Sensors and Signal Processing in Manufacturing Processes

Dear Colleagues,

Manufacturing processes play a critical role in industrial manufacturing. Optimizing these processes is vital for improving the industry’s efficiency, quality, and productivity. In this context, sensors and signal processing play a crucial role. Sensors are used to measure different physical variables and capture real-time information about the manufacturing process, such as cutting forces, temperature, vibrations, and displacements. These sensors can be integrated into machine tools or specific cutting tools.

Signal processing is the stage where sensor data is analyzed, filtered, and interpreted to extract relevant information about the manufacturing process. While focusing on manufacturing, this field also explores the potential integration of sensors and signal processing in other manufacturing processes. The main objective is to extract features and patterns from the signals to evaluate manufacturing quality, detect anomalies, optimize cutting parameters, predict tool wear, and control process stability.

The use of sensors and signal processing in manufacturing processes provides numerous advantages. It enables real-time monitoring of the process status, facilitating early detection of issues and reducing downtime. It also helps improve the precision and quality of end products by optimizing manufacturing parameters. Additionally, it contributes to workplace safety by providing information about hazardous conditions or abnormal situations.

In summary, “Sensors and Signal Processing in Manufacturing Processes” focuses on applying sensor technologies and signal analysis to optimize and control manufacturing processes. This research and development area aims to enhance the industry’s efficiency, quality, and productivity while ensuring the safety and optimal performance of manufacturing processes.

Prof. Dr. Alain Gil Del Val
Guest Editor

Dr. Mariluz Penalva
Dr. Fernando Veiga
Co-Guest Editors

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• manufacturing processes (cutting, joining, welding, additive, etc.)
• CNC machine tools
• cyber-physical systems
• digital twins
• big data management and analytics
• automation
• interoperability
• digital thread
• multisensor data fusion
• data acquisition
• smart monitoring and control
• precision machining
• intelligent process planning
• digital manufacturing
• additive manufacturing sensor integration
• human–machine interfaces
• adaptive interfaces
• human tracking and monitoring
• virtual reality, augmented reality and mixed reality