The Evolution of Condition Based Maintenance in Maximo Jamie Markham 15.04.2026 The Evolution of Condition Based Maintenance in Maximo Condition Monitoring In Maximo 7, condition‑based maintenance began with the Condition Monitoring application. It provided a straightforward way to generate work orders based on meter readings for specific assets or locations. This worked with characteristic and gauge meters, triggering when a value matched a characteristic or fell outside a defined tolerance range.Although useful, Condition Monitoring was often under‑utilised. It required configuration on a per‑asset or per‑location basis, making it cumbersome to scale. Triggers also ran on a scheduled cron task rather than in real time, meaning work orders were sometimes created with a delay. And if the asset stayed out of range, the next scheduled run could generate additional work orders, resulting in unwanted duplicates. Maximo Asset Health Insights To address these limitations and provide a more holistic view of asset condition, IBM introduced Maximo Asset Health Insights (MAHI) as an add‑on for Maximo 7.6. MAHI shifted the focus from individual meter thresholds to broader health calculations applied at the asset group or location group level.MAHI introduced:Health formulas that could be applied to groups rather than individual assetsWeighted scoring, allowing organisations to control how much each factor contributed to the overall healthThe ability to generate work based on combined factors instead of a single out‑of‑range valueVisualisation of asset health across the entire estateThis was the first major step toward health‑based, rather than meter‑based, maintenance. MAS Health With the transition to the Maximo Application Suite, MAHI evolved into MAS Health, a fully integrated and more powerful approach to assessing asset condition, understanding risk, and managing reliability.MAS Health introduces:A unified asset and location health scoreAdditional calculated scores including risk, criticality, and custom scoring modelsVisual access to maintenance history, incident records, meter trends, and hierarchy positionTools to flag assets for closer monitoring, create service requests, or generate work orders directlyFull support for escalations, enabling automated action when health criteria are metFor reliability engineers, MAS Health provides both detail and context, not just the current state of an asset, but the contributing factors and historical patterns behind that state. Assets and Locations Dashboard MAS 9 added a new Assets and Locations dashboard, expanding how organisations visualise asset condition and reliability. It provides:Map‑based viewsMatrix‑style portfolio analysisA consolidated dashboard showing health, risk, history, relationships, and recommended actionsThis delivers a more holistic, portfolio‑level understanding of asset performance. Condition Insights With MAS 9.2 (set to release in June 2026), IBM is introducing Condition Insights, a major step forward in how organisations understand and act on asset condition. Unlike traditional rule‑based approaches or user‑configured health formulas, Condition Insight is powered by a true AI agent that continuously observes asset data, reasons over patterns, takes action by recommending interventions, and adapts as more information becomes available.This marks a shift from static health scoring to a dynamic diagnostic capability that behaves much more like a digital reliability engineer. The AI analyses a wide breadth of data from within your Maximo Manage environment including work order history, meter trends, KPIs, alerts, and even reliability strategies. It synthesizes these into clear, contextualised insights. Instead of manually reviewing asset records or building analytics models, users receive an instant explanation of what is happening, why it’s happening, and what should be done next. The MAS AI Assistant deepens this further by allowing users to explore these findings conversationally, helping them understand contributing factors and recommended actions in plain language.One of the most impactful elements of Condition Insight is how it democratizes advanced reliability analytics. Historically, gaining this level of insight required specialist data science expertise, custom modelling, or deep familiarity with Maximo configuration. Condition Insight removes these barriers. No formulas, rule sets, or statistical modelling are required. Any organisation, regardless of size or analytical maturity, can benefit from high‑quality diagnostic intelligence immediately.For asset managers and reliability engineers, this means faster clarity, less cognitive load, and the ability to act decisively based on actionable, AI‑derived evidence rather than manual investigation. It complements the existing MAS Health capabilities by layering intelligent interpretation on top of established scoring models, creating a more complete and accessible picture of asset condition and risk. Paul IrvingInnovation Lead Share:
The Evolution of Condition Based Maintenance in Maximo Condition Monitoring In Maximo 7, condition‑based maintenance began with the Condition Monitoring application. It provided a straightforward way to generate work orders based on meter readings for specific assets or locations. This worked with characteristic and gauge meters, triggering when a value matched a characteristic or fell outside a defined tolerance range.Although useful, Condition Monitoring was often under‑utilised. It required configuration on a per‑asset or per‑location basis, making it cumbersome to scale. Triggers also ran on a scheduled cron task rather than in real time, meaning work orders were sometimes created with a delay. And if the asset stayed out of range, the next scheduled run could generate additional work orders, resulting in unwanted duplicates. Maximo Asset Health Insights To address these limitations and provide a more holistic view of asset condition, IBM introduced Maximo Asset Health Insights (MAHI) as an add‑on for Maximo 7.6. MAHI shifted the focus from individual meter thresholds to broader health calculations applied at the asset group or location group level.MAHI introduced:Health formulas that could be applied to groups rather than individual assetsWeighted scoring, allowing organisations to control how much each factor contributed to the overall healthThe ability to generate work based on combined factors instead of a single out‑of‑range valueVisualisation of asset health across the entire estateThis was the first major step toward health‑based, rather than meter‑based, maintenance. MAS Health With the transition to the Maximo Application Suite, MAHI evolved into MAS Health, a fully integrated and more powerful approach to assessing asset condition, understanding risk, and managing reliability.MAS Health introduces:A unified asset and location health scoreAdditional calculated scores including risk, criticality, and custom scoring modelsVisual access to maintenance history, incident records, meter trends, and hierarchy positionTools to flag assets for closer monitoring, create service requests, or generate work orders directlyFull support for escalations, enabling automated action when health criteria are metFor reliability engineers, MAS Health provides both detail and context, not just the current state of an asset, but the contributing factors and historical patterns behind that state. Assets and Locations Dashboard MAS 9 added a new Assets and Locations dashboard, expanding how organisations visualise asset condition and reliability. It provides:Map‑based viewsMatrix‑style portfolio analysisA consolidated dashboard showing health, risk, history, relationships, and recommended actionsThis delivers a more holistic, portfolio‑level understanding of asset performance. Condition Insights With MAS 9.2 (set to release in June 2026), IBM is introducing Condition Insights, a major step forward in how organisations understand and act on asset condition. Unlike traditional rule‑based approaches or user‑configured health formulas, Condition Insight is powered by a true AI agent that continuously observes asset data, reasons over patterns, takes action by recommending interventions, and adapts as more information becomes available.This marks a shift from static health scoring to a dynamic diagnostic capability that behaves much more like a digital reliability engineer. The AI analyses a wide breadth of data from within your Maximo Manage environment including work order history, meter trends, KPIs, alerts, and even reliability strategies. It synthesizes these into clear, contextualised insights. Instead of manually reviewing asset records or building analytics models, users receive an instant explanation of what is happening, why it’s happening, and what should be done next. The MAS AI Assistant deepens this further by allowing users to explore these findings conversationally, helping them understand contributing factors and recommended actions in plain language.One of the most impactful elements of Condition Insight is how it democratizes advanced reliability analytics. Historically, gaining this level of insight required specialist data science expertise, custom modelling, or deep familiarity with Maximo configuration. Condition Insight removes these barriers. No formulas, rule sets, or statistical modelling are required. Any organisation, regardless of size or analytical maturity, can benefit from high‑quality diagnostic intelligence immediately.For asset managers and reliability engineers, this means faster clarity, less cognitive load, and the ability to act decisively based on actionable, AI‑derived evidence rather than manual investigation. It complements the existing MAS Health capabilities by layering intelligent interpretation on top of established scoring models, creating a more complete and accessible picture of asset condition and risk. Paul IrvingInnovation Lead
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