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Letting Data Speak!
Case Study
Optimizing CNC Machine Maintenance with AI
About the Client
A prominent automotive manufacturing company based in India.
Challenge
The client faced significant production losses due to frequent unplanned downtime of their CNC machines. This resulted in high maintenance costs and reduced operational efficiency.
Key Results
Reduced unplanned downtime by 30%, decreasing from 60 hours per quarter to 42 hours per quarter
Achieved 25% cost savings in maintenance expenses
Increased machine lifespan through proactive maintenance strategies
Solution
JashDS implemented a comprehensive AI-driven solution to optimize CNC machine maintenance:
Gathered diverse data from CNC machines, including real-time spindle speed, motor current draw, axis position and velocity, tool wear metrics, and cutting force measurements
Implemented sophisticated machine learning algorithms, including ensemble models and anomaly detection techniques to identify unusual patterns in CNC machine data
Developed a continuous monitoring system that collects real-time data from CNC machines, sensors, and PLCs (Programmable Logic Controllers)
Created a model that generates tailored maintenance recommendations for each machine's specific needs and issues
Implemented an automated system to deliver maintenance recommendations via email, enabling proactive intervention
Technologies Used
Machine Learning (Ensemble Models, Anomaly Detection)
Sensor Integration
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