Enhancing Reliability with Asset Health Maintenance Assessment (AHMA) Author Sticky Ryan Finger Global Director, Software Product Marketing GE Vernova’s Software Business Ryan Finger leads global Product Marketing for SaaS, Platform, and AI solutions at GE Vernova, helping customers accelerate their digital and energy transformation journeys. With a strong background in bringing advanced software and data platforms to market, Ryan focuses on positioning solutions that connect asset performance, AI, and industrial applications at enterprise scale. He holds an MBA with a concentration in Computer Science and Digital Transformation, bringing both technical depth and business strategy to the evolving world of industrial technology. François de Fromont Senior Product Manager, Digital Business, GE Vernova François is the Product Manager for the Accelerators product line. He has been with GE for 20+ years and has 30 years of experience designing, deploying, maintaining and product managing industrial equipment and software in various part of the world. Aug 21, 2025 Last Updated Share Introduction:Energy organizations understand centralized data unlocks insights. Yet, data from the field (outage reports & inspections), operator rounds (routes), time series (sensor and historian), and alerts and cases are often difficult to centralize. The common challenges include: Data silos across business units and systems: In many scenarios, field operations, SCADA, historian, CMMS, and EAMs operate independently. With no single source of truth, asset health data gets lost.Lack of interoperability: Connecting systems can be costly and imperfect, sometimes requiring manual work. Legacy systems may not support new integration standards or lack of connectivity as a whole.Poor Data Quality and Confidence: Due to the complexity, trust might be reduced in asset health data. This could be due to missing values, outdated sensors, user entry errors, and other gaps.Lack of Visualization and Diagnostics: Operators and reliability engineers often can’t easily diagnose or act on early-stage defects. Even if the data is centralized, users lack intuitive dashboards to visualize, trend, and associate contributing factors. Ultimately, gaining more control and confidence of data is incredibly important to run an operation with reduced operational risk, increased performance, and overall increased asset reliability. Prefer to listen?Stream our audio version 00:00/00:00 What is Asset Health Maintenance Assessment (AHMA)? Continuous monitoring of asset health is vital to support reliable and consistent performance of assets. Through continuous monitoring, teams are better equipped to detect potential defects early and take more timely corrective actions to help prevent unexpected downtime.With Asset Health & Maintenance Assessment (AHMA), organizations can evaluate the overall condition of assets, whether it's a piece of equipment or a specific location, and generate key performance indicators (KPIs) to aid in planning maintenance activities. Currently, AHMA is offered by GE Vernova as a “Workflows and Processes” subscription in Accelerators – ready-to-use, pre-built configurable content for the Asset Performance Management (APM) suite. A prerequisite to implement AHMA is the APM Health application, a holistic equipment health monitoring solution for condition-based maintenance programs. Readings and measurements can be captured using Rounds Pro (mobile application in APM Health) along with other industrial data sources elaborated below. Asset Health Maintenance Assessment (AHMA) processImage credit: GE Vernova How does Asset Health Maintenance Assessment work? Asset Health Maintenance Assessment utilizes Health Indices (HIs) to categorize an asset's status into three levels: normal, warning, or alert, based on its health evaluation. Asset Performance Management Policies are used to calculate these health indices by analyzing both raw and processed data.AHMA can accommodate multiple input sources: Field data: Readings taken during field operations such as inspections, repairs, and outages.Rounds Pro: Readings taken during rounds inspection by an operator via Rounds Pro.Time Series: Readings collected through an established OT Connect source in on-premises APM or a time series connection in SaaS APM.Alerts and Cases: Notifications are generated when the logic of an asset analytic instance detects an issue, and documentation is created from alerts when further investigation and collaboration are needed to resolve a suspected equipment issue. AHMA gathers data from various sources, processes it, and produces a standardized score that indicates an asset's overall health status. This approach helps provide cohesive and precise evaluations of asset health. Image credit: GE Vernova Image credit: GE Vernova What does Asset Health Maintenance Assessment include? Built to accelerate the outcomes from GE Vernova’s Asset Performance Management software, AHMA includes: The Asset Health Index (AHI): quantifies an asset's overall condition, providing a score from 0 to 100, with 100 representing excellent health and 0 indicating very poor health. The AHI is broken down into sub-level Health Index (HI) to provide additional granularity.The Confidence Index (CI): indicates the level of trust in a Health Index (HI). If certain necessary inputs for calculating the Health Index are absent or outdated, the Confidence Index will decline. Essentially, the more inputs available for calculating the Health Index, the greater the confidence in the HI value produced. An HI value with low confidence necessitates a more detailed review before taking effective action, unlike an HI value with high confidence.The Asset Maintenance Index (AMI): a scoring system used to assess the need and effectiveness of maintenance actions.Auto Recommendations: For each input, recommended actions can be generated automatically, based on the template configuration. Recommended actions are categorized as non-urgent, urgent, or critical within the template. This can be done for each input.Estimated Remaining Life (ERL) and Probability of Failure (PoF): Estimated Remaining Life (ERL) and Probability of Failure (PoF) are calculated based on the asset's age, adjusted for actual asset health. Estimated Remaining Life (ERL) is an estimation of the remaining life of an asset, expressed in years. Probability of Failure (PoF) is the probability of failure within one year.The Asset Risk Index (ARI): the risk associated with the asset based on its current health condition. ARI is measured in the same units as the Asset Criticality Index (ACI), which is included in the template, typically in thousands of dollars (K$). How does Asset Health Maintenance Assessment Work with GE Vernova’s APM? GE Vernova’s Asset Performance Management software is built on a modernized platform, for both on-premises and SaaS deployments. Due to this flexibility, APM is uniquely positioned to help organizations gain more control over their data. With the ability to integrate with EAM/ERP, historian, CMMS, time series and other data sources, APM delivers the ability to centralize and orchestrate data from disparate systems. To assist in the generation of health scores, GE Vernova can provide: Connectivity: with APM Connect and APIs, GE Vernova’s Asset Performance Management software can integrate with systems that are often siloed. This includes EAM, historians, CMMS, and others.Field Data: inspection, outage, and repair data can be imported automatically in APM using the connectivity option or manually with data loader.Rounds Data: the readings taken during inspections or operator routes can be used in calculating an overall health score. Using GE Vernova applications like Rounds Pro (APM Health) or Integrity Mobile (APM Integrity), or other non-GE devices, allows health scores to be updated every time data is collected.Time Series Data: With APM’s connectivity, time series data can flow in both on-premises and in the cloud. As the data is ingested, the health score is updated based on each tag based on limits set.Alerts & Cases: New alerts and cases are imported automatically and included in the calculation of the health score based on their severity and status.Policy Designer: Create business rules and run automated policies in APM to update health scores based on new inputs available.KPI Tracking and Reporting: Multiple dashboards provide a fleet and asset overview of health with the ability to drill down to investigate assets with lower KPI scores. In today’s energy landscape, organizations must move faster and verify that every asset decision is backed by data. By unifying asset health scores, AHMA delivers consistent, reliable insights into equipment condition—enabling organizations to simplify complex data, reduce variability, and prioritize the work that matters most. Whether improving maintenance planning, enhancing reliability, or accelerating digital transformation, AHMA lays the foundation for operational excellence and enterprise-wide impact. Author Section Authors Ryan Finger Global Director, Software Product Marketing GE Vernova’s Software Business Ryan Finger leads global Product Marketing for SaaS, Platform, and AI solutions at GE Vernova, helping customers accelerate their digital and energy transformation journeys. With a strong background in bringing advanced software and data platforms to market, Ryan focuses on positioning solutions that connect asset performance, AI, and industrial applications at enterprise scale. He holds an MBA with a concentration in Computer Science and Digital Transformation, bringing both technical depth and business strategy to the evolving world of industrial technology. François de Fromont Senior Product Manager, Digital Business, GE Vernova François is the Product Manager for the Accelerators product line. He has been with GE for 20+ years and has 30 years of experience designing, deploying, maintaining and product managing industrial equipment and software in various part of the world.