MCCI: Enhancing CNC Machining Performance with AI Monitoring
Monitor & Control system for Chatter identification
CNC Solutions is a precision machine shop specializing in subcontract manufacturing for CNC machining centers, serving demanding sectors such as defense, production automation, and medical equipment. With a strong reputation for quality and reliability, the company continuously explores new ways to optimize operations and remain competitive in a high-precision, high-stakes environment.
As part of the MCCi experiment, CNC Solutions focused on leveraging AI and real-time data to improve machine utilization, reduce waste, and enhance the working conditions of its skilled operators. This initiative targeted both performance gains and a more sustainable, worker-friendly production process.
Precision Manufacturing Optimization
AI-powered Efficiency and Operator Support
- Set up an AI-based system to efficiently address the chatter phenomenon in machining;
- Low availability or suitability of training data or unclear level and type of interaction of the AI system with the machine operators /users;
- Reliability of the set up/integration, referring mainly to the case of low quality/ unreliable sensor inputs;
- The nature of the chattering phenomenon, which, by definition, is hard to predict and measure.
- MEMS accelerometers placed on specific areas of the machines collect vibrational data;
- Experimental trials to generate the dataset for training of the AI algorithm;
- Selection of vibration signal features that have a significant correlation with the phenomenon;
- Training of a Support Vector Machine model for chatter detection;
- Integration in a user-friendly dashboard to support operators;
- Link with the CAM software to enable auto-configuration.
- 10 % increase in Overall Equipment Effectiveness (OEE):
- Real-time performance monitoring and intelligent scheduling improved machine availability and output efficiency;
- 10 % Reduction in Energy Consumption:
- Optimized machining strategies and load balancing helped decrease power usage without compromising quality;
- Scrap Reduction:
- Process improvements and AI-assisted monitoring led to a notable decrease in material waste and rejected parts;
- Lower Operator Stress Levels:
- Enhanced visibility and automation of routine tasks reduced mental workload and improved operator well-being.
CNC Solutions plans to expand the AI monitoring system to additional machines and production lines, aiming to further increase efficiency, reduce scrap, and support operator well-being. Looking ahead, the company also intends to integrate predictive maintenance and adaptive scheduling features, moving toward a more intelligent, data-driven manufacturing environment.
This strategic use of AI is expected to strengthen competitiveness and production resilience in high-precision sectors.