Eastern Railway CPRO Kaushik Mitra said the latest advancement is AI-powered wheel prediction software for locomotives.
“This software carefully monitors locomotive wheel dimensions and is set to revolutionize maintenance practices by reducing human error,” he said.
He said the Wheel Prediction software boasts of several key features to streamline operations and enhance safety.
“Built on a cloud-based platform using Google Sheets, the software provides an intuitive user experience, enabling personnel to input wheel measurements directly from their mobile devices. By analyzing the data provided, the software accurately predicts the likely date when flange or root wear will exceed set limits, allowing timely maintenance intervention,” said Kaushik Mitra.He explained that through accurate monitoring and predictive analysis, this software contributes to increasing the lifespan of locomotive wheels, ultimately reducing maintenance costs and enhancing operational efficiency.
"The software can predict the probable date when the wheels will reach the condemnation limit, allowing preemptive action to be taken," he said.
Mitra said that by aggregating data across different locomotives, the software facilitates derivation of average wheel life, aiding strategic decision making and resource allocation.
“The software can accurately determine the number of locomotives requiring wheel replacement in the near future due to reduced wheel diameter, enabling proactive maintenance planning,” he said.
According to a senior railway official in New Delhi, the integration of AI-powered solutions by ER will not only ensure the safety of passengers and personnel, but also optimize operations for increased reliability and efficiency.
“This software carefully monitors locomotive wheel dimensions and is set to revolutionize maintenance practices by reducing human error,” he said.
He said the Wheel Prediction software boasts of several key features to streamline operations and enhance safety.
“Built on a cloud-based platform using Google Sheets, the software provides an intuitive user experience, enabling personnel to input wheel measurements directly from their mobile devices. By analyzing the data provided, the software accurately predicts the likely date when flange or root wear will exceed set limits, allowing timely maintenance intervention,” said Kaushik Mitra.He explained that through accurate monitoring and predictive analysis, this software contributes to increasing the lifespan of locomotive wheels, ultimately reducing maintenance costs and enhancing operational efficiency.
"The software can predict the probable date when the wheels will reach the condemnation limit, allowing preemptive action to be taken," he said.
Mitra said that by aggregating data across different locomotives, the software facilitates derivation of average wheel life, aiding strategic decision making and resource allocation.
“The software can accurately determine the number of locomotives requiring wheel replacement in the near future due to reduced wheel diameter, enabling proactive maintenance planning,” he said.
According to a senior railway official in New Delhi, the integration of AI-powered solutions by ER will not only ensure the safety of passengers and personnel, but also optimize operations for increased reliability and efficiency.
