Proactive asset maintenance with AI-powered insights
Stay on top of asset performance
Extend asset life, reduce costs and optimize performance with IBM Maximo Asset Performance Management (APM). By continuously assessing asset health, predicting risks and applying the right maintenance strategy, APM helps you prevent failures, reduce unplanned downtime and improve reliability. With AI-driven insights and advanced analytics, you can make data-driven decisions and drive long-term asset performance and sustainability.
Prevent failures by continuously assessing asset health, predicting risks and applying the right maintenance strategy. By identifying potential issues before they occur, you can schedule maintenance during planned downtime, reducing the likelihood of unexpected shutdowns and minimizing the impact on your business.
Prolong the lifespan of your assets and delay their replacement by reducing wear and tear. By applying the right maintenance strategy at the right time, APM helps you make data-driven decisions about maintenance, repair and replacement, ensuring that your assets operate at peak performance for longer.
Optimize maintenance schedules by using APM to help reduce unnecessary maintenance and repair work. By identifying the root cause of issues and applying targeted maintenance, you can minimize waste and the cost of spare parts and labor.
Gain insights into asset performance and energy consumption, identifying opportunities to reduce waste and optimize resource usage. By extending asset lifespan, reducing energy consumption and optimizing maintenance schedules, you can minimize your organization’s environmental footprint and contribute to a more sustainable future.
Key capabilities
Reliability-Centered Maintenance (RCM) for optimized asset strategies
Conduct RCM studies to identify critical assets and prioritize failure modes. Integrate Failure Mode and Effects Analysis (FMEA) data into APM workflows to enable data-driven maintenance decisions, optimize asset performance, and align with operational goals.
Condition-Based Maintenance (CBM) for proactive asset care
Take a proactive approach to maintenance by analyzing real-time and historical data to monitor failures before they happen and to initiate the right maintenance at the right time based on actual asset condition and performance. This helps improve asset uptime, reduce unnecessary maintenance.
Forecasting future asset performance and maintenance needs
AI-powered forecasting delivers accurate insights into asset performance and maintenance needs. By analyzing trends and patterns, it predicts failures before they occur and prescribes optimal maintenance plans. This enables proactive maintenance, minimizes downtime, and optimizes resources for better business outcomes.
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.
Maximo APM applications
IBM Maximo provides a comprehensive APM solution that enhances its enterprise asset management (EAM) with RCM, CBM and advanced forecasting, all in a unified platform powered by AI, analytics and automation.
Provides a comprehensive view of your assets’ health, criticality and risk. It uses advanced scoring methodologies to analyze operational data from various sources, including Maximo® Manage and IoT devices. With Health, you’ll gain a deeper understanding of your assets’ condition, enabling you to prioritize maintenance, optimize reliability, and make better operational decisions.
Uses AI and machine learning to predict asset performance and maintenance needs. By analyzing time-series data from Maximo Monitor and failure data from Maximo Manage, it builds models that forecast days to failure, probability of failure and other key indicators. Maximo Predict provides actionable insights, enabling you to anticipate and prevent issues, optimize maintenance and reduce downtime.
Provides AI-powered remote monitoring to enable advanced Condition Based Maintenance (CBM) practices at scale. With Monitor, you can ingest and unify operational data from PLCs and SCADA systems, with IoT data from devices and sensors into a single source of truth. There you can process this data through advanced analytics pipelines and anomaly detection models to drive alerts, dashboards and integrations to help asset managers, improve reliability, reduce downtime and optimize maintenance strategies.