Blog 2: Asset Performance Management – From Data to Predictability
This blog is part of a 3-part series on Asset Lifecycle Management.
In this series, I explore how organizations can strengthen their maintenance strategy through the combined power of Asset Performance Management (APM) and Enterprise Asset Management (EAM)—supported by IBM Maximo Application Suite.
- Read Blog 1: Strategy, Execution, and Synergy
- Read Blog 2: From Data to Predictability (this blog)
- Read Blog 3: Operational Excellence in Execution (not yet ready)
Each blog builds on the last, but can also be read independently.
Introduction – Why Asset Performance Management (APM)?
Asset Performance Management (APM) focuses on improving asset reliability and performance through data-driven decision-making. Organizations that successfully implement APM experience fewer unplanned outages and lower maintenance costs, while also achieving significant energy savings and CO₂ reductions through optimized asset utilization.
Solutions in Maximo Application Suite for APM
IBM’s Maximo Application Suite provides a powerful set of integrated tools that give asset managers control and insights into asset performance and health. The core APM solutions within MAS include:
- Monitor – Real-time insights
- Continuously monitor asset performance via sensor and IoT data.
- Respond proactively to anomalies and prevent unplanned downtime.
- Example: Real-time monitoring of motors, pumps, or HVAC systems to reduce energy usage and emissions.
- Health – Asset condition and health scores
- Calculate indicators like Mean Time Between Failures (MTBF) and Mean Time To Repair (MTTR).
- Visualize asset health using real-time condition and historical data.
- Example: Gaining insight into remaining useful life of critical assets, allowing more efficient maintenance planning. It’s not necessary to start with Monitor; even with only work order data, Health can already provide valuable insights, such as identifying assets with frequent breakdowns or high maintenance needs.
- Predict – Predictive maintenance with AI
- Apply artificial intelligence to enable predictive analysis.
- Identify and prevent future failures before they occur.
- Example: AI-driven predictions for bearing wear in production equipment or early detection of corrosion in piping systems.
The Role of Data and AI in APM
Data and AI are essential to modern asset management. AI uncovers patterns that traditional methods often miss, enabling more precise maintenance strategies. This not only reduces operational costs but also contributes to sustainability by minimizing waste and energy usage.
Challenges and Opportunities in Practice
APM provides major opportunities, particularly as organizations face growing pressure from workforce shortages and an aging technician base. Proactive and predictive maintenance allows companies to do more with fewer resources, while simultaneously improving safety and sustainability.
Conclusion and Bridge to the Next Blog
APM is the key to predictable performance, cost control, and sustainable asset management. Maximo Application Suite integrates the necessary technologies to make this possible. In the next blog, we’ll explore the other side of asset management—Enterprise Asset Management (EAM)—and how MAS enhances operational efficiency.