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The trouble is that maintenance system data is never perfect, and it varies from site to site and maintainer to maintainer — which usually means more effort goes into wrangling it than acting on it.
Components are pulled for planned preventative replacement long before their useful life is used up, and nobody notices until the invoice lands.
Random failure modes become immediately visible, with the ability to target specific at-risk equipment instead of fleet-wide work.
Planners and reliability engineers spend months collecting data to analyse a single part — time that should be spent on the fix, not the spreadsheet.
From the front line to leaders, IronMan® gives everyone a targeted view of improvements to be acted on.
A cockpit of the actionable items that matter to each user — not a dashboard of everything.
Accelerated tactic optimisation and RCA, powered by automated reliability insights from cleansed age inputs such as Weibull and Crow-AMSAA, plus failure modes surfaced from text mining.
Flags called work and strategies that would waste remaining part life, with one-click accept/reject and value tracking.
FMEA and strategy authoring, evidence-based interval optimisation, and integrated ERP master data outputs for your asset population.
AI-generated usage forecasts, obsolete & duplicate stock detection, and missed warranty claims surfaced automatically.
End-to-end workflow for identifying, triaging and investigating chronic maintenance defects, with bottom-line impact value tracked automatically.
Condition monitoring and predictive analytics across oil, vibration and sensor data, prioritised by risk at the anomaly and equipment level.
Automates Annual Estimate inputs to SAP — the foundation for cost forecasting and budgeting tools to come.
AI-enabled maintenance effectiveness metrics and a live critical asset index, with multiple pathways to benchmark and prioritise by equipment or site.
No data cleanup projects required. IronMan® is engineered to extract value from what you already have — the core method has approved patents in the United States, South Africa, Chile & Japan, with applications pending in six more countries.
Connects to SAP, other ERPs and CMMS platforms — legacy, current or a mix.
Machine learning takes care of data transformation to build a reliable source of truth.
An RCM approach at scale surfaces waste, risk and warranty opportunity — ranked by dollar impact, not alert volume.
Front line to leadership accept or reject each recommendation, with value capture reported automatically.
“Previously it would take me months to collect data to analyse just one part, but now with IronMan® it's all there.”
“A refreshing exception to this is IronMan®. I was impressed by the intelligent use of existing CMMS data to generate useful insights.”
“When it comes to extracting part life automatically, there is no one else doing what IronMan® does.”
We run live demonstrations and zero-risk pilot deployments — so you can see the value before you commit to anything.