Predictive Maintenance
Project Scope
- To assess the health state of the equipment and predict whether an equipment is in its last ‘n’ periods of life
- To predict the number of cycles remaining before the equipment completely breaks down
Business Challenges
- Sudden Asset Breakdown and continuous monitoring
- High Skilled Team to predict future analysis
ARi’s Solutions
- Build a scalable data pipeline that is strong enough to accept huge amounts of data and process it
- Process the data from sensors and analyze them in real-time to identify and report critical events to take timely appropriate action
- Technologies Used: Python, AWS/GCP
ARi’s Value Proposition
Reduces the assets downtime and increases the asset efficiency and life span.
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Case Study
Case Studies
Related
https://www.arigs.com/wp-content/uploads/2025/11/Predictive-Maintenance.pdf