//
Category
Enterprise Ai
//
Stack
industrial intelligence
//
Timeline
7 Months
// problem
Ansell faced challenges with disorganized maintenance scheduling, leading to unexpected breakdowns and production disruptions. The lack of tracking for spare parts resulted in overstocking or shortages, increasing costs. Additionally, unpredictable machine failures caused delays and high repair expenses due to the absence of predictive insights.
// How we fixed it
Our AI-powered system optimizes maintenance scheduling, tracks spare parts usage, and predicts potential failures. By leveraging real-time monitoring, predictive analytics, and automated alerts, it minimizes downtime, reduces costs, and enhances operational efficiency.
// How we made it happen
The system is deployed in phases, starting with infrastructure setup and data collection. A mobile app enables technicians to log maintenance activities, while AI models analyze machine data for predictive maintenance. Automated alerts, reporting, and continuous optimization ensure seamless integration and long- term efficiency improvements.
+45%
Efficiency
+35%
Productivity
-2%
Down Time
