Category · 19 products
Asset Performance Management Software
Asset performance management is the most marketing-saturated category in this directory. Every vendor claims AI and prediction, and the claims are frequently indistinguishable from one another on a home page. So this directory holds a deliberately strict line: failure prediction, anomaly detection and digital twin capability are recorded as supported only where a vendor source actually describes the capability. A banner saying AI-powered is not evidence of anything, and where that was all we found, the capability is marked not verified.
The products divide usefully. APM suites cover asset health, reliability strategy and often work management integration. Condition monitoring products are built around measurement, usually vibration, and frequently come with the vendor’s own sensors. Predictive analytics platforms ingest existing process data and apply machine learning without supplying hardware. Reliability modelling tools are engineering tools for RCM and FMEA rather than monitoring systems.
The single most important commercial fact in this category is whether a product requires the vendor’s own sensors. Software that reads your existing historian is a different commitment from a platform that only works with proprietary hardware you must install and maintain, and each profile states which it is. Some entries are closer to a monitoring service than licensable software, and those say so too.
Vendors
ABB, AspenTech (Emerson), Augury, AVEVA, Bentley Systems, C3.ai, Emerson, Falkonry, Fluke Reliability (Fortive), GE Vernova, Honeywell, IBM, Infinite Uptime, Nanoprecise Sci Corp, SAP, Siemens, SKF, SymphonyAI, TwinThread
19 matching products · clear filters
Senseye Predictive Maintenance
Siemens
Cloud, machine learning based predictive maintenance software from Siemens that provides advisory condition monitoring using machine signals sent from a customer existing data collection systems. It supplies no sensors of its own.
Documented API Work order and CMMS integration Sensor connectivity Asset health scoring
- Cloud
- Commercial
- Predictive AI and analytics
- Enterprise
Honeywell Forge Asset Performance Management
Honeywell
Honeywell vendor-agnostic asset health and performance platform, currently marketed as Honeywell Forge Performance+ for Industrials Asset Performance. Combines first-principles efficiency models, machine-learning anomaly detection and mechanical fault monitoring. On-premises or cloud.
Reporting and dashboards Work order and CMMS integration Root cause analysis Reliability modelling
- Cloud, On-premises
- Commercial
- APM suite
- Enterprise
SAP Asset Performance Management
SAP
Cloud asset performance management product from SAP that runs an RCM process based on SAE JA1012 and standard FMEA to analyse failure modes, with failure data synchronised from SAP ERP. Pricing and much documentation are behind a 403 block.
FMEA support Reliability-centred maintenance Reliability modelling
- Cloud
- Commercial
- APM suite
- Enterprise
AssetWise Reliability
Bentley Systems
Reliability engineering and asset performance software for building proactive inspection and maintenance programmes, with named support for RCM2, FMEA, RBI and SIF plus asset condition assessment.
Digital twin FMEA support Reliability-centred maintenance Reliability modelling
- Cloud, On-premises
- Commercial
- Reliability modelling
- Medium, Enterprise
AVEVA Predictive Analytics
AVEVA
Predictive maintenance software that flags asset anomalies before failure and supports fault diagnostics and case management, with predefined model templates and the option to bring your own algorithms in Python.
Root cause analysis Failure prediction Anomaly detection Condition monitoring
- Cloud
- Commercial
- Predictive AI and analytics
- Medium, Enterprise
Aspen Mtell
AspenTech (Emerson)
Machine learning based prescriptive maintenance software that builds anomaly and failure agents from process and condition data, with embedded FMEA to prescribe corrective action and push coded work orders into an EAM system.
Work order and CMMS integration FMEA support Asset health scoring Failure prediction
- Not verified
- Commercial
- Predictive AI and analytics
- Medium, Enterprise
GE Vernova Asset Performance Management
GE Vernova
Modular asset performance management suite for industrial and energy assets, sold by GE Vernova after the GE split. Includes the Meridium and SmartSignal lines and is positioned around asset health, reliability and integrity.
Sensor connectivity Asset health scoring Condition monitoring
- Cloud
- Commercial
- APM suite
- Enterprise
Published comparisons
How to choose
How to choose in this category
Earn the right to buy this. APM sits on top of working maintenance management. If your asset register is unreliable or your work history is thin, a prediction platform will produce confident output from bad data. Get the asset hierarchy and criticality classification right first, because criticality is what tells you which assets justify monitoring at all.
Know which failure modes you are targeting. Prediction is only meaningful against a specific degradation mechanism with a measurable signal and a useful lead time. From remaining useful life to FMEA and condition monitoring techniques cover what is actually detectable and by what means. Vendors rarely start here, and it is the question that determines whether a deployment pays back.
Decide whose sensors. Proprietary-sensor platforms deploy quickly and lock you in. Historian-reading software avoids new hardware and depends entirely on the quality of what you already measure. Both work; the choice has long consequences for cost and portability.
Insist that output lands in a work order. An alert nobody actions is a cost, not a benefit. The integration into maintenance execution is where value is realised, and it is routinely deferred to phase two and then never done. Turning recommendations into maintenance action covers the loop that has to close.
Be sceptical about model performance. No figure in this directory describes accuracy, precision or lead time, because any such number would have to come from the vendor or be invented. Threshold versus statistical anomaly detection explains why simple limits often match complex models on industrial data, which is a useful corrective when evaluating a demo.
Mind the difference between predictive and condition based. They are not the same thing and the distinction affects what you must install and what you can expect: see condition based versus predictive maintenance and RCM versus predictive maintenance.
Further reading on this site
For narrative evaluation guidance, see predictive maintenance software and platforms compared. On architecture, edge versus cloud for predictive maintenance and digital twin and CMMS integration cover decisions that outlast the product choice.
Frequently asked questions
Yes, and the profiles say so where we established it. Several companies in this space sell a sensor and analysis service with a managed element rather than software you licence and operate. That is a materially different purchase with a different cost structure, and worth knowing before a comparison.
None. There are no accuracy, precision, lead time or savings figures anywhere in this directory, because every such number would be either vendor-supplied marketing or invented. The profiles describe what a product does and what evidence exists for it, and nothing else.
A reliable asset register, a criticality assessment so you know which assets justify monitoring, identified failure modes with a detectable signal and useful lead time, and a path from an alert to an actioned work order. Deployments usually fail on the first and last of those rather than on the analytics.
No. A CMMS or EAM manages maintenance work and asset records. APM analyses asset condition and reliability to decide what maintenance should happen. APM generally assumes a work management system already exists and integrates with it. Buying APM without working maintenance management underneath rarely produces value.
It depends on the product, and it is the most consequential commercial difference in this category. Some platforms only work with their own hardware, which deploys quickly and ties you to that vendor. Others read an existing historian or control system and add no hardware, which avoids lock-in and depends entirely on what you already measure. Each profile states which model applies.
Because a marketing claim of AI is not evidence of failure prediction. This directory records that capability only where a vendor source actually describes the mechanism, the data it needs or the failure modes it addresses. Where all we found was general AI language, the capability shows as not verified. That is a statement about the published evidence, not a judgement that the product cannot do it.
Selecting Asset Performance Management Software?
Independent help building the requirement, shortlisting honestly and designing the integration the chosen system will depend on. No reseller arrangements.
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