IndustrieDiagnostik

IndustrieDiagnostik refers to the systematic collection, analysis, and interpretation of data to diagnose the condition and performance of industrial systems. It encompasses technologies and methodologies used to detect faults, predict failures, optimize maintenance, and improve process quality across manufacturing, energy, and process industries. The core aim is to minimize unplanned downtime, extend asset life, and reduce operational costs by moving from reactive to proactive maintenance.

Key components include condition monitoring, fault diagnosis, and performance diagnostics. Condition monitoring uses sensors to track parameters such as vibration, temperature, acoustic signals, electrical signatures, and corrosion indicators. Fault diagnosis identifies the likely causes of observed anomalies, while performance diagnostics assesses process efficiency, energy use, and product quality.

Common methods and tools include vibration analysis, infrared thermography, ultrasonic testing, motor current signature analysis, thermometry, non-destructive testing, and data-driven analytics. Modern IndustrieDiagnostik relies on data acquisition from field sensors, PLCs and SCADA systems, cloud-based analytics, machine learning, and digital twins to model and predict system behavior.

Applications span manufacturing lines, rotating equipment (pumps, motors, turbines), power plants, chemical and oil refining, HVAC systems, and transport infrastructure. The approach is often integrated into asset management strategies and maintenance planning, aligned with safety and reliability requirements.

The term is used in German-speaking industries and may denote dedicated service offerings, research groups, or software platforms focusing on industrial diagnostics and prognostics.