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Condition Monitoring - user driven complex conditions

Condition Monitoring - user driven complex conditions

Condition Monitoring - Bundle Customer Advantages

Condition Monitoring - Bundle Customer Advantages

What Problem are We Solving? 

Large volumes of machine and process data make it difficult to continuously monitor operations and manually identify critical deviations. Without automated support, anomalies or critical combinations of operating conditions may remain unnoticed, delaying reactions and increasing waste and downtime.

Solution Description

Condition Monitoring in atmos.io transforms raw production data into actionable alerts and automated responses.

Users can define custom if‑then conditions and thresholds for KPIs or tracked values. When limits are exceeded or complex condition combinations occur, real‑time notifications are sent to managers and operators.

The solution monitors all assets connected to the platform and supports fully customizable rules across machines and production areas. Data from multiple sources—such as winders and related process parameters—can be combined to create advanced conditions, benchmarks, and comparisons (e.g. winders producing the same product).

Condition Monitoring also integrates seamlessly with dashboards, historical reports, and apps, enabling both real‑time control and long‑term performance analysis.

Bundle (Workflow and Task Management + Condition Monitoring + App) 

Condition Monitoring, Workflow, App Bundle
By combining condition monitoring, workflows, and apps, atmos.io enables event‑driven automation: KPIs, data points, or app events are continuously monitored. When anomalies are detected, a workflow is automatically created and pushed to the responsible operator via notification.

 

Example:
Spinning pump pressure exceeds 100 PSI → maintenance workflow is triggered → operator is notified and guided through corrective actions.

Customer Benefits (Bundle) 

  • Fully customizable condition definitions and rules 
  • Real-time alerts with pinpoint accuracy 
  • Faster response times to anomalies and deviations
  • Reduced waste through early detection of issues 
  • Higher operational efficiency and process stability 
  • Automated triggering of workflows and corrective actions
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