as Computerised Maintenance Management Systems (CMMS), and Enterprise Resource Planning (ERP) Systems
- Challenges, Ethical Considerations, and Future Trends
- Explainable AI: Performance, Attributable, and Responsible Analytics.
- Challenges in scaling AI for Predictive Maintenance Across Industries
- The Future of AI in Industrial Automation and Predictive Maintenance
- Getting the Best out of Data in Computerized Maintenance Management System (CMMS)
- AI Challenges and AI from its Pioneers (from Noble Prize Winners in AI)
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ACCREDITATION
EuroMaTech is registered with the National Association of State Boards of Accountancy (NASBA) as a sponsor of continuing professional education on the National Registry of CPE Sponsors. State boards of accountancy have final authority on the acceptance of individual courses for CPE credit. Complaints regarding registered sponsors may be submitted to the National Registry of CPE Sponsors through its website: www.NASBARegistry.org.
Euromatech is a Knowledge & Human Development Authority (KHDA) approved training institute in Dubai, licensed and approved to deliver training courses in the UAE.
The KHDA is the regulatory authority in the UAE, that oversees administering, approving, supervising, and controlling the activities of various education providers in the UAE. We are proud of our commitment to ensuring quality training courses and status as a KHDA-approved training provider.
