Machine diagnostics and monitoring

One of the main areas of activity of the department involves diagnostic systems enabling monitoring of the technical condition of equipment and technological processes. Research focuses on developing methods for machine condition identification and assessment using advanced statistical methods and time-series analysis.

Research includes, among others:

• intelligent sensors and distributed measurement systems
• autonomous sensors powered by energy harvested from the environment (e.g. mechanical vibrations)
• machine monitoring and predictive diagnostics systems

Vibration analysis and energy harvesting

The department conducts research on the analysis of mechanical structures with regard to their susceptibility to vibrations and the possibilities of recovering energy from mechanical vibrations. Research includes analysis of nonlinear systems, chaos phenomena, and interactions between complex dynamic systems.

The results are applied, among others, in the design of energy-efficient measurement systems and autonomous sensors.

Quality control and process analysis systems

An important research direction involves systems for monitoring product quality in industrial processes. Advanced statistical methods and data analysis tools are used to support the control and optimisation of production processes.

Research includes:

• statistical monitoring of continuous and discrete processes
• statistical inference methods
• process data analysis to improve product quality

Autonomous navigation systems

The department develops navigation technologies for autonomous vehicles, particularly intelligent industrial vehicles used in warehouses and production halls.

Research includes:

• integration of data from multiple measurement sources (sensor fusion)
• indoor localisation and navigation systems
• control of precise autonomous vehicles in industrial environments

Industrial vision systems

Another area of activity involves vision systems used in industrial automation and quality control.

Research includes:

• hyperspectral analysis
• image acquisition and analysis using slow-motion techniques
• analysis of material structures using advanced image-processing methods

Modern measurement systems

The department conducts research on new measurement methods and the design of modern sensors used in automation and process monitoring systems.

Research areas include:

• advanced analysis of measurement signals
• feature detection and inference from indirect measurements
• design of new sensor structures
• MEMS technologies
• energy converters based on inductive and piezoelectric phenomena

The Department of Automation conducts courses within the study programme Robotics of Manufacturing Processes, which aims to prepare students for work in modern production environments using industrial robots and advanced automation systems.

Students acquire competencies in the design, programming and integration of robotic systems and production process automation, enabling them to work in the dynamically developing modern industry sector.