An induction motor manufacturing company, requiring a regular maintenance of the induction motors to minimize the wait time. 

Unplanned breakdowns and inefficient maintenance scheduling led to frequent production downtimes and high maintenance costs. The company struggled to balance preventive and corrective maintenance schedules effectively.  

Using predictive maintenance algorithms and optimization models, we developed an adaptive maintenance scheduling system. The model prioritized maintenance tasks based on failure probabilities, cost trade-offs, and production constraints.  

Predictive maintenance reduced unplanned downtime, optimized scheduling, and lowered costs. Equipment lifespan improved, ensuring stable operations and higher efficiency.