Characterization and monitoring of the machining process

DESCRIPTION

Machining is one of the fundamental techniques in the manufacturing industry, used to precisely shape parts through processes such as turning, milling, drilling, and grinding. This sector is particularly critical in the production of high-value components, such as parts for the aerospace, automotive, and medical industries, where even a small defect can lead to significant economic losses.
Real-time process analysis has become a key tool for ensuring machining quality. This approach allows for the supervision of every stage of the process, identification of deviations, and detection of anomalies that could cause defects in parts. For high-cost components, this activity is essential to minimize material waste, reduce downtime, and avoid costly rework.
This asset applies artificial intelligence models for real-time process monitoring. To achieve this, the machining process is thoroughly analysed to identify the signals that best define it and provide a reliable foundation for anomaly analysis. These signals are processed to generate the information that feeds predictive models capable of defining the operational normality of processes. The system monitors normality and alerts about any anomalies that occur. All collected information is made available to operators and supervisory teams through real-time applications that provide data on new operations and their normality.
The alerts generated are integrated with various systems, such as CNC, email, corporate platforms, and any connected smart device.