Predict.Prevent.Perform

Exploring how IoT, AI, and digital twins are transforming predictive maintenance in machine tools, enabling manufacturers to shift from reactive fixes to intelligent, data-driven operations.

- BY: Shriyal Sethumadhavan

IoT is transforming predictive maintenance by enabling real-time monitoring and data analysis to anticipate machine failures.

“By embedding sensors to track performance metrics, usage patterns, and environmental conditions, manufacturers can use this data to shift from reactive to proactive maintenance,” says Prakash T, Deputy Manager Marketing, Brother Machinery India Pvt Ltd. The measurable benefits include reduced downtime, longer machine lifespan, improved operational efficiency, and lower maintenance costs – ultimately enhancing reliability and maximising productivity across manufacturing processes.

“IoT is transforming predictive maintenance (PdM) in machine tools by enabling real-time condition-based monitoring (CBM), early fault detection, and data-driven decision-making,” says Ramesh J, Product Head - Industry 4.0 & Marketing, Micromatic Machine Tools Pvt Ltd. He explains, “The process begins by identifying components prone to failure and selecting relevant data points for AI/ML model building. This data is collected through external sensors – such as spindle vibration, hydraulic oil level, and coolant pressure – as well as controllerintrinsic inputs like alarms, spindle speed, load, and vibration, which are often overlooked.”

Combining these data sources offers a comprehensive view of machine health, enabling AI/ML models to analyse patterns and anomalies for accurate failure prediction well in advance.

Highlighting the benefits for manufacturers, Vaibhav Shah, CMO & Chief of Global Business, Cosmos Group of Companies (CNC Machines), lists the following. He mentions that Cosmos Digifac provides every industry with all possible benefits and solutions.

• Reduced downtime: Up to 30-50 per cent reduction in unplanned downtime, improving machine availability and production continuity.