Monitoring context built around failure modes, evidence, and engineer review.
AndonEAM connects configured telemetry and approved RCM context to help teams investigate potential degradation. It proposes a model, evidence trail, diagnostic hypothesis, and next action for an engineer to validate rather than presenting an alert as a confirmed diagnosis.
The Problem
A threshold or generic model can identify an unusual signal without explaining its asset context. If monitoring rules are not connected to an approved FMEA, relevant history, and operating conditions, engineers still have to determine whether a signal represents degradation, a load transient, an instrumentation issue, or another cause.
When an alert lacks a failure-mode hypothesis, supporting evidence, and a review path, a reliability engineer must reconstruct the diagnostic context manually.
"Temperature high" describes a signal. Reviewers also need the candidate failure mode, affected component, supporting evidence, and a suggested next step.
Bearing wear, thermal degradation, cavitation, and seal leakage have different physical signatures and may require different analytical methods and tuning.
Failure-mode knowledge often remains in a separate document or spreadsheet while monitoring rules are configured without that engineering context.
When case evidence and work-order outcomes remain in separate systems, prior investigations are difficult to compare with a new signal.
How It Works
AndonEAM connects source data, structured drafts, engineering review, and approved downstream records in a governed maintenance workflow.
An approved FMEA or other customer-validated failure-mode register can provide the diagnostic context for monitoring. The imported scope and taxonomy are confirmed before rules are activated.
The system can suggest a model family based on the failure mode, available data, and configured engineering rules. Customer engineers validate model choice, data sufficiency, tuning, and operating boundaries before relying on the output.
Your engineers can map available telemetry streams — such as vibration, temperature, pressure, flow, or current draw — to the failure modes and components they are intended to indicate. Those mappings are validated against site instrumentation and operating context.
Configured telemetry can be evaluated by the approved models and cadence. When a rule detects an anomaly, AndonEAM can compare it with the available failure-mode taxonomy and historical records, then open a draft diagnostic case with a hypothesis and suggested next action.
Each diagnostic case can enter the reliability team's review queue with the proposed failure mode, model used, anomaly evidence, available historical context, and a suggested intervention for approval, revision, or escalation.
Capabilities
Monitoring rules can be linked to customer-approved FMEA records so reviewers can see the component, candidate failure mechanism, and maintenance context associated with an alert. A link provides context; it does not prove the diagnosis.
Available model families include static rules, statistical fingerprinting, time-series forecasting, multivariate regression, unsupervised clustering, and supervised classification. Selection and tuning are reviewed against the data and use case.
Where the necessary history is available, an anomaly can be compared with prior cases and the configured RCM taxonomy. The result is a candidate pattern match for an engineer to assess, not a confirmed root cause.
A diagnostic output can retain the proposed failure mode, the model that detected the anomaly, supporting evidence, available historical comparisons, and the suggested maintenance response. Engineers can review and challenge that reasoning before action.
Built For
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See how AndonEAM could fit your reliability programme. Scope, source data, integrations, governance, and deployment requirements are validated with your team.