Envision

September 7, 2022

O & M solutions driven by analytics and AI

To support and sustain the metropolitan transit systems of urban travelers in meeting the rapid demands of commuting, deploying, reliable and state-of-the-art technology solutions enhance the reliability for :

 Automation from manual operations processes to automatic processes

 Analytics-driven operations management for effective resource utilization

 Robust O & M solutions for handling diversified assets and operations planning

 AI/ML-based algorithmic solutions

Envision’s Integrated Digital platform ranging from Enterprise Asset Management, Operations, Maintenance, and Analytics that support the key business elements like :

 Time (reduced over-all cycle times identifying the delay and resolution)

 Visibility (effectively monitor and control)

• Utilization (optimized resource utilization)

 Cost (reduced operations cost)

 Risk (better accountability and mitigation)

Operational Analytics like :

• Predict & Demand to forecast for route planning and optimization

• Revenue realization and forecasting analytics

Maintenance Analytics like :

• Identify trends for asset and resource performance, minimize manual operations, and maintain a healthy asset

• Actions for faster restoration of services or adapting to changing service demand

• Defect/failure analysis - diagnosing which parts are more likely to fail based on their historical, sensor data available

• Predictive analytics and a nomaly detection on critical components to identify failure trends and early warnings. Deploy algorithmic solutions

Advanced Analytics Modelling and RCA (root cause analysis) for the following areas to be taken into consideration during the project implementation

• Customer delight & passenger grievances

• Graph DB-based network analysis

• Visualization and Spatial analytics

The AI/ML-based predictive Intelligent solutions for - Defect Detection and identification of physical defects such as asset failures, cracks, and scratches with in railway components

• Defect Prediction majorly aims at predicting the evolution of the defects in rolling stock, tracks for Maintenance Planning, including decision support systems

• The capability of AI applications to apply optimization models in scheduling, route planning, maintenance, and inspection planning there by capturing energy efficiency, verifications, and validations.

• The capability of AI applications, using a wide range of data inputs from sensors, visual images, and traffic movement logs, enables to set future trends in HSE.

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