Advanced Maintenance Management

Maintenance strategies in leading industrial organizations are rapidly transitioning from reactive approaches—where intervention occurs only after equipment failure—to proactive paradigms that emphasize prediction, prevention, and strategic asset care. Modern maintenance is a core component of life-cycle-focused Asset Management, enabling organizations to anticipate and address potential issues before they escalate, thereby enhancing operational continuity and asset reliability.

This Advanced Maintenance Management course is designed to equip participants with both the conceptual foundations and practical competencies essential for implementing contemporary maintenance and asset optimization methodologies. Through a structured curriculum grounded in industry best practices, the program fosters the ability to enhance asset performance, minimize downtime, reduce lifecycle costs, and deliver measurable return on investment (ROI).

Participants will engage with key topics including:

• Strategic Asset Management principles as a framework for structured maintenance governance.
• Utilisation of Key Performance Indicators (KPIs) and balanced scorecard methodologies to systematically measure and improve performance.
• Assessment of maintenance maturity and the development of targeted improvement roadmaps.
• Building robust business cases through cost/benefit analysis to justify targeted asset management improvements.
• Introduction to risk-based maintenance techniques to prioritize resources and mitigate operational risk.
• Principles of Life Cycle Management, including Systems Engineering and reliability, availability, maintainability, and safety (RAMS) frameworks.
• Life-cycle costing methods that support informed decision-making for asset investments.
• Exploration of advanced predictive and smart maintenance concepts, leveraging modern technologies to pre-emptively detect failure modes.

Through a combination of theoretical grounding and application-focused insights, this program prepares professionals to lead maintenance transformation initiatives and to integrate advanced maintenance strategies into organizational practices for sustained performance gai

This training course is suitable to a wide range of professionals involved in the area of Advanced Maintenance Management, but will greatly benefit:

• All professionals involved in Maintenance Management
• Professionals involved in work planning & control
• Maintenance Supervisors
• Maintenance Engineers
• Maintenance Team Leaders and Managers
• Operations Team Leaders and Managers

Day One: Foundations of Asset Management for Maintenance Optimization

• Conceptualizing Asset Management as an integrated business process for achieving organizational objectives.
• Exploring the Asset Management Landscape Model to understand the interactions between governance, planning, and execution.
• Establishing a strategic framework and Line of Sight that connects organizational objectives to asset-related activities.
• Developing and differentiating between an Asset Management Policy and an Asset Management Strategy.
• Formulating a (strategic) Asset Management Plan that aligns maintenance operations with enterprise goals.
• Defining the role and scope of Maintenance Management within overall asset governance.
• Clarifying Asset Management roles at strategic, tactical, and operational levels.
• Overview and application of ISO 55000 — the internationally recognized standard for Asset Management systems and principles.

Day Two: Assessing Asset Management Maturity for Maintenance Advancement

• Measuring organizational performance using structured frameworks.
• Differentiating between leading and lagging indicators and applying Key Performance Indicators (KPIs) and dashboards to track outcomes.
• Conducting assessments and benchmarking against internationally accepted standards such as ISO 55000.
• Performing Asset Management maturity assessments to identify improvement opportunities.
• Utilizing tools such as gap analysis based on ISO 55000 requirements.
• Executing self-assessment methodologies to strengthen internal compliance and performance.
• Developing a roadmap for continuous improvement in maintenance practices.
• Building business cases for enhancement initiatives using cost/benefit thinking and financial justification.
• Addressing practical aspects of implementation in organizational contexts.

Day Three: Managing Asset Risks through a Risk-Based Maintenance (RBM) Approach

• Understanding that not all failures have equal impact — applying risk principles to prioritize maintenance.

• Analyzing risk at the business level and its influence on operational performance.

• Using tools such as risk matrices and risk registers for documenting and managing asset risks.

• Evaluating risk at the asset level, including the behaviour of system failures.

• Selecting appropriate maintenance interventions based on risk exposure and consequence severity — the core of Risk-Based Maintenance (RBM).

Day Four: Life Cycle Management of Physical Assets

• Introducing Life Cycle Management (LCM) as a structured approach for maximizing asset value from acquisition to disposal.
• Mapping the life cycle of an asset, including stages such as planning, acquisition, operation, maintenance, and end-of-life.
• Applying demand forecasting techniques for effective resource and capacity planning.
• Incorporating Systems Engineering practices to ensure integrated performance and reliability.
• Addressing RAMS requirements (Reliability, Availability, Maintainability, Safety) and associated methodologies.
• Evaluating and applying Life Cycle Costing (LCC) to support investment decisions and optimize total cost of ownership.
• Considering strategies for disposal, replacement, life extension, and asset rationalization.

Day Five: Smart and Predictive Maintenance

• Introducing the principles and rationale behind Predictive Maintenance (PdM) as a proactive strategy.
• Reviewing relevant PdM technologies and their appropriate application contexts.
• Exploring Smart Maintenance approaches that leverage modern data technologies to monitor and evaluate asset performance continuously.
• Covering essential aspects of data analysis, signal processing, and condition monitoring.
• Highlighting optimization techniques aimed at refining maintenance strategies.
• Utilizing decision support tools for informed maintenance planning and execution.