AI-driven operational intelligence platform for asset performance optimization
Move from reactive maintenance to AI-driven operational decisions
IBM Maximo Asset Performance Management extends Maximo’s enterprise asset management capabilities with asset health monitoring, reliability engineering, predictive analytics, and AI-embedded decision support. By connecting asset insights directly to maintenance execution, Maximo APM helps organizations identify emerging risks, predict failures, optimize maintenance strategies, and prioritize corrective actions before disruptions occur.
Maintenance and reliability teams can move beyond reactive maintenance to implement condition-based, predictive, reliability-centered, and prescriptive maintenance strategies within a unified platform.
Detect degradation earlier, predict failures before they impact operations, and prioritize the right maintenance actions. Improve reliability, reduce operational risk, and keep critical assets running longer.
Maximize the value of critical assets through data-driven maintenance and replacement decisions. Use asset health, risk, and performance insights to optimize lifecycle strategies and delay unnecessary capital investments.
Prioritize maintenance based on asset condition, failure risk, and criticality. Reduce unnecessary maintenance activities, optimize labor and spare parts usage, and improve maintenance effectiveness.
Optimize asset performance and energy efficiency using condition monitoring, reliability insights, and predictive maintenance. Reduce waste, extend asset life, and improve resource utilization across operations.
AI-driven insights that elevate every maintenance strategy
IBM Maximo APM embeds AI directly into maintenance and reliability workflows, helping teams understand the asset condition, investigate emerging risks, accelerate reliability engineering processes, and prioritize maintenance actions. Rather than requiring specialized analytics expertise, AI-assisted capabilities help reliability and maintenance teams move from insight to action faster.
Maximo Condition Insight enhances your APM program by transforming real-time and historical asset data into clear, actionable recommendations. It highlights health trends, identifies anomalies, and supports prescriptive maintenance decisions—all within the Maximo Application Suite.
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Built for modern maintenance operations
Condition-Based Maintenance (CBM)
Monitor asset health in real time using operational, IoT, inspection, maintenance, and quality data. Consolidate leading and lagging indicators into a comprehensive health score that helps maintenance teams identify degradation, detect anomalies, and prioritize attention before performance is impacted. Gain a current view of asset condition across your enterprise and focus resources where they are needed most.
Predictive Maintenance (PdM)
Move beyond understanding current asset condition to predicting future performance. By leveraging historical asset health data, operating conditions, failure patterns, and machine learning models, organizations can forecast emerging issues and estimate when assets will no longer perform optimally. Predict failures before they occur and schedule interventions at the most effective time to minimize risk, downtime, and maintenance costs.
Reliability-Centered Maintenance (RCM)
Develop and operationalize maintenance strategies based on asset criticality, failure modes, business risk, and operational impact. Standardize maintenance decisions using proven reliability methodologies and continuously refine strategies using real-world performance data. Align maintenance activities with business objectives while improving reliability, safety, and asset availability.
Prescriptive Asset Intelligence
Combine asset health insights, predictive analytics, maintenance history, reliability strategies, and operational context with AI-powered recommendations to guide decision making. Move beyond identifying problems to understanding the most effective response. Augment maintenance teams with contextual intelligence that helps prioritize actions, evaluate tradeoffs, and make faster, more informed decisions.
AI agents for asset performance management
IBM Maximo is evolving from traditional predictive maintenance toward AI-native operational decision support.
AI agents embedded directly into maintenance and reliability workflows help organizations reduce decision complexity, improve operational consistency, and accelerate action across the asset lifecycle.
Rapidly analyzes asset data, strategies, work history, alerts, and meter trends to explain asset condition, identify degradation patterns, and recommend actions.
Accelerates reliability engineering by helping teams build FMEAs, maintenance strategies, and mitigation workflows using AI-assisted recommendations.
Enhances alerts with contextual diagnostics and recommended maintenance actions based on known failure modes and asset history.
Case studies
Downer and IBM are using smart preventative maintenance to keep passengers on Australia's light and heavy rail systems moving safely, reliably, comfortably and more sustainably.
GRE is using Maximo to analyze sensor data from 188,000 assets globally in a move towards condition-based maintenance, triggered by actual run time, excessive heat or vibration.
Using Maximo Monitor, Novate has seen a 30% improvement in product quality by knowing how assets perform in real time.
DP World gets real-time insights into equipment performance, enabling proactive maintenance strategies that reduce downtime and improve overall equipment effectiveness.